Cac cong trinh da cong bo

VIỆN HÀN LÂM KHOA HỌC VÀ CÔNG NGHỆ VIỆT NAM
HỌC VIỆN KHOA HỌC VÀ CƠNG NGHỆ
……..….***…………

TỔNG HỢP
CƠNG TRÌNH KHOA HỌC CĨ
LIÊN QUAN ĐẾN LUẬN ÁN ĐÃ CƠNG BỐ

NGHIÊN CỨU SINH: NGUYỄN MINH CƯỜNG
CHUYÊN NGÀNH: KỸ THUẬT ĐIỀU KHIỂN & TĐH
MÃ SỐ: 9.52.02.16
NGƯỜI HƯỚNG DẪN: PGS. TS. THÁI QUANG VINH

Hà Nội – 2020


-2-

DANH MỤC CƠNG TRÌNH KHOA HỌC CĨ LIÊN QUAN
ĐẾN LUẬN ÁN ĐÃ CÔNG BỐ
1.
Nguyễn Minh Cường, Kiều Thị Khánh, Đặng Danh Hoằng, Nguyễn Đức
Tường, Tổng quan về giải pháp dùng pin sạc dung lượng cao để tiết kiệm năng lượng,
Tạp chí Khoa học và Cơng nghệ ĐHTN, ISSN 1859-2171; e-ISSN 2615-9562, 2017,
Vol. 176 (16).
2.
Lê Tiên Phong, Nguyễn Minh Cường, Thái Quang Vinh, A Method to Harness
Maximum Power from Photovoltaic Power Generation Basing on Completely Mathematical
Model, 2017. International Journal of Research and Engineering, ISSN: 2348-7860 (O),
2348-7852(P), 2018, Vol. 5 No. 8.
3.

Nguyễn Minh Cường, Lê Tiên Phong, Thái Quang Vinh, Dynamic control of
power flow in DC microgrids with the participation of photovoltaic power generation
and battery using power converters, International Journal of Research in Engineering
and Innovation (IJREI), ISSN (Online): 2456-6934, 2018, Vol-2, Issue-5, 484-491.
4.
Nguyễn Minh Cường, Thái Quang Vinh, Lê Tiên Phong, Demand-Side
Management Program with A New Energy Strategy for Photovoltaic and Wind Power
Generation System in Viet Nam, International Journal of Research and Scientific
Innovation (IJRSI) | ISSN 2321-2705, 2018Volume V, Issue X.
5.
Nguyễn Minh Cường, Thái Quang Vinh, Vũ Phương Lan, Lê Tiên Phong,
Optimal Energy Storage Sizing in Photovoltaic and Wind Hybrid Power System
Meeting Demand-Side Management Program in Viet Nam, International Journal of
Research and Engineering, ISSN: 2348-7860 (O) | 2348-7852 (P), 2018, Vol. 5 No. 9.
6.
Nguyen Minh Cuong, Nguyen Thi Dieu Huyen, Thai Quang Vinh, Demand-Side
Management in Microgrids with the Presence of Renewable Sources in Vietnam,
Science Journal of Circuits, Systems and Signal Processing, ISSN: 2326-9065 (Print);
ISSN: 2326-9073 (Online), 2019, Vol. 8, No. 1
7.
Nguyễn Minh Cường, Thái Quang Vinh, Điều khiển bộ biến đổi DC/AC một pha
ghép nối lưới vận hành theo chương trình điều tiết nhu cầu phụ tải, Hội nghị - Triển
lãm quốc tế lần thứ 5 về Điều khiển và Tự động hoá (VCCA-2019), 2019.


Nguyễn Minh Cường và Đtg

Tạp chí KHOA HỌC & CƠNG NGHỆ

176(16): 77 - 80

TỔNG QUAN VỀ GIẢI PHÁP DÙNG PIN SẠC DUNG LƯỢNG CAO
ĐỂ TIẾT KIỆM NĂNG LƯỢNG
Nguyễn Minh Cường*, Kiều Thị Khánh,
Đặng Danh Hoằng, Nguyễn Đức Tường
Trường Đại học Kỹ thuật Cơng nghiệp - ĐH Thái Ngun

TĨM TẮT
Do đặc điểm q trình cơng nghệ, trình độ tay nghề của công nhân, chế độ vận hành và một số yếu
tố khác dẫn tới đồ thị phụ tải ngày của các khách hàng sử dụng điện ít bằng phẳng, điều này làm
cho hiệu quả khai thác hệ thống điện giảm thấp.
Thời gian gần đây, với sự phát triển của công nghệ sản xuất các pin sạc dung lượng cao đã góp
phần nâng cao hiệu quả sử dụng năng lượng. Dùng pin sạc để điều chỉnh biểu đồ phụ tải các hộ
tiêu thụ điện mang lại nhiều lợi ích cho cả bên bán điện và khách hàng sử dụng điện. Bài viết này
các tác giả sẽ nêu tổng quan vấn đề áp dụng pin sạc vào hệ thống điện.
Từ khóa: Tiết kiệm năng lượng; Pin dung lượng cao; Điều chỉnh biểu đồ phụ tải điện

ĐẶT VẤN ĐỀ*
P
Pmax

Pmin
0

5

7

11 14 18 20 22 24

t (giờ)

Hình 1. Đồ thị phụ tải ngày của khách
hàng

Phụ tải điện luôn biến thiên theo thời gian,
đường biểu diễn mối quan hệ giữa công suất
tiêu thụ với thời gian được gọi là đồ thị phụ
tải điện. Có thể phân loại đồ thị phụ tải theo
nhiều cách: Theo đại lượng đo (đồ thị phụ tải
cơng suất tác dụng, phản kháng, tồn phần);
theo thời gian (ngày, tháng, năm hoặc mùa);
theo vị trí trong hệ thống (đồ thị phụ tải của
hệ thống, nhà máy điện, trạm biến áp, hộ tiêu
thụ,…).
Trong bài báo này chúng tôi quan tâm chủ
yếu đến đồ thị phụ tải ngày của các hộ tiêu
thụ điện (Hình 1). Đồ thị phụ tải của các hộ
tiêu thụ do nhiều nguyên nhân như do việc tổ
chức, q trình cơng nghệ, sắp xếp sản xuất
khơng thật hợp lý… Vì vậy, giờ cao điểm
cơng suất yêu cầu quá lớn, còn giờ thấp điểm
*

Tel: 0913 908999, Email:

(sau 23 giờ hôm trước đến 7 giờ sáng hôm
sau chẳng hạn…) công suất yêu cầu lại quá
bé. Nên đồ thị phụ tải thường không thật bằng
phẳng. Cũng chính vì vậy, để nâng cao hiệu quả

sử dụng năng lượng trong quá trình vận hành hệ
thống điện, đồng thời làm cho việc vận hành hệ
thống điện đơn giản và linh hoạt hơn, người ta
tìm cách san bằng đồ thị phụ tải điện.
CÁC BIỆN PHÁP SAN BẰNG ĐỒ THỊ
PHỤ TẢI
Đặc điểm của sản xuất điện năng là sản xuất
và tiêu thụ điện phải thực hiện đồng thời. Tại
mỗi thời điểm, hộ tiêu thụ (kể cả tổn thất) sử
dụng bao nhiêu điện năng thì nhà máy điện
phải sản xuất ra lượng điện năng tương ứng.
Trong thực tế, lượng điện năng tiêu thụ trong
một ngày đêm thay đổi rất nhiều. San bằng đồ
thị phụ tải thực chất là là việc điều chỉnh sao
cho lượng cơng suất phát của nhà máy thay
đổi ít nhất.
Về lý thuyết, những biện pháp chủ yếu để san
bằng đồ thị phụ tải như sau [1], [2]:
- Bố trí các xí nghiệp, nhà máy sản xuất…
làm việc 3 ca để san bằng đồ thị phụ tải xí
nghiệp, nhà máy… giữa ngày và đêm;
- Bố trí ngày nghỉ quy định trong tuần của các
phụ tải như nhà máy, xí nghiệp ... xen kẽ nhau
để san bằng đồ thị phụ tải giữa ngày thường
với các ngày nghỉ thứ 7, chủ nhật;
77


Nguyễn Minh Cường và Đtg

Tạp chí KHOA HỌC & CƠNG NGHỆ

- Hiệu chỉnh giờ bắt đầu làm việc của các phụ
tải (xí nghiệp, nhà máy…) để tránh hiện
tượng mở máy cùng 1 lúc;
- Phát triển các hộ tiêu thụ điện theo mùa;
- Kết nối các nhà máy điện thành hệ thống
điện là biện pháp mang tính chiến lược để
điều chỉnh đồ thị phụ tải điện;
- Sử dụng các nhà máy thủy điện tích năng để
điều chỉnh phụ tải;
- Nâng cao ý thức của từng con người về sử
dụng điện.
Tuy nhiên, các biện pháp này mang nặng tính
lý thuyết, rất khó thực hiện và thực tế cho đến
nay ngành điện và các cơ quan chức năng
chưa thực hiện được nhiều, hiệu quả điều chỉnh
đồ thị phụ tải chưa cao. Việc áp dụng các biện
pháp trên vào thực tế gặp nhiều khó khăn vì thói
quen sinh hoạt, đặc điểm quy trình sản xuất, các
chi phí phát sinh do thay đổi (như tiền lương
tăng thêm đối với ca 3…), ….
DÙNG PIN SẠC DUNG LƯỢNG CAO ĐỂ
ĐIỀU CHỈNH ĐỒ THỊ PHỤ TẢI
Trong thời gian qua, các nguồn năng lượng sơ
cấp truyền thống và nhiên liệu của thế giới
ngày càng cạn kiệt gây ảnh hưởng rất lớn tới
giá thành sản xuất điện. Đồng thời, các nguồn
cấp khí hoạt động khơng ổn định, dự báo thuỷ
văn cho nhà máy thuỷ điện còn nhiều hạn chế

trong khi hệ thống điện khơng có cơng suất
dự phịng dẫn tới tình trạng vận hành khơng
ổn định, ảnh hưởng tới khả năng cân bằng
cung – cầu của toàn hệ thống điện.
Hiện tại, ngành điện đang phải đương đầu với
sự thiếu hụt ngày càng lớn về công suất. Sự
thiếu hụt công suất hệ thống này thường xuất
hiện vào thời gian cao điểm, với phụ tải đỉnh
cao từ 1,8 đến 2 lần phụ tải trong giờ thấp
điểm. Điều này dẫn đến hệ số phụ tải hệ
thống rất thấp và phần lớn yêu cầu đầu tư chỉ
để đáp ứng nhu cầu của khách hàng trong vài
giờ mỗi ngày. Những nỗ lực hiện nay trong
công tác đưa lưới điện quốc gia về nông thôn
và các vùng xa xơi hẻo lánh sẽ càng làm cho
tình hình thêm trầm trọng.
78

176(16): 77 - 80

Để đối mặt với vấn đề này, ngay từ năm
1997, với sự trợ giúp của Ngân hàng Thế giới,
Chính phủ đã thực hiện dự án “Đánh giá tiềm
năng Quản lý nhu cầu ở Việt Nam” với nhiều
chương trình và biện pháp nhằm giảm tối đa
sự mất cân bằng năng lượng.
Một trong những biện pháp đã được triển khai
đó là sử dụng cơng tơ 3 giá với giá bán điện quy
định theo 3 khung giờ: Giờ bình thường; giờ
thấp điểm; giờ cao điểm [4]. Trong đó giá điện

giờ cao điểm gấp gần 3 lần giá giờ thấp điểm.
Bên cạnh đó chính phủ cũng đang có những
chính sách khuyến khích các dự án phát điện
từ năng lượng tái tạo, đặc biệt là năng lượng
gió và mặt trời. Cùng với sự phát triển nhanh
chóng của các hệ thống tích trữ năng lượng,
vấn đề điều chỉnh biểu đồ phụ tải cũng có
hướng đi mới với nhiều triển vọng tốt.
Năm 2015, Tesla một cơng ty đa lĩnh vực
trong đó có thế mạnh sản xuất hệ thống pin
siêu việt đã đưa ra thị trường 2 dịng sản
phẩm Powerwall và Powerpack. Đó là các hệ
thống pin lưu trữ điện năng dung lượng cao từ
10 kWh đến 10 MWh, có thể được nạp từ lưới
điện truyền thống hay từ các nguồn điện năng
lượng tái tạo [5].
Chính vì những lý do trên, biện pháp sử dụng
pin sạc dung lượng cao để điều chỉnh biểu đồ
phụ tải cần được nghiên cứu áp dụng rộng rãi.
Đối tượng ứng dụng pin để điều chỉnh biểu
đồ phụ tải
Qua phân tích trên thấy rằng việc sử dụng pin
để nạp trong khoảng thời gian thấp điểm và
phát vào thời gian cao điểm sẽ làm cho biểu
đồ phụ tải bằng phẳng hơn. Biện pháp này
hầu như không ảnh hưởng đến quá trình cơng
nghệ, đặc điểm sản xuất của khách hàng sử
dụng điện cũng như thói quen sử dụng của
các khách hàng tiêu thụ điện sinh hoạt. Do đó,
hiệu quả nhất khi áp dụng pin sạc để điều

chỉnh biểu đồ phụ tải là (Hình 3):
- Các khách hàng sử dụng điện có biểu đồ phụ
tải mấp mơ, trong đó phụ tải đỉnh rơi vào giờ
cao điểm;


Nguyễn Minh Cường và Đtg

Tạp chí KHOA HỌC & CƠNG NGHỆ

176(16): 77 - 80

P
Pmax

có thể dùng 1 máy biến áp và 1 hệ thống pin
để nâng cao tính liên tục cung cấp điện.

P’max

Ưu điểm của biện pháp

P’min

Đối với khách hàng dùng điện do việc nạp pin
ở thời gian thấp điểm và sử dụng ở thời gian
cao điểm sẽ làm cho chi phí phải trả với cùng
1 lượng điện năng tiêu thụ giảm đi, đồng thời
hiệu quả sử dụng hệ thống cũng được nâng
cao vì hệ số điền kín đồ thị phụ tải tăng.

Pmin
0

5

7

11 14 18 20 22 2 t (giờ)
4

Hình 2. Đồ thị phụ tải sau khi lắp pin

Ví dụ khách hàng dùng điện có đồ thị phụ tải
như Hình 1, nếu sử dụng pin sạc nạp ở giờ
thấp điểm và phát ở giờ cao điểm thì biểu đồ
phụ tải sẽ có dạng như sau (Hình 2):
Nhìn vào biểu đồ sau khi điều chỉnh bằng pin
sạc ta thấy hiệu quả khai thác hệ thống điện
được nâng cao do nâng được hệ số điền kín
biểu đồ phụ tải; đồng thời cơng suất cực đại
yêu cầu được giảm xuống đáng kể, đồ thị phụ
tải tương đối bằng phẳng.
- Các vị trí có thể khai thác các nguồn năng
lượng tái tạo để phát điện;
Các trạm biến áp khách hàng có phụ tải loại
1, thay bằng việc sử dụng nhiều máy biến áp

Đối với bên cung cấp điện khi có nhiều khách
hàng sử dụng pin sạc dung lượng cao để điều

chỉnh biểu đồ phụ tải thì vấn đề mất cân đối
cung cầu ở các giờ cao điểm sẽ giảm đi, áp
lực đầu tư vào nguồn và lưới cũng giảm, khả
năng huy động tối đa các nguồn điện giá rẻ
được nâng cao góp phần làm giảm giá thành
điện năng.
Đối với Nhà nước khi các khách hàng dùng
điện mở rộng, huy động các nguồn năng
lượng tái tạo kết hợp với pin sạc là biện pháp
tốt để đảm bảo an ninh năng lượng, vấn đề an
tồn mơi trường cũng như cơ cấu nguồn điện
phù hợp với quy hoạch phát triển lưới điện
trong tương lai [3].

Hình 3. Sử dụng pin sạc để điều chỉnh biểu đồ phụ tải

79


Nguyễn Minh Cường và Đtg

Tạp chí KHOA HỌC & CƠNG NGHỆ

Nhược điểm
Nhược điểm lớn nhất của biện pháp này đó
chính là giá thành của các pin sạc hiện tương
đối cao. Do đó, để biện pháp này được áp
dụng rộng rãi thì Nhà nước nên có những
chính sách khuyến khích phù hợp sao cho
ngày càng có nhiều khách hàng sử dụng biện

pháp này để điều chỉnh biểu đồ phụ tải.
KẾT LUẬN
Qua phân tích trên, chúng tơi thấy rằng việc
nghiên cứu ứng dụng hệ thống pin sạc dung
lượng cao để điều chỉnh biểu đồ phụ tải mang
lại hiệu quả cao và có tác dụng tích cực trong
việc cắt đỉnh phụ tải trong giờ cao điểm.
Trong bối cảnh hiện nay của nước ta, cùng
với phát triển kinh tế - xã hội nhu cầu tiêu thụ

176(16): 77 - 80

điện tăng nhanh thì đây là một giải pháp quan
trọng trong tổng thể các giải pháp góp phần
đảm bảo cân bằng cung cầu điện góp phần
đảm bảo tăng trưởng kinh tế bền vững và bảo
tồn nguồn nhiên liệu hóa thạch quốc gia.
TÀI LIỆU THAM KHẢO
1. Bùi Ngọc Thư (2002), Mạng cung cấp và phân
phối điện, Nhà xuất bản Khoa học và Kỹ thuật.
2. Nguyễn Hữu Khái (2001), Nhà máy điện và
trạm biến áp, Nhà xuất bản Khoa học và Kỹ thuật.
3. Quy hoạch phát triển điện lực quốc gia giai
đoạn 2011-2020 có xét đến năm 2030 (Quy hoạch
điện VII).
4. Quyết định quy định về giá bán điện, số
2256/QĐ-BCT.
5. />
SUMMARY
OVERVIEW OF SOLUTIONS WITH HIGH-CAPACITY RECHARGEABLE

BATTERY TO ENERGY SAVING
Nguyen Minh Cuong*, Kieu Thi Khanh,
Dang Danh Hoang, Nguyen Duc Tuong
University of Technology - TNU

Due to the characteristics of the technological process, working skill of employees, the operation
mode and some other factors leading to the unbalanced load graph of electricity consumers. This
lowers the efficiency of exploitation.
Recently, the development of high-capacity rechargeable battery technology has contributed to
improving energy efficiency. Using a rechargeable battery to adjust the load chart of power
consumers brings many benefits to both the electricity seller and the customers. This paper reviews
general problems leading to applications of rechargeable batteries to electrical systems.
Keywords: energy saving; High capacity battery; Adjust the load chart

Ngày nhận bài: 01/11/2017; Ngày phản biện: 19/11/2017; Ngày duyệt đăng: 05/01/2018
*

Tel: 0913 908999, Email:

80


International Journal of Research and Engineering
ISSN: 2348-7860 (O) | 2348-7852 (P) | Vol. 5 No. 8 | August 2018 | PP. 486-493
Digital Object Identifier
DOIđ />Copyright â 2018 by authors and International Journal of Research and Engineering
This work is licensed under the Creative Commons Attribution International License (CC BY).
creativecommons.org/licenses/by/4.0 |
|

A Method to Harness Maximum Power from Photovoltaic
Power Generation Basing on Completely Mathematical Model
Author(s): *1Le Tien Phong, 2Nguyen Minh Cuong,
3
Thai Quang Vinh, 4Ngo Duc Minh
Affiliation(s):1, 2, 4Electrical Faculty, Thai Nguyen University of Technology,
Thai Nguyen, Viet Nam, 3 Institute of Information Technology,
Vietnam Academy of Science and Technology, Hanoi
*Corresponding author:
Abstract: This paper introduces a new method that
no previous study has been done in this photovoltaic
power generation similar to this paper to harness
maximum potential power from photovoltaic power
generation. The completely mathematical model
added the relation between diode factor of the
generation and p-n junction temperature is
proposed to use in this method. The maximum
power point tracker combines the iterative and
bisectional technique, the completely mathematical
model of PVG and the system of equations that
converts value of parameters from standard test
condition to any working condition, measuring
sensors to measure power of solar irradiance and pn junction temperature to determine parameters at
maximum power point at any working condition.
The voltage controller is designed to drive this
generation to expect working state to harness
maximum power. An experimental model
corresponding to this method was designed and
operated in real conditions in Viet Nam.
Experimental results show the high accuracy of

analyzing in theory and high capability to bring this
method out real applications to harness all available
energy of this generation.
Keywords: Bisectional technique, voltage controller,
iterative technique, maximum power point, maximum
power point tracker, completely mathematical model,
photovoltaic power generation.

I. INTRODUCTION
Photovoltaic power generation (PVG) has been harnessed in
many different approaches. General blocks for systems

ORIGINAL
ARTICLE

harnessing PVG can be considered as power converters,
maximum power point tracker (MPPT), controllers and
energy storage (ES) or utility to extract maximum power
from PVG. Although maximum power point (MPP) of PVG
has been approached in many techniques, they can be still
classified into online and offline groups [1], [2], [3].
Techniques such as Perturb and Observe (P&O), Incremental
Conductance (INC) or Extremum Seeking Control (ESC),...
are in the online group [1], [2], [3]. These techniques only
give appraisements about MPPs out after being actively
change control pulse for power converters to try the response
of PVG [1], [2]. Due to only using voltage and current
sensors with low cost and easy implementation, these
techniques can be applied for any capacity of PVG without
providing all parameters for controllers but the detective

process causes power loss quite much and is easy to make
wrong appraisements about MPP when power of solar
irradiance (G), p-n junction temperature (T) or voltage at
DCbus (vDCbus) varies [2], [3], [4]. Because of these reasons,
they can't be highly evaluated and applied in applications
having high requirements.
Offline techniques such as Constant Voltage (CV),
Temperature (Temp), Optimal Gradient (OG),... determine
MPP basing on mathematical model of PVG [2], [3], [4], [5].
They have appraisements about MPPs before sending control
pulse to power converters. To decrease power loss caused by
control process, these techniques must be used adequate
information about implemented structure and mathematical
model of PVG, value of (G, T). It means that controllers are
only designed for each system. To have information about G
and T, it must be correctly implemented sensors or chosen
right type of sensors that has a suitable range of wavelength
corresponding to type of PVG. Recently, some
manufacturers have produced pyranometers (PYR) such as
PYR-BTA (a production of Vernier) that can measure G and
be quite suitable for PVG produced from semiconductors.


IJRE | Vol. 5 No. 8 | August 2018 | L. T. PHONG et al.
Moreover, value of temperature at back of the panel is quite
stable and the nearest value of p-n junction temperature so
this is the the best place to implement the temperature sensor
(TempS). So, mathematical model is the biggest problem for
offline techniques.

487
power from PVG [6], [7], [8]. The general structure of the
system is depicted in Fig. 1.
The sun

+

Almost previous studies have not any accurate evaluation
about the relation between currently mathematical model and
publications of manufacturers. It makes mathematical model
of PVG not complete and techniques to determine MPP
basing on mathematical model haven't applied widely.
Recently, the mathematical model was added the relation
between diode factor (n) and T. So, the completely
mathematical model corresponding to the single-diode model
includes series resistor (RS), parallel resistor (Rp), reversed
saturation current (I0), photo-generated current (Iph), thermal
voltage (Vt), relation between n and T, open-circuit voltage
(VOC), short-circuit current (ISC). Value of almost above
parameters is often published by manufacturers or
determined by mathematical tools in standard test condition
(STC), that has G=Gstc=1000 W/m2 and T=Tstc=250C. They
also change corresponding to the variation of (G, T) in real
working conditions and can be determined the rule of
variation in laboratories [1].
Moreover, the iterative and bisectional (IB) technique was
proposed recently and used in MPPT to determine voltage
(Vmpp) and power (Pmpp) at MPP [1], [2]. Vmpp is set as a
reference value to drive current state to expected state (at
MPP). Pmpp is used to test the coincidence of power (ppv)

generating from PVG and Pmpp. The IB technique is
considered as the best way to calculate parameters at MPP
faster and can be applied in any structure of PVG [1], [2].
This paper will present a method to harness energy from
PVG basing on its completely mathematical model. Section
II will introduce the general structure of the system, the IB
algorithm to determine parameters at MPP, system of
equations to convert value of parameters from STC to any
working condition and control strategy for this structure.
Section III will introduce an experimental system using
commercialized devices such as SV-55 panel, PYR-BTA and
LM-35. Experimental results will be represented in section
IV. Conclusions and next research problem will be shown in
section V.

II. METHOD TO HARNESS POWER AT MAXIMUM

DC/DC
converter

PVg
PYR

-

CSpv

TempS

ES

vDCbus

iDCbus

Control pulse
generator
T vpv

G

Vmpp
MPPT

Pmpp

ipv

Measuring
center

+-

Voltage
controller

d

Vmpp
Center of
vpv

ipv dispatching,
Pmpp displaying
and drawing
G
diagrams
T
vDCbus
iDCbus

Fig. 1. General structure of the system
Measuring center collects value of all information provided
by sensors to dispatch and draw diagrams, including:
 Instantaneous currents: ipv at the output terminals of
PVG and iDCbus at the output terminals of the DC/DC
converter from current sensors.
 Instantaneous voltages: vpv at the output terminals of
PVG and vDCbus at DCbus from voltage sensors.
 Instantaneous value of G from a PYR and T from a
TempS.
The combination of the measured information about (G, T)
and the completely mathematical model of PVG helps the IB
technique in MPPT calculate parameters at MPP accurately.
The controller compares instantaneous value of vpv and Vmpp
to decide a suitable control pulse before sending it to the
control pulse generator.
The DC/DC converter is used an adjustable block to regulate
electrical load for PVG that is suitable to the available
maximum power at the considered time (power at MPP).
Voltage at DCbus must be held at a constant value so it has a
big capacity that can absolutely absorb power from the

DC/DC converter and its voltage isn’t affected much by
charging current.

POWER POINT USING THE IB TECHNIQUE

2.1 General structure of the system
To execute the purpose of harnessing all available maximum
energy from PVG (power at MPP), output terminals of PVG
must be connected to a DC/DC converter and an energy
storage (ES) having large capacity to absolutely absorb

Center of dispatching, displaying and drawing diagrams sets
working mode up, collects and displays value of all
instantaneous information measured by sensors, draws
diagrams as required in computer software of management
and control.


IJRE | Vol. 5 No. 8 | August 2018 | L. T. PHONG et al.

488

Table 1. Parameters of a SV-55 panel

2.2 MPPT basing on completely mathematical model
The IB technique uses the detective technique to determine
pair-values of (vpv, ipv) and bisectional technique to reduce
the volume of calculation process in the processor. The IB
algorithm is depicted in Fig. 2 [1], [2].

Type of parameters

Value

Short-circuit current (A)

3.25

Open-circuit voltage (V)

22.14

Voltage at MPP (V)

18.4

Current at MPP (A)

Start

3.06
0

Temperature coefficient of ISC (mA/ C)

Enter parameters of PVg

0

Set initial value of vpv(i)

Calculate value of ppv(i)
i=i+1

vpv(i+1) = vpv(i) + V
vpv(i+2) = vpv(i) + 2V

N
ppv(i+3)–max{ppv(i), ppv(i)+1, ppv(i+2)}<

Calculate ipv(i+1), ipv(i+2)
ppv(i+1), ppv(i+2)

Y
Stop
Pmpp=ppv(i+2)
Vmpp=vpv(i+2)

i=i+1
ppv(i) = ppv(i+1)
vpv(i+3) =
vpv(i+2)+0.5V

Y

ppv(i+1)<

ppv(i+2)

Temperature coefficient of power (%/0C)

-0.451

Photo-generated current (A)

3.2502

Reversed saturation current (A)

1.623x10-8

Thermal voltage at p-n junction (V)

1.141

Series resistor ()

0.151

Parallel resistor ()

1675.9

vpv(i+3)=vpv(i+1)–0.5V

n(T)  1 
N

vpv(i+3)=vpv(i+1)+0.5V

Fig. 2. MPPT basing on the completely mathematical model

In the process of real operation, parameters in the
mathematical model of PVG always change corresponding
to the variation of (G, T), where range of G is from 0 to
1000 W/m2 and range of T is from about 100C to 700C in
Viet Nam. It makes vpv-ipv and vpv-ppv curves vary and MPPs
move continuously corresponding to working conditions.
The variation of parameters is represented by (1) [1], [2]:



-0.743

The relation between n and T is represented in (2):
N

Y
Y

Temperature coefficient of VOC (mV/ C)

Calculate
ppv(i+3)

N
ppv(i)< ppv(i+1)

4.7

G


I ph G,T  G {I phstc1  CTI (T  Tstc)}
stc


 G

ISC
 ISCstc 
 CTI (T  Tstc)
G
,
T
G

 stc



T
Vt
 Vtstc
G ,T
Tstc


G
VOC
 VOCstc1  CTV (T  Tstc)  Vt ln
G,T
G stc



G
R p
 R pstc stc
 G ,T
G

R

R
Sstc
 S G,T



where, values of symbols having
“stc” are defined in STC.
System of equations (1) is used to determine the current state
and helps to construct vpv-ipv and vpv-ppv curves. Considering
a type of PVG, parameters of a SV-55 panel are represented
in Table 1.

91
1
(T  Tstc ) 
(T  Tstc )2
10000
20000

vpv-ipv and vpv-ppv curves of the SV-55 panel in:
case 1 (G varies, T=Tstc) and
case 2 (T varies, G=Gstc) are shown in Fig. 3.

(2)


IJRE | Vol. 5 No. 8 | August 2018 | L. T. PHONG et al.

489

III.

EXPERIMENTAL SYSTEM

3.1 Implementation of the experimental system
Main blocks in the experimental system include:
 SV-55 panel, a production of Scott-Germany.
 PYR-BTA, a production of Verniner.
This device collects power of solar irradiance in visible and
infrared wavelength as describing in Fig. 5. PYR-BTA is a
new device produced some years recently and has a wave
range that is suitable with PVG made from semiconductor
[9].

Signal
converter

a. G changes (T=Tstc)

Đáp ứng theo tần số

PYR-BTA

 (nm)

b. T changes (G=Gstc)

Fig. 3. vpv-ipv, vpv-ppv curves of the SV-55 panel in two cases
2.3 Control strategy for MPPT
Basing on measured and calculated information, a control
strategy for this system to harness all maximum power from
PVG is depicted in Fig. 4.

Fig. 5. PYR-BTA to measure G
The signal converter and cable are provided by Vernier to
convert value of G to voltage signal. Output of the signal
converter is from 0 to 5 V corresponding to G in range
(01000)W/m2 (linear ratio 200 W/m2 per V).
 A temperature sensor with high accuracy, LM-35, is
used in linear ratio [10].

Start

 A main board including a power circuit of DC/DC buck
converter and a measuring circuit. Control center is
ATMega328U microprocessor.

Measure G, T
MPPT (IB technique)

 A battery 12V-35Ah, a production of Dong Nai branch,
is used as an ES.

Vmpp, Impp
Measure vpv

Control strategy for the experimental system is shown in Fig.
6.

Voltage controller
Vmpp-vpv>

N

Y
Maintain vpv=Vmpp
Y

Change (G, T)?
N
Y

Continue

N

Stop

Fig. 4. Control strategy to harness MPP

This strategy combines the control strategy described in Fig.
4 and the characteristic of battery. It has two charging modes.
For the bulk charging mode, charging current can increase to
a high value if it has much power from PVg delivered to
DCbus and the capacity of the battery is smaller than 80%
rated capacity. In the trickle charging mode, charging current
is decreased to a small value to protect the battery.


IJRE | Vol. 5 No. 8 | August 2018 | L. T. PHONG et al.

490

Management / control software is constructed basing on
Kingview 6.5 software to observe instantaneous information
and execute control command from computer. Measured
information is executed in the circuit and transferred to
computer by using RS232 communication protocol and
USB-COM cable. The controller and type of data/diagrams
can be set up or displayed in this management/control
software to have experimental results as required.

Start
Implementation hardware and choose type
of information to draw
Measure vpv, ipv, idc, Vdc, G, T

Vdc < VDCbusref
N

Y
Bulk charging mode

Trickle charging mode

MPPT (IB technique)

Control iDCbus

EXPERIENMENTAL RESULTS

Three experimental sample tests were executed in real
conditions in Thai Nguyen province, Viet Nam. They were
also random sample tests in 20 June 2018. The first one was
taken from 9h09'09" to 9h12'29", the second sample was
taken from 10h06'20" to 10h09'40" and the last sample was
taken from 11h30'50" to 11h34'10". The management/control
displays measured and calculated information, including G,
T, vpv, ipv, vDCbus, iDCbus, Pmpp, ppv, pDCbus.

Vmpp
Control vpv=Vmpp
Charge energy from PVg at output
terminals of DC/DC converter to battery
Calculate ppv, pDCbus, display
and draw diagrams
Y

IV.

Continue?

Experimental results corresponding to sample tests are
represented in Fig. 8, Fig. 9, Fig. 10.

N
Stop

Fig. 6. Control strategy for experimental system
The power generating from PVG and delivering to the
DCbus can be calculated by (3) and (4):
ppv  vpvi pv

(3)

pDCbus  vDCbusi DCbus

(4)

The implementation of above devices is represented in Fig. 7.
SV-55 panel
PYR

TempS

Battery

Control and
power circuit

Computer

Fig. 7. Implementation of the experimental system

Experimental results show that G can vary continuously in
wide range while T varies very slowly as depicted in Fig. 8ab,
Fig. 9ab, Fig. 10ab. Whenever a new value of Vmpp is
provided by MPPT, the voltage controller immediately
changes the control pulse and drives voltage at the output
terminals of PVG to Vmpp to have the coincidence as
described in Fig. 8c, Fig. 9c, Fig. 10c. Because of the effect
of voltage controller, the current at the ouput terminals of
PVG also changes corresponding to the variation of (G, T) và
vpv as shown in Fig. 8d, Fig. 9d, Fig. 10d. Consequently,
amount of power generating from PVG goes through the
DC/DC buck converter, is delivered to DCbus and charges
ES. Value of vDCbus changes very slowly corresponding to the
variation of iDCbus as represented in examples in Fig. 8, Fig. 9,
Fig. 10.


IJRE | Vol. 5 No. 8 | August 2018 | L. T. PHONG et al.

491

a. Diagram of G

a. Diagram of G

b. Diagram of T

b. Diagram of T

c. Diagrams of Vmpp, vpv

c. Diagrams of Vmpp, vpv

d. Diagram of ipv

d. Diagram of ipv

e. Diagram of vDCbus

e. Diagrams of vDCbus

g. Diagram of iDCbus

g. Diagram of iDCbus

h. Diagrams of Pmpp, ppv, pDCbus

h. Diagrams of Pmpp, ppv, pDCbus

Fig. 8. The first sample

Fig. 9. The second sample


IJRE | Vol. 5 No. 8 | August 2018 | L. T. PHONG et al.

a. Diagram of G

b. Diagram of T

492

Results in Fig. 8h, Fig. 9h, Fig. 10h show that p pv diagram
always coincides with the Pmpp diagram and pDCbus diagram is
always lower than Pmpp diagram a bit but they have the same
appearance corresponding to the variation of (G, T). The
reasons for this problem are switching loss and power loss
caused by conductive units in the DC/DC buck converter. It
characterizes for efficiency of the converter and means that
the received power is always smaller than harnessed power at
the output terminal of PVG.
Experimental results prove that the experimental model is
suitable to test the ability to harness all maximum potential
power from PVG. They show the high accuracy for the
process of extraction, the essence of PVG and the DC/DC
buck converter. They also show the ability of high feasibility
and efficiency when this structure is applied in system
having large capacity.

V.

c. Diagrams of Vmpp, vpv

d. Diagram of ipv

e. Diagram of vDCbus

g. Diagram of iDCbus

h. Diagrams of Pmpp, ppv, pDCbus
Fig. 10. The third sample

CONCLUSION

This paper proposes a method to harness all maximum power
from PVG basing on the completely mathematical model of
PVG. This method collects all information about parameters
of used PVG (provided by manufacturer or calculated by
mathematical tools), system of equations converting value of
parameters from STC to any working condition and
measured information about working state of whole system.
A control strategy to harness all maximum power from PVG
is proposed, where the IB technique combines the completely
mathematical model and IB technique in MPPT to accurately
calculate parameters at MPP and timely provide desired
value for the voltage controller.
An experimental model is introduced and the control strategy
for the experimental system is proposed in this paper.
Experimental results are shown in three samples to see the
role of MPPT and controller in this model. The controller
always tracks accurately and fast corresponding to the
variation of (G, T) and makes ppv track Pmpp accurately at any
time. The coincidence of measured quantities and calculated
quantities shows the accuracy of choosing type and location
to install of sensors to measure (G, T) and the accuracy of the
completely mathematical model of PVG and the IB

technique in MPPT.
The success of the experimental model shows the feasibility
of the proposed structure in real operation with many
different capacities. To use the proposed method, panels of
PVG must be installed in the same direction, work in
unshaded or uncorrupted cells and particularly design
controller for each structure of PVG. It shouldn’t be design
one controller for large scale because the accuracy of this
method depends much on measured quantities and
surrounding factors that can affect to the working mode of


IJRE | Vol. 5 No. 8 | August 2018 | L. T. PHONG et al.
PVG such as clouds shading panels or difference of
temperature on panels. In the future research, this method
can be applied in problem of demand-side management for
hybrid systems.

VI.

ACKNOWLEDGEMENT

This study is partly supported by Science research project
(ID: DH2018-TN02-02), Thai Nguyen University, Viet Nam.

VII.

DECLARATION

Authors have disclosed no conflicts of interests.

REFERENCE
[1]

[2]

[3]

[4]

[5]

[6]

[7]

[8]

Le Tien Phong (2018), “A Study on Methods to
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photovoltaic power generation”, Dissertation for the
degree Doctor of Philosophy on Control Engineering
and Automation, Thai Nguyen University of
Technology.
Le Tien Phong, Ngo Duc Minh, Nguyen Van Lien
(2017), “Improving Efficiency and Response of
Photovoltaic Power Generation with DC/DC Buck
Converter”, International Journal of Engineering
Research and Technology, ISSN: 2278-0181, Vol. 6,
Issue 3.

Ali Reza Reisi, Mohammad Hassan Moradi, Shahriar
Jamasb (2013), “Classification and comparison of
maximum power point tracking techniques for
photovoltaic system: A review”, Renewable and
Sustainable Energy Reviews, ISSN: 1364:0321, Vol.
19.
Pawan D. Kale, D.S. Chaudhari (2013), “A Review
on Maximum Power Point Tracking (MPPT)
Controlling Methods for A Photovoltaic System”,
International Journal of Emerging Science and
Engineering, ISSN: 2319–6378, Volume. 1, Issue. 5.
Jiyong Li, Honghua Wang (2009), Maximum Power
Point Tracking of Photovoltaic Generation Based on
the Optimal Gradient Method, International
Conference IEEE ComManTel 2015 placed in Da
Nang Province and IEEE Xplore, ISSN: 2157-4847.
Hisham Mahmood, Dennis Michaelson, and Jin Jiang
(2012), “Control Strategy for a Standalone
PV/Battery Hybrid System”, IECON 2012 - 38th
Annual Conference on IEEE Industrial Electronics
Society, ISSN: 1553-572X.
Nabil Karami (2013), “Control of a Hybrid System
Based
PEMFC
and
Photovoltaic
Panels”,
Dissertation for the degree Doctor of Philosophy,
Aix-Marseille University.
Teresa Orłowska-Kowalska,

Frede Blaabjerg,
José Rodríguez (2014), “Advanced and Intelligent

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[9]

[10]

Control in Power Electronics and Drives”, Springer
Publisher, Volume 531, ISBN 978-3-319-03401-0.
Vernier
(2013),
/>Texas Instrument (2013), “LM35 Precision
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Temperature
Sensors”,
/>

International Journal of Research in Engineering and Innovation Vol-2, Issue-5 (2018), 484-491
__________________________________________________________________________________________________________________________________

International Journal of Research in Engineering and Innovation
(IJREI)
journal home page:
ISSN (Online): 2456-6934

_______________________________________________________________________________________

Dynamic control of power flow in DC microgrids with the participation of

photovoltaic power generation and battery using power converters
Nguyen Minh Cuong1, Le Tien Phong2, Thai QuangVinh3
1Electrical

Faculty, Thai Nguyen University of Technology, Thai Nguyen city, Viet Nam
Electrical Faculty, Thai Nguyen University of Technology, Thai Nguyen city, Viet Nam
3Institute of Information Technology, Vietnam Academy of Science and Technology, Ha Noi capital, Viet Nam
2

_______________________________________________________________________________________
Abstract
This paper designs a hybrid system with the participation of photovoltaic power generation and battery that can regulate flows of
power in a two-source DC microgrid. A center of measuring and hybrid dynamic control basing on analyzing power-flow cases
and characteristic of the generation is constructed to hold voltage at DCbus at a fixed value and make power ratio delivered from
each source track the reference value to resolve demand-side management program. Power converters are used as main blocks to
harness maximum available power from the generation and regulate flows of power in whole DC microgrid. An experimental
model is also designed including power and control circuits and the center of hybrid dynamic control to observe working states or
change the working modes as natured or required. Experimental results prove the good adaptability to different tasks of the center
of hybrid dynamic control and the good capability to analyze power flow in whole system as designed. They also prove that the
proposed structure and center of hybrid dynamic control are able to apply to meet demand-side management problem in large
systems when combined with forecasting systems of load and available power of photovoltaic power generation in considered
period time.
© 2018 ijrei.com. All rights reserved
Keywords: Demand-side management, DC microgrid, hybrid control system, power-flow control, photovoltaic power generation,
power converter.
_________________________________________________________________________________________________________
1.

Introduction

Photovoltaic power generation (PVG) can be harnessed in
isolated or grid-connected systems. It is also coupled with
energy storage (ES) such as battery, fuel cell, supercapacitor,
or other generations to construct hybrid systems. In these
systems, power converters play an important role to extract
energy at maximum power point (MPP), synchronize with the
utility, and regulate power flow as required or dispatched and
meet intelligent requirements at each node in the smart grid
[1-5].
The IB-AVC method is a new approach that helps to extract
all available power of PVG. Because of combining the
iterative and bisectional technique in the maximum power
point tracker (MPPT), the average voltage control technique
and using information provided by a pyrometer (PYR) and
temperature sensor (Temp), IB-AVC method can help to

Corresponding author: Le Tien Phong
Email Address:

bring dynamic control of power flow from PVG at any
variation of power of solar irradiance (G) and p-n junction
temperature (T). Because it actively calculates parameters at
MPP before creating control pulse to regulate DC/DC
converter, it can help to reduce power loss in the circuit and
avoid losing control signal when predicting wrong movement
of working points caused by the variation of (G, T) or value
of voltage at DCbus as traditional methods. For this reason,
IB-AVC is one of best method to exploit all available energy
of PVG [6].
DC/DC converters (buck, boost, buck-boost, one or

bidirectional) and DC/AC converters (single or three phases)
are often used in systems harnessing PVG. Input terminals of
DC/DC converters are directly connected to PVG and their
output terminals are connected to an ES or utility. Power
from PVG goes through DC/DC converters, charges ES,
directly provide for AC load in isolated system or deliver to

484


Nguyen Minh Cuong et al / International Journal of Research in Engineering and Innovation (IJREI), Vol 2, Issue 5 (2018), 484-491

utility. So, DC/AC converters convert DC current/voltage to
AC current/voltage that has the suitable frequency for AC
load and utility. Controllable switches (SW) placed in above
converters must be changed on and off states in each duty
cycle to conduct flows of power as calculated by controllers
[1-5].
Value of exchanged power at each node can be required by
dispatchers or continuously provided by demand-side
management (DSM) program to harness optimal capacity of
all blocks [7-9]. In two-source DC hybrid microgrids, an
working schedule in considered period time will be created
basing on rated, measured and predicted information to
provide expected values to controllers and balance sources on
power. Moreover, flow of power from each source in this
microgrid can change depending on natured or required
mode. For natured mode, the difference between values of
voltage and capacity of sources decides the distribution of
power in these system. For required mode, the amount of

power or proportion of power (POP) can be set up by the
operator or DSM program. For this reason, a center of hybrid
control system (HCS) at each node must be designed by
collecting all controllers to optimize flows of power in whole
system. Due to the variation of (G, T) and electrical load,
HCS also execute dynamic control of power flow at any time
to meet electrical load and solve DSM program. Moreover,
flows of power are often analyzed as natured depending on
impedance or the difference of voltages [7], [8] so there has
not had any deep study yet to give out a clear method to
accommodate as required. With the participation of PVG, the
power-flow distribution becomes more complexly and it
needs to build a method to accommodatethe time of
charging/discharging for ES and make a working plan in long
time. According to the advantages of power electronic,
control of power flow in DC microgrids can be done
completely by using DC/DC converters.
To overcome above problem, this paper will design a system
and a center of measuring and HCS to supply electric for AC
load in an isolated microgrid. This system has two sources,
where one source has the participation of PVG and another
source characterizes for a balanced source. HCS will gather
problems of harnessing MPP of PVG and controlling flows of
power in a DC microgrid using power converters to adapt the
DSM program. The second section will introduce the scheme
system including general structure, power sharing control
strategy and control scheme. The third section will represent
an experimental model that helps to distribute flows of power
as natured or required. Experimental results will be shown in
the fourth section. The last section will represent some

conclusions, contributions and future study.
2.

Scheme system

2.1 Organization
The considered a microgrid has two sources, where source 2
plays a role of balancing power and source 1 is a combination

of PVG and ES. SWs in DC/DCpv, DC/DCs1, DC/DCs2
converters are controlled by a center of measuring and HCS.
General structure of the system is represented in Fig. 1.
DC/DCs2
converter

Source 2
is2

vs2

DCbus
ACbus

SW

DC/AC Transformer
converter

CSs2

SW

DC/DCs1
converter

Filter

CSac

SW

vDCbus

iac

vac

CSs1

Data display
and draw
diagram

Center of measuring and HCS
is1

vs1

CSpv

AC
load

ipv

vpv
G T

PCC SW
DC/DCpv
converter

Control signal
PVG

ES

Measured signal
Source 1

Figure 1: General structure

The center of measuring collects information measured by
sensors to dispatch and draw diagrams, including:
 Current sensors provide instantaneous values of currents
about is1 and is2 generated from sources, iac at ouput
terminals of DC/AC converter, ipv generated from PVG.
 Voltage sensors provide instantaneous values of voltages
about vs1 and vs2 at output terminals of sources, vac at
output terminals of the transformer, vpv at output

terminals of PVG and vDCbus at DCbus.
 PYR provides instantaneous value of G and temperature
sensor provide instantaneous value of T.
Center of HCS includes 4 different controllers for DC/DCpv,
DC/DCs1, DC/DCs2 and DC/AC converters. Controllers that
create control signals CSpv, CSs1, CSs2 and CSac co-ordinates
to each other to execute requirements of the operator or DSM
program.
2.2 Power sharing control strategy
In two-source system with the participation of PVG as
depicted in Fig. 1, information about a reference value of
POPref (proportion of power between power from source 1
and source 2) or working mode (natured or required) can be
set up. Center of HCS collects all measured information to
work power-flow cases in whole system as represented in Fig.
2.
Where: ppv, pES, ps1, ps2 are instantaneous values of power
from PVG, ES, source 1 and source 2. Continuous lines show
the positive value of power, dash lines show the zero value of
power.

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Power in whole system will be distributed and controlled by
the center of HCS in the following rules:
ps2

ppv

pac
PCC

ps2

ppv

ps1

AC
load

pES

pac
PCC ps1
pES

a. Case 1
ps2

ppv

ppv
pac

PCC

ps1

b. Case 2
ps2
pac

AC
load

PCC

ps1

AC
load

pES

pES

d. Case 4
ps2

c. Case 3
ppv

AC
load

ppv

ps2
pac
PCC ps1

AC
load

PCC

ES will be merged to become source 1. Flows of power in
this source depend on required power that must be mobilized
from source 1 at each time. Moreover, power from source 1
or source 2 depends on the requirement of AC load, ability to
generate power of PVG and working mode (change control
signal of CSpv, CSs1 to control SWs placed in DC/DCpv and
DC/DCs1 converters). Voltage at DCbus is controlled to
maintain at a reference value VDCbusref by sending control
signal CSs2 to drive SW placed in the DC/DCs2 converter.
Furthermore, control signal CSac is determined to change on
and off states of SWs placed in the DC/AC converter in each
duty cycle to create AC signal (frequency is 50 Hz) at output
terminals [10], [11], [12]. Power flow (p ac) going through the
DC/AC converter is power of AC load and loss in the
transformer and switching loss.
Control strategy for center of HCS is represented in Fig. 3.

AC
load

ps1

Start

pES

pES
e. Case 5

ppv

ps2

ppv

pac
PCC

ps1

Implement hardware and choose type of
information to draw

g. Case 6
ps2
pac

AC
load

PCC

ps1

Enter POPref and VDCbusref

AC
load

Collect information about is1, vs1, is2, vs2, ipv, vpv, iac,
vac, vDCbus, G, T from sensors

pES

pES

i. Case 8

h. Case 7

Active controller for DC/DCpv converter to harness
power at MPP

Figure 2: Power-flow cases



Power harnessed at MPP of PVG goes through the
DC/DCpv converter to point of common coupling (PCC)
in source 1 as depicted in case 1 (Fig. 2a), case 2 (Fig.

2b), case 4 (Fig. 2d), case 5 (Fig. 2e), case 7 (Fig. 2h),
case 8 (Fig. 2i).
 Power Ps1 from source 1 can be the sum of both PVG and
ES as depicted in case 1 (Fig. 2a) and case 4 (Fig. 2d)
when power at output terminals of the DC/DCpv
converter is smaller than ps1 or only PVG as depicted in
case 2 (Fig. 2b) and case 5 (Fig. 2e) when power at
output terminals of the DC/DCpv converter is equal ps1 or
only ES as depicted in case 3 (Fig. 2c) and case 6 (Fig.
2g) when there is not any power from PVG (value of G
is too small).
 Power of AC load can be supplied by both sources as
depicted in case 1 (Fig. 2a), case 2 (Fig. 2b) or case 3
(Fig. 2c) when POPref is set up by the operator or DSM
program.
 Power of AC load can be only supplied by source 1 as
depicted in case 4 (Fig. 2d), case 5 (Fig. 2e), case 6 (Fig.
2g) as required by the operator or DSM program (source
2 is to reserve).
 There is redundant power from PVG that charges ES
after supplying power Ps1 as depicted in case 7 (Fig. 2h)
and case 9 (Fig. 2g).
Above analysis shows that PVG, the DC/DCpv converter and

Active controller for the DC/DCs2 converter to
control vDCbus
Active controller for the DC/DCs1 converter to
control propotion of power from source 1
Active controller for DC/AC converter to change
DC current into AC current

Y

Change POPref or/and VDCbusref
N
Continue
N
Stop

Y

Figure 3: Control strategy for center of HCS

2.3 Control scheme
As above analysis, IB-AVC method is one of the best method
to harness power at MPP for PVG. Using information about
(G, T), value of voltage at MPP is always accurately
determined by the IB technique in MPPT to provide a desired
destination for the controller of the DC/DCpv converter. Value
of Pmpp determined by MPPT is used to compare with
instantaneous value of ppv to evaluate the ability to track MPP
at any working condition. The controller for the DC/DCpv
converter using the IB-AVC method was tested and evaluated

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very carefully to highly meet the dynamic requirement for the
process of harnessing MPP [6]. So, designing controllers for

DC/DCs1 and DC/DCs2 converters is an important task to
control flows of power. The principle to design the control
structure is that controller for the DC/DCs2 converter
considers source 2 as a large and stable source to regulate
voltage at DCbus at value of VDCbusref (set up by the operator)
and the controller for the DC/DCs1 converter regulates the
value of ps1to reach value of POPref. Control structure to
regulate VDCbusref and POPref is represented in Fig. 4.
POPref
+

-

Power is1ref
controller

+

Control pulse
Current
generator
controller d
s1

-

CSs1









is1
PoP
a. For DC/DCs1 converter
VDCbusref

+

-

Voltage
controller

ds2

Control pulse
generator

sending control signal to pulse driver.
Batteries are used in this model to characterize for source
2 and ES in source 1. Their capacity is 35 Ah and
nominal voltage is 12V (a production of Dong Nai
branch).
AC load is an electric motor. The nominal power is 40W
and the nominal voltage is 220V.

A power transformer is used in this model to stepvoltage
up and filter harmonic. Winding ratio of high side and
low side is 760/28. Diameter of high voltage side
winding is 0.45 mm and diameter of low voltage side is
2.1 mm.
OWON digital oscilloscope is used to measure voltage
waveform of high and low voltage side of the
transformer.The implementation of the model is depicted
in Fig. 5.

CSs2

vDCbus
b. For DC/DCs2 converter

Figure 4: Control structure for DC/DCs1 and DC/DCs2 converters

3.

Experimental model

3.1 Implementation of the experimental model
An experimental model is designed to test the ability to
control flows of power in the DC microgrid in accordance
with the DSM program. Main blocks in the experimental
model are:
 A SV-55 panel (a production of Scott-Gemany).
Parameters of SV-55 panel defined in STC is shown in
Table 1.
Table 1. Parameters of a SV-55 panel

Type of parameters
Value
Short-circuit current (A)
3.25
Open-circuit voltage (V)
22.14
Voltage at MPP (V)
18.4
Current at MPP (A)
3.06
Temperature coefficient of ISC (mA/0C)
4.7
Temperature coefficient of VOC (mV/0C)
-0.743
Temperature coefficient of power (%/0C)
-0.451
Photo-generated current (A)
3.2502
Reversed saturation current (A)
1.623x10-8
Thermal voltage at p-n junction (V)
1.141
0.151
Series resistor ()
1675.9
Parallel resistor ()




Sensor to measure G is PYR-BTA (a production of
Vernier), sensor to measure T is LM-35 (a production of
National Semiconductor).
A power and control board for the DC/DCpv converter, a
power and control board for DC/DCs1, DC/DCs2 and
DC/AC converters. ATMega328U microprocessors are
placed in above boards to calculate and decide before

a. Power and control circuit

b. PVG and PYR
Figure 5: Implementation of the experimental model

Center of HCS is combined by the program for DC/DC pv
converter to regulate PVG and the program for DC/DCs1,
DC/DCs2 and DC/AC converters. A control/management
program is designed by the Kingview 6.5 software in the
laptop to observe instantaneous information and send control
signal to the board. Measured information is transfered from
boards to laptop by RS232 communication. The operator
directly sets value of POPref and VDCbusref up and selects
working buttons (called auto and manual buttons) in the
control/management program that help to study natured and
required distribution.
4.

Experimental results

The first and the second sample tests were executed in 20
June 2018 to study flows of power in the natured mode. In

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Nguyen Minh Cuong et al / International Journal of Research in Engineering and Innovation (IJREI), Vol 2, Issue 5 (2018), 484-491

these tests, the operator switches to the auto button in the
program. The first sample test, from 7:26:06 to 7:29:26 (T
was near a constant and approximately 350C), the value of
VDCbusref was hold at 4 V (constant) while value of
POPrefchanged in three levels (decreased from 80% to 50%
and then increased up to 90%). The second sample test, from
7:50:48 to 7:54:08 (T was near a constant and approximately
440C), value of POPref was hold at 90% while value of
VDcbusrefwas changed in three levels (increased from 4 V to 6
V and then decreased to 5 V). The experimental results in
these sample test are represented in Fig. 6 and Fig. 7. These
results show that values of is1, is2, ps1, ps2 can not be affected
by values of POPref. Corresponding to the variation of (G, T),
power from PVG tracked MPP correctly (p pv diagram
coincided Pmpp diagram) and power delivered to PCC was
smaller than ppv due to the power loss in the DC/DCpv
converter). Because value of voltage on source 1 is always
higher than it on source 2 and there has the participation of
PVG, almost pac power always provided by source 1. In both
these two sample tests, The controller for the DC/DC s2
converter helped to drive vDCbus to VDCbusref accurately and
flow of power from source 2 only occupies a small ratio even
when AC load increases (accordance with increasing
vDCbusref). It means that the controller for the DC/DC pv

converter worked very well in the extraction process to
harness all maximum power from PVG and flows of power
between sources distributed naturally.
The third and fourth sample tests were also executed in 20
June 2018 to study the required mode. In these tests, the
operator switches to the manual button in the program. The
third sample test, from 9:59:16 to 10:02:36 (T was near a
constant and approximately 460C), the value of VDCbusrefwas
changed in three levels (increased from 5 V to 6 V and then
decreased to 5 V) while value of POP ref was also changed in
three levels (decreased from 80% to 50% and then increased
up to 90%). The fourth sample test, from 10:32:14 to
10:35:34 (T was near a constant and approximately 43 0C), the
value of VDCbusref was changed in four levels (decreased from
7 V to 6 V and then increased to 7.5 V and finally decreased
to 6 V) while value of POPref was hold at 60%. The results in
these sample test are represented in Fig. 8 and Fig. 9. These
results show that values of is1, is2, ps1, ps2 are highly affected
by values of POPref and vDCbusref. Similar to the first and
second sample test, power from PVG tracked MPP correctly
(ppv diagram coincided Pmpp diagram) and power delivered to
PCC was smaller than ppv due to the power loss in the
DC/DCpv converter). The controller for the DC/DCs2
converter helped to drive vDCbus to VDCbusref accurately
although vDCbus must be taken a short time to track VDCbusref.
Power from sources changed correctly in accordance with the
increase or decrease of POPref. It means that flows of power
in this model distributed very exactly as required, help to well
prove the ability to regulate power flow in the DC microgrid
using power converters.

(a) Diagram of VDCbusref

(b) Diagram of POPref

(c) Diagram of vDCbus

(d) Diagrams of vs1 and vs2

(e) Diagrams of is1 and is2
G

(g) Diagrams of G

(h) Diagrams of Pmpp, ppv, pDCbus

(i) Diagrams of power through DC/AC converter and ps1, ps2
Figure 6: The first sample test

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Nguyen Minh Cuong et al / International Journal of Research in Engineering and Innovation (IJREI), Vol 2, Issue 5 (2018), 484-491

(a) Diagram of VDCbusref

(a) Diagram of VDCbusref

(b) Diagram of POPref

(b) Diagram of POPref

(c) Diagram of vDCbus

(c) Diagram of vDCbus

(d) Diagrams of vs1 and vs2

(d) Diagrams of vs1 and vs2

(e) Diagrams of is1 and is2

(e) Diagrams of is1 and is2

(g) Diagram of G

(g) Diagram of G

(h) Diagrams of Pmpp, ppv, pDCbus

(h) Diagrams of Pmpp, ppv, pDCbus

(i) Diagrams of power through DC/AC converter and ps1, ps2
Figure 7: The second sample test

(i) Diagrams of power through DC/AC converter and ps1, ps2
Figure 8: The third sample test

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Nguyen Minh Cuong et al / International Journal of Research in Engineering and Innovation (IJREI), Vol 2, Issue 5 (2018), 484-491

(a)Diagram of VDCbusref

Using OWON digital oscilloscope, wave forms of AC voltage
signal at terminals of the transformer (red line for low voltage
side and yellow line for high voltage side) are represented in
Fig. 10. Wave form of AC voltage signal contains high
harmonic content at the low voltage side and low harmonic
content at the other side because the transformer plays an
important role of filting harmonic. It can help to reduce
harmonic before providing electric for AC load. Moreover,
the controller for the DC/AC converter worked very well
because it provided the standard frequency (50 Hz).

(b) Diagram of POPref

(c) Diagram of vDCbus

Figure 10: Wave forms of AC voltage signal

5. Conclusion
(d) Diagram of vs1 and vs2

(e) Diagram of is1 and is2

(g) Diagram of G

(h) Diagrams of Pmpp, ppv, pDCbus

(i) Diagrams of power through DC/AC converter and ps1, ps2
Figure 9: The fourth sample test

This paper proposed a hybrid system that has the participation
of PVG and designed a center of measuring and HCS. Flows
of power in whole system can be analyzed as natured or
required by the operator or DSM program using power
converter. The center collected all measured information and
determined suitable control pulse for DC/DCpv, DC/DCs1,
DC/DCs2, DC/AC converters. All controllers in HCS correctly
coordinated to harness power at MPP of PVG, regulate values
of VDCbusref and POPref and create a suitable AC signal to
provide electric for AC load.
An experimental model including power and control circuits,
motor load, transformer, batteries, SV-55 panel and computer
was designed to depict the proposed system. Experimental
results showed the capacity of analyzing power flow as
natured or required. For natured, mobilized power from each
source depends on the power generating from PVG and the
voltage difference of sources. For required, the mobilized
power from each source always accurately track the reference
value not depending on power from PVG. It showed the
flexibility of HCS in a complex system that have the
participation of multi generations. Due to the participation of
PVG, voltage at PCC (source 1) was always higher than
voltage of source 2. It showed the correct characteristic of the
battery when it has a power delivered to its input terminals.
Experimental results in sample tests show the experimental
model is suitable to operate a hybrid system in DSM problem

using power converters. The study of control design for
power converters in the hybrid system represents a correct
direction to harness power at MPP and regulate power flow in

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whole system and create AC signal to adapt AC load in
isolated systems. It also shows the correct approach and
feasibility of DSM problem in system harnessing renewable
energy. This model can be enlarged and developed to apply in
large system to enhance the capacity of devices and make
intelligent for each bus in whole system.
Acknowledgement
This study is partly supported by Science research project
(ID: DH2018-TN02-02), Thai Nguyen University, Viet Nam
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International Journal of Research and Scientific Innovation (IJRSI) | Volume V, Issue X, October 2018 | ISSN 2321–2705

Demand-Side Management Program with A New
Energy Strategy for Photovoltaic and Wind Power
Generation System in Viet Nam
Nguyen Minh Cuong1, Thai Quang Vinh2, Le Tien Phong3
1, 3

Electrical Faculty, Thai Nguyen University of Technology, Thai Nguyen, Viet Nam
Institute of Information Technology, Vietnam Academy of Science and Technology, Hanoi

Corresponding Author: Le Tien Phong

2

Abstract— This paper proposes a new energy strategy to
distribute energy at each bus in Viet Nam electric power system
with the participation of photovoltaic and wind power
generations. A structure for this system is also constructed
including some main blocks: power circuit, forecasting center
and center of measurement, dispatch and control. Each block
closely works together with others and energy storage to have a
balance power at any time in whole considered cycle. A demandside management algorithm is designed corresponding to a case
study that has energy from the generations smaller than
consumed energy of electric load in whole time stages. In this
algorithm, the deficient energy in stages having high and
medium electric price levels can be bought from the electric
power system to charge to the energy storage in the stage having
low electric price level to reduce the economic function.
Simulation results were carried out by the MATLAB 2017a
software to show the feasibility of the demand-side management
program to re-dispatch power flows in whole system and bring
out high economic effectiveness.
Index Terms— Demand-side management, dispatch power flow,
photovoltaic power generation, wind power generation, hybrid
system.

I. INTRODUCTION

R

enewable energy is considered as a effective solution to
prolong life on earth when traditional energy sources
become to exhaust. Although there are many types of
renewable sources, photovoltaic power generation (PVG) and
wind power generation (WG) are the most potential sources
because they can be installed anywhere in the world and are
constantly present during the day. They can be combined
together into a hybrid generation system to support each other
and enhance the ability to supply electricity because WG can
generate electricity at any time while PVG can only generate it
when daylight is present. With the combination of power
converters, control and communication techniques and energy
storage (ES), power flows in whole system can be dispatched
and operated by using the model of smart grid via a demandside management (DSM) program.
Unlike traditional electric power system (EPS), smart grids
uses the DSM program and forecasting data to determine
values of power that will receive from generations or be
consumed by electric load before entering the working cycle.

www.rsisinternational.org

There are much forecasting data in this structure such as power
of solar irradiance, ambient temperature, wind speed and other
factors of weather condition. All data must be forecasted in a
high accuracy to make a schedule for control and energy
management. One of the most important device in this
structure is ES and the its sizing must be enough large to
completely compensate for the deficient energy of load as
required. Because of having the support from ES, power
directions between DCbus and ES, DCbus and ACbus are

calculated and controlled by the DSM program as required [16].
In Viet Nam, there are three electric price levels for
customers. To buy electricity, they must be one of the
following objects: provided by transformers having rated
power more than 25 kVA, having average electric
consumption in three continuous months more than 2000 kWh
per month, saling electricity at industrial zones, buying
electricity to sale for other purposes at commercial, service and
living complex. Three levels can help to promote the electric
consumption in the stage having low price level and limiting it
in stages having medium and high price levels [7], [8].
Recently, forcasting centers can provide quite accurate
values of forecasting data due to using many modern
measurement devices, history of data in many years and
mathematical tools. They can help to completely optimize
power flows in whole system and make minimum cost for
buying electricity and maximum profit from saling it [9], [10],
[11], [12], [13]. Although there are many reseaches about
applying the DSM program in hybrid systems harnessing PVG
and WG but it must be met requirements of each country.
Until now, it hasn't had any complete research about this
problem in Viet Nam.
In this paper, a new DSM program is proposed for hybrid
generation systems at any bus applied in Viet Nam EPS. The
purpose of this program is to ensure the ability to meet
requirements of energy supply for electric load. The next
section will introduce the system scheme and the relation of
power quantities in the process of power conversion. The
section III will represent a new strategy to distribute power
flows in whole system applied in Viet Nam in accordance with

a case study of deficient energy in all stages. This section will

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International Journal of Research and Scientific Innovation (IJRSI) | Volume V, Issue X, October 2018 | ISSN 2321–2705
also construct a method to evaluate economic effectiveness of
the DSM program. Section IV will demonstrate some
simulation results. The last section will show some conclusions
and propose the problem for next researches.

II. SYSTEM SCHEME AND POWER CONVERSION
2.1 System scheme
The structure of the hybrid power generation system is
represented in Fig. 1. It has DC coupled structure with three
main blocks for power circuit, forecasting, measurement,
dispatch and control with [1-6].
Block 1: Forecasting center

Forecast
G
Forecast
temperature,
cloud, rain,..

Forecast electric load

Forecast
wind speed

Block 2: Center of measurement, dispatch and control
- Collect information from block 1.
- Collect instantaneous parameters in the working operation from measurement devices: G from PYR, T from
TempS, current and voltage at buses from voltage and current sensors.
- DSM program to dispatch power flows in whole system.
- Controllers to determine control signal that carry out the DSM program.

Send
instantaneous
control signal
from controllers

Measure
instantaneous
parameters
g1

PVG

PPVG

Power converters
for PVG

PWG

Power converters
for WG

~

PWGconv

2
PES
ES

PES

Bidirectional
converters for ES
2

ACbus
PDC

g2
WG



PPVGconv

PESdc

PDC

PEPS

Grid-connected

converter

PEPS



DC
load

EPS

~
AC
load
PACload



PESdc

Equivalent
load
DCbus
Pload

Block 3: Power circuit

Fig. 1 System scheme


Block 1 provides diagrams about forecasting values
of working parameters at any time in the considered
cycle (time length is ). They include G, T, wind

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speed, cloud... and the variation of electric load. This
block must use programs basing on their values in the
past, mathematical models, intelligent algorithms and

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International Journal of Research and Scientific Innovation (IJRSI) | Volume V, Issue X, October 2018 | ISSN 2321–2705





forecasting devices to show values that will receive in
the future [9-13].
Block 2 collects all instantaneous information about
operating states of whole system from sensors such as
current through each branch, voltage at buses to
regulate control signals. These signals are sent to
controlable switches placed in power converters to
execute all requirements of the DSM program:
harnessing maximum power from hybrid power
generation, supplying electricity for load, holding
voltage at DCbus as a constant value, synchronizing

to the grid.
Block 3 has power converters to regulate power for
PVG and WG, bidirectional power converter for ES
to regulate power for charging/discharging ES and
bidirectional power converter to interact power with
the grid. These converters must be co-ordinated
closely to meet all operating requirements

The DSM program is placed in the second block to make a
schedule of power flows in all cycle at any time for all units in
the system. The redundant energy of hybrid power generation
system or ES will be generated to EPS or the deficient power
will be bought from EPS.
2.2 Energy conversion
When currents go through power circuits, they always
cause power losses in conductive units and switching power
loss. They can be characterized by the following quantities:




g1 and g2 for the efficiency of energy conversion in
the process of harnessing PVG and WG,
 for for the efficiency of energy conversion in the
process of interacting power between DCside and
ACside (same value in both two directions).
2 for the efficiency of energy conversion in the
process of interacting power between DCbus and ES
(same value in both two directions).





The relation of above stages and electric price is
represented in Fig. 2.

Fig. 2 The relation of stages and electric price in Viet Nam

We can see the electric price in the H-stage (3=2862
VND/kWh) is nearly three times it at the L-stage (1=1004
VND/kWh) and nearly twice it at the M-stage (2=1572
VND/kWh).
Due to the development of electric market and renewable
sources, EPS in Viet Nam also sets values of buying electric
from renewable energy. This paper considers that they are
same for PVG and WG to have a target to evaluate benefit
received from generations.
3.2 DSM strategy for the case study of deficient energy in Hstage and M-stage
DSM strategy is proposed to evaluate deficient energy and
working capacity of each unit as the following descriptions:


Quantities have subsymbol "conv" to depict the power
received after doing the conversion. The relations of these
quantities are represented by (1):





PPVGconv  PPVG 1g

PWGconv  PWG 2g


P

P

(Power
from
ES
to
DCbus)
ESdc
ES
2


or PESconv  P 'ES 2 (Power from DCbus to ES)

P
Pload  PDCload  ACload


P

P

(Power

from DC to AC)
DC
 EPSconv

or PDC  PEPS (Power from AC to DC)

High price stage (H-stage) including H1-stage and
H2-stages,
Medium price stage (M-stage) including M1-stage,
M2-stage and M3-stage,
Low price stage (L-stage) including L1-stage and L2stage.






III. DSM STRATEGY WITH APPLICATION IN VIET
NAM
3.1 Diagram of electric price in Viet Nam

Deficient energy (power from hybrid is smaller than
load power) is only bought from EPS in L1-stage and
L2-stage. Specially, it needs to buy energy to charge
ES to rated capacity (Cr) and provide energy for load
before working in the H-stage and M-stage. It means
that the DSM program helps to reduce cost for buying
electricity from EPS because deficient energy in Hstage and M-stage can be provided by ES.
In the H-stage and M-stage, redundant energy (load
power is smaller than power from hybrid generations)

will be generated to EPS if ES can not absorb.
Capacity of ES will be discharged to minimum
capacity (Cmin) before finishing the M3-stage.
Beside Cr and Cmin, value of instantaneous capacity
(Cins) represents the ability to meet electricity demand
at the current time. Unit for all of these quantities is
kWh. The constraint for above quantities is shown in
(2)
C min  0.2C r


C min  Cins  C r

Viet Nam EPS is using a diagram with three price levels
corresponding to the following stages [7], [8]:

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

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