Energy Storage Evaluation Tool September

PNNL-31300

Energy Storage
Evaluation Tool
September 2021
D Wu
X Ma
S Huang

D Wang
T Ramachandran
T Fu


DISCLAIMER
United States Government. Neither the United States Government nor any
agency thereof, nor Battelle Memorial Institute, nor any of their employees, makes
any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not
infringe privately owned rights. Reference herein to any specific commercial
product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation,
or favoring by the United States Government or any agency thereof, or Battelle
Memorial Institute. The views and opinions of authors expressed herein do not
necessarily state or reflect those of the United States Government or any agency
thereof.

PACIFIC NORTHWEST NATIONAL LABORATORY
operated by
BATTELLE
for the
UNITED STATES DEPARTMENT OF ENERGY
under Contract DE-AC05-76RLO1830

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This document was printed on recycled paper.
(7/2019)


PNNL-31300

Energy Storage Evaluation Tool

D Wu
X Ma
S Huang

D Wang
T Ramachandran
T Fu

September 2021

Prepared for
the U.S. Department of Energy
under Contract DE-AC05-76RL01830

Pacific Northwest National Laboratory
Richland, Washington 99352



Contents
1.0 Introduction . . . . . . . . . . . . . . . . . . . . . . .
2.0 ESET Platform . . . . . . . . . . . . . . . . . . . . .
2.1 Platform Architecture . . . . . . . . . . . . . . . .
2.2 Getting Started . . . . . . . . . . . . . . . . . . .
2.2.1 Registration and Account Management . .
2.2.2 Dashboard and Project Management . . .
2.2.3 Project Input and Output Pages . . . . . .
3.0 Battery Storage Evaluation Tool . . . . . . . . . . . .
3.1 Input . . . . . . . . . . . . . . . . . . . . . . . .
3.1.1 Use Cases and Functions . . . . . . . . . .
3.1.2 Grid and End-user Services . . . . . . . .
3.1.3 BESS Technical Parameters . . . . . . . .
3.1.4 Sizing Range and Step Size . . . . . . . .
3.1.5 BESS Economic Parameters . . . . . . . .
3.2 Output . . . . . . . . . . . . . . . . . . . . . . .
3.2.1 Optimal BESS Size . . . . . . . . . . . .
3.2.2 Present-Value Cost and Benefits . . . . . .
3.2.3 Sizing Exploration . . . . . . . . . . . . .

3.2.4 Summary of Annual Results . . . . . . . .
3.2.5 BESS Operation . . . . . . . . . . . . . .
4.0 Microgrid Asset Sizing Considering Cost and Resilience
4.1 Input . . . . . . . . . . . . . . . . . . . . . . . .
4.1.1 Settings . . . . . . . . . . . . . . . . . . .
4.1.2 Load Profile . . . . . . . . . . . . . . . .
4.1.3 Tariff Structure . . . . . . . . . . . . . . .
4.1.4 Financial Analysis . . . . . . . . . . . . .
4.1.5 DER Selection . . . . . . . . . . . . . . .
4.1.6 PV Parameters . . . . . . . . . . . . . . .
4.1.7 ESS Parameters . . . . . . . . . . . . . .
4.1.8 DG Parameters . . . . . . . . . . . . . . .
4.2 Output . . . . . . . . . . . . . . . . . . . . . . .
4.2.1 Sizing Results . . . . . . . . . . . . . . .
4.2.2 Cost Analysis . . . . . . . . . . . . . . .
4.2.3 Monthly Peak Load . . . . . . . . . . . .
4.2.4 Annual Operation in Grid-Connected Mode
5.0 Hydrogen Energy Storage Evaluation Tool . . . . . . .
5.1 Input . . . . . . . . . . . . . . . . . . . . . . . .
5.1.1 System Configuration . . . . . . . . . . .
5.1.2 Financial Analysis . . . . . . . . . . . . .
5.1.3 Grid Services . . . . . . . . . . . . . . . .
5.1.4 Electrolyzer . . . . . . . . . . . . . . . .
5.1.5 Water Cost . . . . . . . . . . . . . . . . .
5.1.6 Hydrogen Storage . . . . . . . . . . . . .
5.1.7 Pathway 1: Tube Compressor . . . . . . .
5.1.8 Pathway 1: Hydrogen Sale . . . . . . . .
iii

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. . . . . . . . . . . .
1.1
. . . . . . . . . . . .
2.1
. . . . . . . . . . . . . 2.1
. . . . . . . . . . . . . 2.3
. . . . . . . . . . . . . 2.3
. . . . . . . . . . . . . 2.4
. . . . . . . . . . . . . 2.5
. . . . . . . . . . . .
3.1
. . . . . . . . . . . . . 3.3
. . . . . . . . . . . . . 3.3

. . . . . . . . . . . . . 3.4
. . . . . . . . . . . . . 3.6
. . . . . . . . . . . . . 3.6
. . . . . . . . . . . . . 3.6
. . . . . . . . . . . . . 3.7
. . . . . . . . . . . . . 3.7
. . . . . . . . . . . . . 3.7
. . . . . . . . . . . . . 3.8
. . . . . . . . . . . . . 3.8
. . . . . . . . . . . . . 3.10
. . . . . . . . . . . .
4.1
. . . . . . . . . . . . . 4.2
. . . . . . . . . . . . . 4.2
. . . . . . . . . . . . . 4.3
. . . . . . . . . . . . . 4.3
. . . . . . . . . . . . . 4.4
. . . . . . . . . . . . . 4.4
. . . . . . . . . . . . . 4.4
. . . . . . . . . . . . . 4.5
. . . . . . . . . . . . . 4.5
. . . . . . . . . . . . . 4.6
. . . . . . . . . . . . . 4.6
. . . . . . . . . . . . . 4.6
. . . . . . . . . . . . . 4.7
. . . . . . . . . . . . . 4.8
. . . . . . . . . . . .
5.1
. . . . . . . . . . . . . 5.2
. . . . . . . . . . . . . 5.2

. . . . . . . . . . . . . 5.2
. . . . . . . . . . . . . 5.3
. . . . . . . . . . . . . 5.4
. . . . . . . . . . . . . 5.4
. . . . . . . . . . . . . 5.4
. . . . . . . . . . . . . 5.5
. . . . . . . . . . . . . 5.5


5.1.9

Pathway 2: Pipeline Injection . . . . . . . . . . . . . . . . . . . . . . .
5.1.9.1 Optional Components . . . . . . . . . . . . . . . . . . . . . .
5.1.9.2 Methanation . . . . . . . . . . . . . . . . . . . . . . . . . . .
5.1.10 Pathway 3: Fuel Cell . . . . . . . . . . . . . . . . . . . . . . . . . . .
5.2 Output . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
5.2.1 Annual Hours of Operation, Production, and Financial Returns . . . . .
5.2.2 One-year Simulated Benefits and O&M Costs . . . . . . . . . . . . . .
5.2.3 HES Hourly Prices, Load/Generation, and Hydrogen Flow . . . . . . . .
6.0 Pumped Storage Hydropower Evaluation Tool . . . . . . . . . . . . . . . . . . . .
6.1 Input . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
6.1.1 System Configuration . . . . . . . . . . . . . . . . . . . . . . . . . . .
6.1.2 PSH Financial Analysis and Economic Parameters . . . . . . . . . . . .
6.1.3 Grid and End-user Services . . . . . . . . . . . . . . . . . . . . . . . .
6.2 Output . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
6.2.1 Present Value Costs and Benefits . . . . . . . . . . . . . . . . . . . . .
6.2.2 Summary of Annual Results . . . . . . . . . . . . . . . . . . . . . . . .
6.2.3 PSH Operation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
7.0 Virtual Battery Assessment Tool . . . . . . . . . . . . . . . . . . . . . . . . . . .
7.1 Navigation Panel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

7.2 Setting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
7.2.1 Geographical Level . . . . . . . . . . . . . . . . . . . . . . . . . . . .
7.2.2 Region and Device Type . . . . . . . . . . . . . . . . . . . . . . . . . .
7.2.3 Assessment Results . . . . . . . . . . . . . . . . . . . . . . . . . . . .
8.0 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

iv

5.5
5.6
5.6
5.6
5.7
5.7
5.8
5.9
6.1
6.1
6.1
6.3
6.4
6.6
6.6
6.6
6.7
7.1
7.2
7.3
7.3
7.3

7.5
8.1


Figures
Figure 1 ESET platform architecture . . . . . . . . . . . . . . . . . . . .
Figure 2 Database architecture . . . . . . . . . . . . . . . . . . . . . . . .
Figure 3 Docker-based deployment . . . . . . . . . . . . . . . . . . . . .
Figure 4 Create an account . . . . . . . . . . . . . . . . . . . . . . . . . .
Figure 5 Account management . . . . . . . . . . . . . . . . . . . . . . . .
Figure 6 User dashboard . . . . . . . . . . . . . . . . . . . . . . . . . . .
Figure 7 Project input page . . . . . . . . . . . . . . . . . . . . . . . . .
Figure 8 Help text . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Figure 9 Notification message when an evaluation is completed . . . . . .
Figure 10 Project output page . . . . . . . . . . . . . . . . . . . . . . . . .
Figure 11 Illustration of MPC-based evaluation approach . . . . . . . . . .
Figure 12 Illustration of bilevel sizing approach . . . . . . . . . . . . . . .
Figure 13 BSET Settings panel . . . . . . . . . . . . . . . . . . . . . . . .
Figure 14 BSET Grid Service Selection and BTM Service Selection panels .
Figure 15 BSET Grid Service Inputs panel . . . . . . . . . . . . . . . . . .
Figure 16 BSET T&D Deferral Inputs panel . . . . . . . . . . . . . . . . .
Figure 17 BSET BTM Service Inputs panel . . . . . . . . . . . . . . . . . .
Figure 18 BSET BESS Technical Parameters panel . . . . . . . . . . . . . .
Figure 19 BSET Sizing Range and Sizing Step Size panels . . . . . . . . . .
Figure 20 BSET BESS Economic Parameters panel . . . . . . . . . . . . .
Figure 21 BSET BESS Size and Optimal BESS Size . . . . . . . . . . . . .
Figure 22 BSET Present-Value Costs and Benefits . . . . . . . . . . . . . .
Figure 23 BSET Sizing Exploration . . . . . . . . . . . . . . . . . . . . . .
Figure 24 BSET Annual Benefits by Service . . . . . . . . . . . . . . . . .
Figure 25 BSET Number of Hours by Service . . . . . . . . . . . . . . . .

Figure 26 BSET Annual Electricity Bill . . . . . . . . . . . . . . . . . . . .
Figure 27 BSET Monthly Peak Load . . . . . . . . . . . . . . . . . . . . .
Figure 28 BSET BESS Operation . . . . . . . . . . . . . . . . . . . . . . .
Figure 29 Illustration of the two-stage stochastic DER sizing method . . . .
Figure 30 MASCORE Settings panel with Min net cost selected . . . .
Figure 31 MASCORE Settings panel with Max survivability selected
Figure 32 MASCORE Load Profile panel . . . . . . . . . . . . . . . . . . .
Figure 33 MASCORE Tariff Structure panel . . . . . . . . . . . . . . . . .
Figure 34 MASCORE Financial Analysis panel . . . . . . . . . . . . . . .
Figure 35 MASCORE DER Selection panel . . . . . . . . . . . . . . . . .
Figure 36 MASCORE PV Parameters panel . . . . . . . . . . . . . . . . .
Figure 37 MASCORE ESS Parameters panel . . . . . . . . . . . . . . . . .
Figure 38 MASCORE DG Parameters panel . . . . . . . . . . . . . . . . .
Figure 39 MASCORE Sizing Results . . . . . . . . . . . . . . . . . . . . .
Figure 40 MASCORE Cost Analysis . . . . . . . . . . . . . . . . . . . . .
Figure 41 MASCORE Monthly Peak Load . . . . . . . . . . . . . . . . . .
Figure 42 MASCORE Annual Operation in Grid-Connected Mode . . . . .
Figure 43 HES system scope . . . . . . . . . . . . . . . . . . . . . . . . .
Figure 44 HES System Configuration panel . . . . . . . . . . . . . . . . . .
Figure 45 HES Financial Analysis panel . . . . . . . . . . . . . . . . . . .
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. 2.1
. 2.2
. 2.3
. 2.3
. 2.4
. 2.4
. 2.5
. 2.6
. 2.6
. 2.7
. 3.2
. 3.3
. 3.4
. 3.4
. 3.5
. 3.5

. 3.5
. 3.6
. 3.6
. 3.7
. 3.7
. 3.7
. 3.8
. 3.9
. 3.9
. 3.10
. 3.10
. 3.11
. 4.2
. 4.2
. 4.2
. 4.3
. 4.4
. 4.4
. 4.4
. 4.5
. 4.5
. 4.6
. 4.6
. 4.7
. 4.7
. 4.8
. 5.2
. 5.2
. 5.3

Figure 46 HES Services and Value Streams panel . . . . . . . . . . . . . . . .
Figure 47 HES grid service input panels . . . . . . . . . . . . . . . . . . . . .
Figure 48 HES Electrolyzer panel . . . . . . . . . . . . . . . . . . . . . . . . .
Figure 49 HES Water Cost panel . . . . . . . . . . . . . . . . . . . . . . . . .
Figure 50 HES Hydrogen Storage panel . . . . . . . . . . . . . . . . . . . . .
Figure 51 HES Compressor panel . . . . . . . . . . . . . . . . . . . . . . . . .
Figure 52 HES Hydrogen Sale panel . . . . . . . . . . . . . . . . . . . . . . .
Figure 53 HES Pathway2: Pipeline Injection panel . . . . . . . . . . . . . . .
Figure 54 HES Pathway2: Optional Components panel . . . . . . . . . . . . .
Figure 55 HES Pathway 2: Methanation panel . . . . . . . . . . . . . . . . .
Figure 56 HES Pathway 3: Fuel Cell panel . . . . . . . . . . . . . . . . . . .
Figure 57 HES Annual Hours of Operation, Production, and Financial Returns
Figure 58 HES PV benefits . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Figure 59 HES PV cost . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Figure 60 HES One-year Simulated Benefits and O&M Costs panel . . . . . . .
Figure 61 HES one-year simulated benefits . . . . . . . . . . . . . . . . . . . .
Figure 62 HES one-year simulated cost . . . . . . . . . . . . . . . . . . . . . .
Figure 63 HES hourly hydrogen flow . . . . . . . . . . . . . . . . . . . . . . .
Figure 64 HES hourly stored hydrogen . . . . . . . . . . . . . . . . . . . . . .
Figure 65 PSHET System Configuration panel . . . . . . . . . . . . . . . . . .
Figure 66 PSH unit types . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Figure 67 PSH generator/motor technologies . . . . . . . . . . . . . . . . . . .
Figure 68 PSHET PSH Unit Parameters panel . . . . . . . . . . . . . . . . . .
Figure 69 PSHET Financial Analysis panel . . . . . . . . . . . . . . . . . . . .
Figure 70 PSHET Economic Parameters panel . . . . . . . . . . . . . . . . . .
Figure 71 PSHET Energy Arbitrage panel . . . . . . . . . . . . . . . . . . . .
Figure 72 PSHET Frequency Regulation panel . . . . . . . . . . . . . . . . . .
Figure 73 PSHET Spinning Reserve panel . . . . . . . . . . . . . . . . . . . .
Figure 74 PSHET Transmission and Distribution (T&D) Upgrade Deferral

panel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Figure 75 PSHET Capacity Value/Resource Adequacy panel . . . . . . . . . . .
Figure 76 PSHET Power Reliability panel . . . . . . . . . . . . . . . . . . . .
Figure 77 PSHET Present Value Costs and Benefits . . . . . . . . . . . . . . .
Figure 78 PSHET Annual Benefits by Service . . . . . . . . . . . . . . . . . . .
Figure 79 PSHET Number of Hours by Service . . . . . . . . . . . . . . . . . .
Figure 80 PSHET grid service prices . . . . . . . . . . . . . . . . . . . . . . .
Figure 81 PSHET unit-level operation . . . . . . . . . . . . . . . . . . . . . .
Figure 82 PSHET system-level operation and water volume state . . . . . . . .
Figure 83 VBAT assessment procedures . . . . . . . . . . . . . . . . . . . . .
Figure 84 VBAT navigation panel . . . . . . . . . . . . . . . . . . . . . . . . .
Figure 85 VBAT Geographical Level page . . . . . . . . . . . . . . . . . . . .
Figure 86 VBAT Device Type page . . . . . . . . . . . . . . . . . . . . . . . .
Figure 87 VBAT Region & Device Type page . . . . . . . . . . . . . . . . . . .
Figure 88 VBAT Assessment Results page . . . . . . . . . . . . . . . . . . . .

vi

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. 5.3
. 5.3
. 5.4
. 5.4
. 5.4
. 5.5
. 5.5
. 5.6
. 5.6
. 5.6
. 5.7
. 5.7
. 5.7
. 5.8
. 5.8
. 5.9
. 5.9

. 5.10
. 5.10
. 6.2
. 6.2
. 6.2
. 6.3
. 6.3
. 6.4
. 6.5
. 6.5
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7.2
7.2
7.3

7.4
7.4
7.5


Tables
Table 1

Solution approaches by use case and functionality . . . . . . . . . . . . . . . . .

vii

3.3



1.0 Introduction
With a growing emphasis on energy security and environmental protection, renewable energy has
been developing rapidly around the world. The operation of the electric power sector requires
flexibility to realize the instantaneous balance between generation and constantly changing
demand. The increasing penetration of renewable generation imposes challenges on power
system operation due to its natural uncertainty and variability. Energy storage can save energy
from electricity at a point in time for later use and respond instantaneously to unpredictable variations in demand and generation. Various energy storage technologies, such as batteries, pumped
hydro, hydrogen energy storage, and compressed air energy storage, have been a candidate for
meeting flexibility and reserve requirements for years and are promising to resolve various operational issues in today’s power systems. The development and deployment of grid-connected
energy storage systems (ESSs) have been gathering momentum, enabling them to provide a
variety of grid and end-user services. As the technologies advanced, many demonstrations and
deployments have been realized, and the regulatory structure is emerging. Clearly, developing
less expensive and safer storage devices with longer cycle life is of great importance. There are
many facilities demonstrating the technical feasibility of storage technologies recently, but few

are truly cost-effective commercial ventures. Value streams must be identified and appropriately
monetized to make ESS a more financially competitive option and thereby adopted at scale.
While energy storage has attributes that provide tremendous flexibility to power systems and
end-users, it is challenging to optimally use an ESS and fully capture its potential benefits from
multiple applications. First, gaining value from a wide variety of services requires broad consideration. Services provided by energy storage have different purposes and vary based on the
benefitting parties. Varying rules and requirements tied to each service must be fully considered to earn the given value. In addition, the economic benefits of an ESS highly depend on
its operational characteristics and physical capability. Physical limitations of an ESS must be
respected and represented in a way that accurately captures their operational characteristics so
that they can be fairly evaluated against other system assets. Regulatory limitations may also
allow or disallow certain kinds of operations at certain times. Lastly, it can be challenging to
schedule and dispatch ESSs as necessary to provide the most value. The complexity of correctly
valuing ESSs comes not only from the devices themselves but also that which is introduced when
multiple, potentially competing applications of gaining value from a given operational opportunity are evaluated. Charging control could be extremely complicated due to the competition
among various services for limited power and energy capacity, not only on a time step but also
intertemporally. When incorporating uncertainties into ESS scheduling and sizing in addition to
capturing diversified system conditions, these problems become extremely challenging to solve.
Electric utilities, system operators, legislators, regulators, ESS vendors, power market participants, energy customers, and researchers and developers need modeling and analytical methods
and tools to understand how ESSs can be used in different use cases and the potential benefits.
The lack of knowledge concerning energy storage capabilities and the ability to generate value
from multiple applications results in an incomplete assessment of ESS value and becomes a significant barrier to ESS penetration in the marketplace. To meet such a need, Pacific Northwest
National Laboratory (PNNL) has developed a valuation taxonomy that includes bulk energy,
ancillary, transmission, distribution, and customer energy management services. In addition,
1.1


PNNL has developed advanced modeling and analytical methods and tools through various ESS
projects at more than 30 sites across the U.S. An application suite named Energy Storage Evaluation Tool (ESET) was recently developed, which contains a set of modules and applications
enabling a broad range of users to model, optimize, evaluate, and size various ESSs for bundling
grid and end-user services. ESET contains five modules designed for different types of ESSs,
including battery energy storage, storage-enabled microgrid, hydrogen energy storage, pumpedstorage hydropower, and thermal storage in building mass.

• Battery Energy Storage Evaluation Tool (BSET)
BSET is a modeling and analysis tool that enables users to evaluate and size a battery
energy storage system for grid applications. It models the technical characteristics and
physical capability of a battery energy storage system. It also incorporates operational
uncertainty into system valuation. Finally, it optimizes battery system operation to maximize stacked value streams from various grid and end-user services, considering trade-offs
among these services.
• Microgrid Asset Sizing considering Cost and Resilience (MASCORE)
MASCORE is a modeling and analysis tool designed for optimal sizing of distributed
energy resources in the context of microgrids, considering both economic benefits and
resilience performance. It is based on a chance-constrained, two-stage stochastic approach
to jointly determine optimal sizes of various distributed energy resources, including renewables, energy storage, microturbines, and diesel generators. MASCORE explicitly models
the interaction between distributed energy resource sizing at the planning stage and hourly
or sub-hourly microgrid dispatch at the operating stage in both grid-connected and island
modes, considering stochastic grid disturbances, load, and renewable generation.
• Hydrogen Energy Storage Evaluation Tool (HESET)
HESET is a valuation tool designed for hydrogen energy storage systems toward multiple
pathways and grid applications. It models economic and technical characteristics of
individual components, multiple pathways of hydrogen flow, and a variety of grid and enduser services. It optimizes the operation of a hydrogen energy storage system to maximize
the economic benefits considering the coupling and trade-off among various pathways and
grid services and performs the cost-benefit analyses.
• Pumped-Storage Hydropower Evaluation Tool (PSHET)
PSHET is an evaluation tool designed for pumped-storage hydroelectric systems. It
supports both fixed- and variable-speed pumped-storage hydropower systems with different
configurations, including separate and reversible pump/turbine and ternary sets. It models
and optimizes these systems at the unit level in different operating modes to maximize
economic benefits from a variety of grid and end-user services.
• Virtual Battery Assessment Tool (VBAT)
VBAT is an assessment tool designed to enable users to quantify the technical and economic potential of regional flexibility from different types of building loads in the U.S.
The aggregate flexibility is characterized using a virtual battery that resembles simplified
battery dynamics parameterized by charging/discharging power limits, energy limits, and

self-discharging rate. It captures the inherent ability of buildings to store heat in thermal
mass, vary their power consumption, and shift the electric energy consumption to an earlier
or later time, subject to customers’ requirements of comfort and convenience.
1.2


ESS models with different levels of complexity and fidelity are used. Appropriate formulation
and solution methods are selected or developed based on the ESS models and applications of
interest. ESET is designed to be easy to use without requiring knowledge of the modeling and
optimization behind the tool. A subset of features and capabilities of ESET are made publicly
accessible as a web-based tool that can be used across a variety of platforms and devices. It
runs from a host server, eliminating the need for download, installation, and updates on local
machines. More comprehensive and powerful ESET modules are available for licensing. This
user’s guide focuses on the web-based ESET and describes how to use the platform and individual modules for customized analysis. An overview of different applications and modeling
approaches for different modules is also provided.
Grid services modeled in different ESET applications include:
• Energy arbitrage – Energy arbitrage or energy shifting refers to the operation of ESSs that
generate electricity when the demand and/or electricity prices are high and consumes electricity when the demand and/or prices are low. Energy arbitrage can be performed in an
electricity market to pursue revenue from energy trading or in a vertically integrated utility
to reduce production cost. The economic reward is the price or cost differential between
charging and discharging electrical energy, considering losses during charging/discharging
operations.
• Capacity and resource adequacy – An important issue in power system planning is to
ensure sufficient resources to meet future demand, either through capacity markets or integrated resource planning. Capacity is not actual electricity, but rather the ability to produce electricity in future years. ESSs can be used to provide peaking capacity since they
are flexible and can be quickly dispatched with a high ramp rate to meet peak demands.
The corresponding economic benefits are capacity payments for market participants or
capacity charge reduction in a market environment or through bilateral contracts, or saving from replacing or reducing the need for new peaking resources in vertically integrated
utilities.
• Frequency regulation – The electric power system must maintain a near-real-time balance
between generation and load. Balancing generation and load instantaneously and continuously is difficult because loads and generation are constantly fluctuating. Frequency

regulation is required to continuously balance generation and load within a control area
and thereby main system frequency and manage differences between actual and scheduled
power flows between control areas. Frequency regulation is the most valuable ancillary service. To provide regulation services, an ESS needs to respond rapidly to systemoperator requests for up and down movements by following automatic generation control
signals. The economic benefits can be defined based on regulation prices in electricity
markets or reduced costs of operating generators in vertically integrated utilities. Most
markets have implemented pay-for-performance to calculate rewarding credit based on regulation capacity, regulation mileage, and performance factor/score. The exact calculation
formula may vary from one ISO to another, but the main idea is the same.
• Spinning reserve – Contingency or operating reserves are called to restore the generation and load balance in the event of a contingency such as a sudden, unexpected loss of
a generator. Any resource that can respond quickly and long enough can supply contin1.3


gency reserves. An ESS can be used to provide both spinning and non-spinning reserves.
Spinning reserve is provided by power sources already online and synchronized to the grid
that can increase the output immediately in response to a major generator or transmission
outage, and can reach full output quickly (e.g., 10 minutes). Considering the typical prices
and required energy reserve, using an ESS to provide spinning reserve is generally more
valuable than non-spinning reserve. Therefore, only the former is considered in ESET.
Unlike regulation up service that is exercised from hour to hour, spinning reserve is not
called upon unless a contingency occurs.
• T&D deferral – ESSs can play an important role by reducing the peak load on a specific
portion of the transmission and distribution (T&D) system, and thereby help defer or
postpone specific projects and T&D system upgrades that otherwise would be needed
earlier to meet the growing demands. Depending on the circumstances, the benefits can be
quite significant, especially if the upgrade that is deferred is expensive. In most situations,
an ESS for this application is only used for a small portion of the year when the load
exceeds the T&D equipment’s capacity. To receive the value from deferring a local T&D
system investment/upgrade, an ESS must exceed a certain power output level during peak
hours. The same ESS can be used for numerous other applications in the remaining time.
The economic benefits can be estimated based on the T&D upgrade cost and the number of
years an upgrade can be deferred.

Commercial and industrial customers and small utilities that purchase electricity from suppliers
can use ESS for bill management and cost reduction, and providing demand response (DR).
• Energy charge reduction – Energy charge is based on the amount of energy consumed
and the time when energy is consumed. It reflects the operational cost in electricity generation and delivery. An ESS can be used for energy shifting to take advantage of timeof-use tariff structures. Some other bill components such as transmission charge depend
on the energy consumption during specific hours that are given or can be forecasted. Such
kinds of charges can also be captured by adding the corresponding rates to the energy
charge rate to generate a lumped “energy” charge rate.
• Demand charge reduction – Demand charge is based on the highest power consumption
during a billing period (typically a month). It is mainly designed to recover the investment in electricity generation and transportation infrastructure. An ESS can be used to
effectively lower the peak load and thereby reduce demand charge.
• Demand response – An ESS may participate in a utility’s DR program, which compensates commercial and industrial customers to curtail their energy when the demand is
forecasted to be at its peak. A participating customer would be compensated for the
amount of energy curtailed on a pay-for-performance basis. The rules and incentives vary
by DR program. An ESS can adjust its power output relative to a baseline calculated by
the applicable program administrator.
• Resilience enhancement – In addition to economic benefits, an ESS can also be used
to strengthen the resilience of distribution systems and reduce power interruptions of
critical facilities. Resilience is the ability of a system to prepare for and adapt to changing
conditions and to withstand and recover rapidly from deliberate attacks, accidents, or
naturally occurring threats or incidents. Economic and resilience performance are two
1.4


different metrics. In practice, it is difficult for a facility manager or end-user to quantify
the value of resilience and estimate the cost associated with an outage occurring at different
times with different durations and magnitudes. More importantly, resilience performance
and requirements, in general, cannot be fully captured as a monetary value.
The remainder of this user’s guide is organized as follows. Section 2 describes the architecture
and features of the ESET platform. Sections 3–5 are dedicated to BSET, MASCORE, and
HESET, respectively. In each of these sections, an overview of the module is first provided.

The inputs and outputs are then described.

1.5



2.0 ESET Platform
2.1

Platform Architecture

ESET is based on a modular structure, as illustrated in Figure 1. One main advantage of such
a structure is that different modules and components can be implemented in a separated and
isolated manner, facilitating maintenance and expansion. In addition, data and applications are
completely separated in ESET to improve data security.

Figure 1. ESET platform architecture

The platform consists of three modules, which are described as follows.
• Modeling & Optimization Engines – This module provides an environment and process
manager for simulation and optimization involved in ESS evaluation and sizing analyses.
The analysis in each project is managed as a task– a process that includes I/O operations,
optimization and simulation engine, pre- and post-processing, and financial analysis,
etc. For each task, the input and log pipes are used to specify required inputs and query
progress, respectively. Once a task is completed, the process manager forwards the outputs to the Information Exchange Portal. A request queue is set up to limit the number of
tasks, and thereby avoiding running out of computing resources.
• Information Exchange Portal – This module serves as an information hub and interacts
with users through http requests. Specifically, users access predefined Uniform Resource
Locators (URLs) with standard http requests through either web browsers or commandline tools. A dynamic graphical user interface is developed to provide an interactive user
experience for easy configuration and settings. An http request is then interpreted by the

Python Flask Framework to either provide input data or query for information on projects.
This module also interacts with the module of Modeling & Optimization Engines through
2.1


standard application programming interfaces (APIs), and interacts with the Database module through Structured Query Language (SQL) interfaces. The input data is forwarded to
Modeling & Optimization Engines to create a task. The query request is sent to Database
to obtain the required data. Once the data is received, the module processes data and output results as tables and figures. The processed data, tables, and figures are then embedded
into html contents using predefined templates. The html contents are then sent back to
users and displayed in a web browser.
• Database – This module stores user information, user groups, permission, and inputs and
outputs of each project using multiple tables. A dedicated table is designed to store user
information. The group and permission tables are created and linked to user information
for user management. In addition, each application has its own table. All the tables
contain a field named User ID, and each user has a unique User ID. Through the User ID,
project data can be linked to users. For any tables that contain project data, there are
two fields Project name and Project status. For each user, each project has a unique
Project name.

Figure 2. Database architecture

To facilitate the deployment, an encapsulated environment with Docker is adopted to eliminate
the need for customized settings. Docker is a set of platform as a service (PaaS) products that
uses OS-level visualization to deliver software in packages called containers. Containers are
isolated from one another and bundle their own software, libraries, and configuration files, and
communicate with each other through a predefined TCP port and HTTP protocol within the
network created through the Docker environment. A dedicated container is created for each
component in ESET, as illustrated in Figure 3. We also set up a port forwarding between the
Information Exchange Portal docker and the host operation system to allow ESET to take inputs
outside the Docker environment. The platform and Docker containers can be deployed on a

server or a local machine.
2.2


Figure 3. Docker-based deployment

2.2
2.2.1

Getting Started
Registration and Account Management

A user account is required to use ESET. To use the ESET hosted at the PNNL server, users can
click the Create Account button on the login page to register an account. Users’ information can be entered on the registration page, as shown in Figure 4. Once submitted, ESET
sends an email that contains a link for users to confirm the registration request. The Reset
Password button can be used when a user forgot the password. When ESET is deployed on
a local machine, a predefined user credential (username: test1, password: test1) can be used.
Users can modify account information and change password through account management, as
shown in Figure 5.

Figure 4. Create an account
2.3


Figure 5. Account management

2.2.2

Dashboard and Project Management

Once logged in to the ESET platform, a user is navigated to the dashboard page, as shown in
Figure 6.

Figure 6. User dashboard

The dashboard page consists of three parts: module list, menu, and project list.
• In the module list area, users can click a module to create a new project. A pop-up window is displayed for users to enter a project name. Note that the project name should be
unique under a user’s account.
2.4


• In the menu area, the user ID is displayed, followed by two buttons: Account and
Logout. By clicking the Account button, a user is navigated to a new web page where
they can review and edit the account information. Clicking the Logout button returns to
the login/registration page.
• All the existing projects under a user’s account are displayed in the project list area. There
are four fields: Model Name, Type, Created Time, and Modified Time. Users can sort
projects by field by clicking a field name. Users can delete, rename, and duplicate a
project using the three buttons below “Options.” By click a project’s model name, users
are navigated to the project input page, where they can view and edit a project.
2.2.3

Project Input and Output Pages

The project input page consists of five parts: input/output navigation, menu, project setting and
parameters, buttons for actions, and optimization log, as shown in Figure 7.

Figure 7. Project input page
• The input/output navigation allows users to switch between the two web pages. Note that
the Output button is disabled for a project without analysis results (e.g., a new project) or

when a project is running.
• There are two buttons in the menu area: Dashboard and Logout. The Dashboard
button is used to return to the dashboard page.
• In the area of action buttons, the Save button is used to save project inputs into the
2.5


database. The Run button is used to start the evaluation. The Cancel button is used
to terminate the evaluation, which is disabled unless a project is running.
• In the setting and parameter area, users can change settings and parameters and upload
customized input files. Help text is displayed to provide additional information when
moving cursor over a setting or parameter name, as shown in Figure 8. When a series of
data are required as inputs, templates are developed for users to prepare and upload inputs.
The Default button is used to reset an input to the default file. Users can download the
current input file using the Download button to view or edit the content, and replace an
existing input file with a new customized one using the Upload button.
• In the log area, optimization progress information is displayed.

Figure 8. Help text

Once the analysis is completed, a pop-up window is displayed, as shown in Figure 9. Clicking
the OK button, the link to the Output page in the input/output navigation area is enabled.

Figure 9. Notification message when an evaluation is completed

An example output page is shown in Figure 10, where a summary of results and visualization of
different results are available. ESET currently supports four types of figures: 3-D surface chart,
pie chart, bar chart, and time series chart. There is a Download button in all the figures for
users to download the numerical data for a record or customized analysis. Detailed information
is displayed when users move the cursor to a legend, a slice in a pie chart, a bar in a bar chart, and

a point in a 3-D surface and time series chart. By clicking a legend, line, or pie slice, users can
show or hide the corresponding line or pie slice. For 3-D surface charts, users can view graphs
from different angles. For time series charts, users can select a particular area to zoom in and
explore the results in detail and click the Reset Zoom button to exit a zoom-in mode and return
to the original axes limits.
2.6


Figure 10. Project output page

2.7



3.0 Battery Storage Evaluation Tool
Among various energy storage technologies, battery energy storage systems (BESSs) have the
best controllability and operational flexibility and can respond instantaneously to unpredictable
variations in demand and generation in today’s rapidly evolving electric power grid. Potential
benefits from a BESS are highly dependent on scheduling and control methods, which can be
extremely complicated considering the competition among various services for limited power and
energy capacity, not only at a time step but also intertemporally. Therefore, valuation and sizing
tools that co-optimize benefits from stacked value streams are required to define technically
achievable benefits. To meet such a need, PNNL developed the Battery Storage Evaluation
Tool (BSET) in 2013, focusing on BESS evaluation and sizing considering bundling grid and
behind-the-meter (BTM) services, including energy arbitrage, ancillary services, capacity value,
T&D deferral, and energy and demand charge reduction. As a cost-free proprietary software,
BSET has been licensed to more than 50 entities, including federal, state, and local governments,
electric utilities, developers, national laboratories, and universities.
BSET was initially developed in MATLAB® and the stand-alone executable can only run in
Windows systems. The new web-based BSET can be used across multiple types of platforms

and devices. In recent years, the BSET engine has been modified, improved, adapted, and
deployed for energy storage economic analysis at more than 20 sites across the U.S. Additional
capabilities for energy storage modeling and optimization have been developed, including highfidelity nonlinear BESS models, state-of-health and degradation models, dispatch/scheduling
strategies for addressing uncertainties, and strategies and algorithms for optimal distribution of
battery life. We are currently working to integrate these capabilities into BSET and plan to make
them available to the public in future versions.
For both grid and BTM services, BSET provides three functionalities:
• Evaluation – evaluate economic benefits through optimal dispatch for a given size of
BESS.
• Direct Sizing – directly determine the optimal BESS power and energy capacity by
modeling them as decision variables in optimization with an objective to maximize net
benefits.
• Sizing Exploration – automatically evaluate net benefits for a number of BESS
sizes.
Three approaches are used for BESS evaluation and sizing, with different assumptions for different use cases:
• Model predictive control (MPC)-based evaluation
In the MPC-based evaluation approach, at each hour, a look-ahead optimal dispatch is
formulated based on information available at the scheduling stage. The length of the
look-ahead window is set to be 24 hours. The scheduling problem is solved to determine
the base operating point and how a BESS is used for different services in each hour. The
actual BESS operation is then simulated with an appropriate time resolution based on
3.1