DI SPUT E S & I NVESTI GATI O N S • ECONOMI C S • F I NAN CI A L ADVI SO RY • MANAGEM E N T CONSULT I NG
©2014 Navigant Consulting, Inc.
February 11, 2014
Survey of Models and Tools for the Stationary Energy Storage Industry
Presented by: Colette Lamontagne Infocast Storage Week
E N E R G Y 1
Key C O N T A C T S Key C O N T A C T S Key C O N T A C T S C O N T E N T S
©2014Navigant Consulting, Inc.
B
A Electric System Planning
2 Study Overview
C
Real-Time Grid Operations
Energy Storage Systems
1 Introduction to Navigant and ESA
3 Findings
4 Questions?
5 Contact Information
2 E N E R G Y
©2014 Navigant Consulting, Inc.
Services Energy Practice
PROFESSIONALS • 350+ professionals • One of largest energy advisory services
FOCAL AREAS • Smart Grid • Energy Storage • Emerging Technologies • Renewable Energy • Transmission • Energy Efficiency Strategies • Demand Side Management • Natural Gas and Energy Generation • Business Planning, Performance
Improvement and Benchmarking • Litigation, Regulatory and Markets
PROCUREMENT SERVICES Procurement support for new generation, renewables, energy storage, & transmission
GENERATION STRATEGY Renewable energy evaluation, business planning, performance improvement, technology and project due diligence, portfolio strategy, and M&A
TRANSMISSION & DISTRIBUTION Smart grid strategies, transmission planning, grid integration support
ENERGY POLICY & REGULATION Carbon market structures, emissions analysis, policy integration, market assessment
GREENHOUSE GAS BUSINESS STRATEGY Carbon market risk & opportunities, regulatory response, investment opportunity assessment
ENERGY EFFICIENCY STRATEGY Marketing & implementation, regulatory analysis/ support, program evaluation
Introduction to Navigant Consulting
Navigant is a global consulting firm providing advisory services to clients in the Energy, Healthcare, Construction and Financial industries.
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To promote the adoption of competitive and reliable energy storage systems for electric service.
The Energy Storage Association (ESA) is a non-profit, member-run organization with over 120 members worldwide.
Introduction to the Energy Storage Association (ESA)
Mission
Goals
Vision
1. Storage is integral to all systems planning and deployment. 2. ESA is a powerful global voice and resource for energy storage. 3. All stakeholders of energy storage are active, collaborating members of the ESA.
1. Industry embraces electricity storage as essential, competitive, reliable and financeable 2. Regulations recognize electricity storage as an essential component of electricity systems. 3. Effective tools support and enhance the understanding and valuation of storage. 4. ESA is recognized as a powerful global voice and resource for electricity storage. 5. Members drive the ESA mission as an engaged community of committed stakeholders
across the industry.
GET INVOLVED! www.energystorage.org
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©2014 Navigant Consulting, Inc.
Electric industry and energy storage stakeholders require appropriate models/tools to understand the true impact and value of energy storage.
Study O b jec t i ves
Sponsor: Electricity Storage Association
Objective: Benchmark existing models & tools and identify gaps.
Desired Outcome: Incentivize software developers to modify existing products or create new products to support the stationary energy storage industry.
1 Characterize Existing Models and Tools 2 Define Stakeholder
Needs 3 Identify Gaps
Study Overview » Objective
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©2014 Navigant Consulting, Inc.
Sub-
Task
s Ta
sks
Information about modeling capabilities and ES stakeholder needs was gathered in order to identify the gaps that exist in the industry.
Characterize Existing Models and Tools
1
Identified models relevant to the energy storage industry.
Collected information on these models through:
• Publically available information • Survey responses; and • Telephone interviews & email
correspondence. Summarized general and energy
storage capabilities for major model categories.
Summarized objectives and key characteristics of individual software packages.
Define Stakeholder Needs
2
Identified major ES stakeholder categories, and relevant organizations within each category.
Obtained information about each stakeholder category’s ES modeling needs through:
• Survey responses • Telephone interviews &
email correspondence Summarized this
information into ES modeling needs for each stakeholder category.
Identify Gaps
3
Compared existing products with stakeholder needs to identify current gaps in ES modeling.
Summarized findings and gaps by type of model/tool.
Study Overview » Scope and Approach
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©2014 Navigant Consulting, Inc.
Energy Storage Systems
Electric system planning models, real-time grid operation software, and tools specific to stationary energy storage systems were characterized.
Estimate and Demonstrate Value
Calculate System Size
Control and Operate Installed Systems
Optimize System Performance
Real Time Grid Operations
Electric System Planning
Energy Production Cost Simulation
Transmission System Planning
Distribution System Planning
Portfolio Planning FO
CU
S
Study Overview » Scope and Approach > Characterize Models and Tools
Generation & Transmission System
Operation
Distribution System Operation
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While we characterized the capabilities of 64 existing models and tools, we did not evaluate the quality or performance.
Software Type Number Reviewed
Electric System Planning Software
Portfolio Planning 8
Energy Production Cost Simulation 11
Bulk Transmission Planning 8
Distribution System Planning 9
Real-Time Grid Operations 6
Energy Storage Systems 22
TOTAL 64
Study Overview » Scope and Approach > Characterize Models and Tools
Note that many models have capabilities across the categories. This list represents the primary category.
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Energy Storage Industry Stakeholders
ISOs
/RTO
s
Gene
rator
s /
IPPs
Utilit
ies
R&D
/ Con
sultin
g
Proje
ct De
velop
ers
Tech
nolog
y Pr
ovide
rs
End U
sers
Finan
ce
Comm
unity
State
& F
eder
al Re
gulat
ors
System Planning Portfolio Planning X X X X X Energy Production Cost Simulation X X X X X Transmission System Planning X X X X X Distribution System Planning X X X Real Time Grid Operations Generation & Transmission System Operation X X X Distribution System Operation X X Energy Storage System Estimate & Demonstrate Value X X X X X X X X Calculate System Size X X X X X X Control & Operate Installed Systems X X X X X X X Optimize System Performance X X X X X X X
Modeling and analysis needs were mapped to each type of energy storage industry stakeholder.
Study Overview » Scope and Approach > Define Stakeholder Needs
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A few key takeaways were highlighted by numerous stakeholders. Findings » Major Takeaways
• Sub-hourly dispatch is needed in long-term planning models to accommodate system flexibility requirements.
1. Sub Hourly Dispatch
• Planning models need the ability to co-optimize various potential applications for energy storage devices.
2. Co-optimization
• Publically available models and standardized methodologies for determining optimal system size and dispatch for energy storage systems is lacking.
3. Availability and Standardization
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Models Reviewed
Portfolio planning models are used to develop long-term system capacity expansion plans.
Findings » Portfolio Planning Models
1. Create optimal generation build plan to minimize total cost given defined constraints. 2. Show the economic and operational impacts of incorporating distributed generation
and energy storage. 3. Include basic energy storage modeling capabilities with few defined inputs.
Portfolio Planning Models Developer Demand Side Management Option Risk Evaluator (DSMore) Integral Analytics
Electric Generation Expansion Analysis System (EGEAS) EPRI
Electricity Market Complex Adaptive System (EMCAS) Argonne National Laboratory
Integrated Planning Model (IPM) ICF Consulting
National Energy Modeling System (NEMS) Energy Information Administration
North American Electricity and Environment Model (NEEM) Charles River Associates
Portfolio Optimization Model (POM) Navigant Consulting, Inc.
Regional Energy Deployment System (ReEDS) Model National Renewable Energy Laboratory
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Findings » Portfolio Planning Models
Major Conclusions Portfolio Planning Models
Portfolio planning models typically use time-block operations which is not sufficient for valuing the quick start capability of energy storage.
Portfolio planning models do not have the ability to co-optimize dispatch between the energy and ancillary services market.
ES devices are not modeled with the same detail as traditional technologies in portfolio planning models.
Improvements include considering atypical time periods, shorter time-blocks, and additional input options and dispatch algorithms for ES devices.
Without appropriate representation of energy storage devices, portfolio planning models will have biases towards conventional solutions.
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Models Reviewed
Energy production cost models are used to forecast the amount of electricity produced, and the cost, to serve the system load.
Findings » Energy Production Cost Models
1. Widely used to perform hourly dispatch of a system to minimize total system cost. 2. Typical outputs include hourly LMPs, generation flows, unit operations, and unit
costs and revenue. 3. Energy storage modeling has traditionally been limited to pumped storage with peak
shaving or economic dispatch.
Energy Production Cost Simulation Model Developer Aurora XMP (Aurora) Epis, Inc. Day-Ahead Locational Market Clearing Prices Analyzer (DAYZER) Cambridge Energy Solutions Flexible Energy Scheduling Tool for Integration of Variable Generation (FESTIV) National Renewable Energy Laboratory GE Multi-Area Production Simulation Software (GE MAPS) General Electric GridView ABB, Inc. HOMER HOMER Energy, LLC PLEXOS Energy Exemplar Portfolio Ownership and Bid Evaluation (PROBE) PowerGEM PROMOD IV Ventyx REFlex National Renewable Energy Laboratory UPLAN Network Power Model (NPM) LCG Consulting
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Findings » Energy Production Cost Models
Major Conclusions Production Cost Models
Linkages to other models are necessary to determine the value of energy storage dispatch for various uses.
Many production cost models have perfect foresight over the outlook period, which does not account for forecast error. This needs to be weighed against optimization of storage.
Most production cost models do not contain a sub-hourly dispatch, and those that have added this capability are often still in the validation phase among industry users.
Improvements include modeling ES with the ability to assign value to various applications and co-optimizing dispatch algorithms for energy, AS, and system cost benefits.
Gaps exist for recognizing the value of energy storage in energy production cost models.
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Models Reviewed
Transmission system planning software is used to model large electrical transmission networks for system reliability calculations.
Findings » Transmission System Planning Models
Transmission Planning Models Developer GE Concordia Power Systems Load Flow Software (PSLF) General Electric
GE Power System Dynamic Simulation (PSDS) General Electric
Integrated Dispatchable Resource Optimization Portfolio (IDROP) Integral Analytics, Inc.
Power System Simulator for Engineering (PSS/E) Siemens Power Technologies, Inc.
PowerFlow & Short Circuit Assessment Tool (PSAT) Powertech Labs
PowerWorld Simulator (PWS) PowerWorld Corp.
Transmission and Distribution Line Design and Analysis Program ETAP
TRANZER Cambridge Energy Solutions
1. Analyze the steady state and contingency line flows and voltage conditions. 2. Review the short- and long-term dynamic stability from major system disturbances. 3. Can assess the ability of energy storage to prevent operating violations under defined
system load and generation dispatch.
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Findings » Transmission Planning Models
Major Conclusions Transmission Planning Models
Users, such as utility planners, often need to build their own models or modules for transmission planning software to assess the impacts of utility-scale ES systems.
Transmission planning models lack standard features that allow the user to properly model energy storage.
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Models Reviewed
Distribution planning models are used by utilities for planning and by ES stakeholders to assess ES system benefits at the distribution level.
Findings » Distribution System Planning Models
1. Predict circuit and equipment loading under normal and emergency conditions to determine capacity requirements.
2. Analyze circuit voltage performance to identify violations and mitigation options. 3. Analyze circuits to identify opportunities to improve efficiency. 4. Evaluate circuit capability to integrate distributed resources and impact of energy
storage.
Distribution System Planning Models Developer Electricity Distribution Grid Evaluator (EDGE) Model Rocky Mountain Institute ES-Grid DNV GL GridLab-D Pacific Northwest National Laboratory
KERMIT DNV GL
LoadSEER Integral Analytics, Inc.
Open Distribution System Simulator (OpenDSS) Electric Power Research Institute
SynerGEE GL Group
TRANZER Cambridge Energy Solutions (CES)
WindMil Milsoft
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Findings » Distribution Planning Models
Major Conclusions Distribution Planning Models
Distribution models do not allow storage units to optimize dispatch based on application priority.
Distribution planning models often require modeling of the actual ES component outside of the model as the available inputs in the model can be limited.
Distribution planning models lack standard features that allow the user to properly model energy storage.
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Findings » Real-Time Grid Operations
Major Conclusions Real-Time Grid Operations
Modifications to EMS - Traditionally, pumped hydro storage has been modeled in energy management systems as a generator type. To incorporate additional forms of ES for applications such as ancillary services, modifications are required and are being explored and implemented.
Market Rules - The issues associated with adjusting market rules to allow for energy storage resources are more complex than software modifications.
Platform for Integration - Distribution Management Systems offer a potential platform for integrating the inputs and outputs of various planning software and ES-specific tools.
Real-Time systems that are used at utilities and ISO/RTOs have begun successful modification to accommodate energy storage systems.
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Various stakeholders and vendors in the energy industry are also developing tools specific to ES needs.
Findings » Energy Storage System Tools
Tools have been created to:
These tools can vary from fairly simple spreadsheets to programs serving many functions that involve complex algorithms and software design.
Calculate the necessary
system size.
2 Control and operate a deployed system.
3
Estimate and demonstrate
the value of ES systems.
1
Optimize system
performance by prioritizing
applications.
4
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Findings » Energy Storage System Tools
Major Conclusions ES System Tools
Technology providers have developed their own proprietary tools to determine the appropriate system size and optimal system operation for their system but they are not publically available or standardized.
Stakeholders believe it would be useful to have a model that optimizes based on real-time grid data.
As these products evolve, it is important to develop appropriate standards for the underlying methodologies.
Improved historical and forecasted data on renewable resources and relevant weather characteristics are critical to calculating the benefit of renewable energy smoothing and ramping applications.
Despite the variety of tools available, many stakeholders still feel that numerous gaps exist in ES- specific software packages.
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©2014 Navigant Consulting, Inc.
The full Final Report will be distributed to ESA members and available for download in the members only portion of the website.
Questions?
Questions???
Key findings will be publically available on the ESA website
www.energystorage.org
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©2014 Navigant Consulting, Inc.
Please feel free to contact us for additional information.
Contact Information
Colette Lamontagne | Director [email protected] 781.270.8340 direct
Laurie Oppel | Managing Director [email protected] 202.481.7534 direct
Vir Chahal | Managing Consultant [email protected] 202.481.7319 direct
Jay Paidipati| Associate Director [email protected] 303.728.2489direct