A model future for the electrical grid

In the electrical grid today, both energy supply and demand are increasing in complexity. This is due to the introduction of renewables on the supply side, and emerging demands like electric vehicles and load growth in more remote areas.

To date, North America has been able to meet these demands and “keep the lights on” 24/7, 365 days a year, thanks to well-established power system planning, procurement and operation practices. The system is well regulated, assets are well understood and the supply chain for established products is strong.

But when new technologies like energy storage emerge, new tools that accurately model their functionality and characteristics need to be built and validated so that planners and operators can safely and reliably assess where and how they can be integrated into the grid, to realize their benefits.

These models for the future of electrical grid are being developed – now.

The next wave: modelling and planning tools for future energy use

North Americans have historically benefitted from low electricity prices relative to other OECD countries and especially in comparison to Western Europe^Footnote1.

Why is our North American power grid relatively reliable and affordable? One of the reasons is that power system planners and operators have consistently used planning and modelling software tools to evaluate the impact of changes to the grid. When maintaining and upgrading the electrical grid, these tools allow new load, capacity, and technologies to be seamlessly added with minimal safety or financial risk. This is, of course, supported by established regulations and procedures, as well as the rich knowledge and experience of power system engineers across the sector. However, by carefully studying the potential impacts of grid equipment prior to its connection, power system planners and operators safely manage an extremely complex high-energy resource and “keep the lights on” 24/7, 365 days a year.

Currently, our energy sources are shifting away from fossil fuels that have historically provided reliable baseload generation, to renewables that are variable in nature. This change in the supply mix, coupled with the electrification of the transportation sector and other demand-side pressures, continues to add complexity to the system.

To support this shift major infrastructure upgrades are required^Footnote2, and system planners and operators need to employ new strategies and tools to continue to deploy the next generation of the electrical grid. The relatively gradual development and integration of renewable generation (e.g. wind, solar, geothermal, tidal, etc.) onto the grid has allowed power system modelling tools to evolve and mature to the current state where they’re sufficiently accurate and flexible enough to be used reliably in many scenarios using traditional generation, regulation and protection assets.

However, this same level of maturity does not yet exist in the models of the energy storage technologies, which can support their use. With the rapid commercialization of several different energy storage technologies, significant gaps exist that are preventing the system planners and operators from accurately evaluating their potential benefits, as well as optimizing their deployment and operation.

First steps to a new model

A “Survey of Modelling Capabilities and Needs for the Stationary Energy Storage Industry”^Footnote3 was conducted by Navigant Research for the Energy Storage Association. As outlined in the figure below, focusing primarily on electric system planning tools, it looked across the entire range of planning and analysis steps, clarified the existing tools capabilities in each segment, and identified where gaps might still exist.

Modelling and planning tools needed for integrating energy storage technologies into the electrical grid

It is clear, both in this work and through individual projects and discussions with stakeholders, that development of new tools is critical to the industry in several key areas. New or improved models would:

1. Enable planners to accurately assess Energy Storage against alternatives: Within the long-term planning processes, stakeholders need to be able to assess energy storage technologies in various applications and operating scenarios, and compare it to traditional alternatives in order to assess the cost and operational benefits. In the portfolio planning process, which assesses the long-term capacity plans of regional systems, current models are limited in their ability to value storage, as basic models lack the ability to optimize between energy and ancillary service markets. Many cost production models are also limited in their ability to integrate, analyze and value other benefit streams such as fast ramp capability, due to longer dispatch intervals (often hourly), without excessive run-time or custom code.
2. Ensure the impact of energy storage integration is well understood: At the transmission and distribution planning levels, it is possible in many cases to use existing tools to create custom models for energy storage devices. However, this can require significant effort, and the lack of standardization and integration in existing tools leads to areas for improvement in order to ensure consistent and uniform analysis of optimum energy storage locational placement on the grid and to analyze various dispatch scenarios. Increased detail at this level and the distribution management system (DMS) level, would also allow various stakeholders to validate the behaviour of these new technologies in a safe, simulated environment, and ensure protection and control scenarios are well understood prior to build out.
3. Assist grid regulators and operators in operations and forecasting: In markets which operate on a day-ahead or hour-ahead basis, detailed forecasts of market prices for both energy and ancillary services are critical. This has become more difficult with the increased introduction of variable generation resources such as wind and solar, but existing tools used by Independent System Operators (ISOs) have largely been upgraded to include these assessments. Many suggest that this is also starting to be true for energy storage devices, however it is not clear to all market participants how energy storage is being treated in these forecasts, which limits the ability of energy storage developers and operators to ensure systems are designed and built to meet these needs most efficiently.

For new modelling and forecasting tools to be effective, significant collaboration is required from across the sector. It is important that these models be developed in partnership between holders of technical, system and financial information so a robust, industry-accepted, standard methodology can be developed and used consistently across many jurisdictions. That way, software developers can ensure that the functionality and performance of systems are accurately represented in each of the decision-support tools and the results from various simulations can be compared, leading to better, more informed decision-making.

Recently, the National Research Council Canada (NRC) and Alberta Electric System Operator (AESO) took a small step to advance the status quo of simulation models available to evaluate the performance of energy storage on the grid.

AESO case study

NRC recently led a project commissioned by the Alberta Electric System Operator (AESO) to assess the relative impact of including fast-acting energy storage systems in a mixed fleet of regulating reserves. The simulation results showed that distinct performance improvements could be attained by adopting the new capabilities provided by a generic energy storage technology; however, it also revealed several limitations of the modelling framework currently available to industry.

Read more about the AESO project.

What did we learn from this experience?

• The analysis revealed that fast-acting assets positively impact system response times under certain conditions, with overall fleet performance being highly dependent on how closely the assets are operating to the limits of their regulating reserve range. Additional study is required to adequately inform a specific policy reform or change to the requirement for regulating reserves due to the complexity of the analysis, and the interplay of both technical and market factors.
• At 100% replacement (all conventional assets replaced by fast-acting assets), the performance was inconclusive as the simulation results only revealed control instability. This behaviour could be a result of the current AGC control philosophy being incompatible with the fast–acting assets, and system planners and operators need updated simulation and modelling tools in order to assess these new technologies, and use them efficiently.
• Regulators and policy makers are looking for better information on how market structures and triggers may hinder planners and operators from harnessing the potential value of new technologies such as energy storage.

The opportunity ahead

The conversation happening here in Canada, regarding how to design, model, build, deploy and operate energy storage, is also occurring in other electricity jurisdictions around the world. Through projects and collaborations with organizations nationally and internationally, as well as projects with individual proponents, NRC is working to bring updated tools and guidance to users across the country:

• Canadian Energy Storage Roadmap: This project initiates, for the first time, a holistic approach to develop and maintain a multi-year (2016-2021) electricity storage roadmap for Canada. It aims to understand market potential, roadblocks and actions required at the planning, procurement, rate treatment, interconnection, market and regulations steps for adopting energy storage technologies in Canada. Specifically, the project will: identify energy storage use cases, define specific application requirements, identify the impacts on grid power planning and operation, and review the current market potential in each electricity market in Canada using frameworks and methodologies that build on the updated models above. It is intended that this will result in fair and practical frameworks and mechanisms, published and updated annually, that truly assess the value of storage at a portfolio level.
• NSERC Energy Storage Technology Network (NEST): This research network, announced in March 2016 and led by Ryerson’s Centre for Urban Energy, has been organized to address more fundamental research gaps identified in each of its 4 themes: (1) Energy Storage Technologies, (2) Power Electronics, (3) System Integration and (4) Economics, Policy and Environment. Both NRC and CanmetENERGY have been involved in the development and approval of this network, and have members on the research steering committees, as well as have individual researchers working closely with principle investigators in the network. Through these engagements, NRC’s goal is to ensure developments in each area are aligned and leveraged where necessary to ensure an effective transition from invention to innovation, including the deployment of newly developed modelling methodologies and frameworks.
• Energy Storage Integration Council (ESIC): The Electric Power Research Institute (EPRI), together with utilities, integrators, research organizations and industry experts created the Energy Storage Integration Council (ESIC). The mission of ESIC is to guide a discussion and develop common approaches to achieve some level of standardization for reliable, safe and cost-effective energy storage options for the utility industry. NRC supports ESIC through participation in several of the working groups: 1) Applications, 2) Performance, 3) System Development 4) Grid Integration, and 5) Analysis. As part of these activities, NRC is working to standardize the collection of data for these models, including the cost templates, integration, and commissioning guidelines. The Analysis working group, in particular, is focused on developing methods and defining data and model requirements for considering energy storage in planning and operations processes. These activities, once translated into the needs of Canadian jurisdictions, lay the foundation for the development of new planning models.

Through projects such as these, it is expected that the next generation tools will enable grid operators and planners of the future to deploy energy storage onto the grid in an effective, reliable and cost effective manner. Learn more about how to get involved in these and other upcoming research projects