By Troy Nergaard, director of technical product management; and Bina Ansari, power systems engineer, for Doosan GridTech
The energy industry today continues to wrestle with the economics of solar. As the levelized cost of energy (LCOE) for solar continues to fall, distributed solar continues to gain adoption. Whether on rooftops, in community solar settings or in grid-scale plants, solar’s midday peak production has created many challenges for systems operators. One of the biggest is the well-known “duck curve” dilemma, in which utilities find themselves with more energy produced than is needed at the moment.
As utilities have struggled to respond to solar’s daily output peaks, most initially reacted by ramping up or down their legacy generation resources. However, these baseload resources (often coal or nuclear plants) were not originally designed for this new use. Turning off and then restarting these resources several times a day often proved difficult, inefficient and costly. Some markets have tried to lessen the duck curve effect by curtailing solar production, an irony since the very success and popularity of the renewable resource has led to it being blocked from greater use.
Energy storage has helped address some of the issues. As costs have fallen (and technologies such as lithium-ion batteries have improved), many utilities have begun to utilize it to significantly extend existing PV generation into off-peak hours. It’s a promising approach, yet storage adds still another asset into the mix of things utility system operators must manage and optimize.
Balancing economic and operational equations holistically
The hard work of adjusting to this industry transformation is taking place at many levels. Regulators, regional grid authorities, independent power providers (IPP), residential consumers, commercial and industrial energy users are all acting, reacting and reshaping their approaches. Yet it is utilities that face perhaps the greatest challenge since they own the task of matching energy supply and demand—reliably, safely and cost effectively.
Within their enterprise, each utility must balance its own economic and operational equations, finding the right mix of resources to deploy at the right time amidst an increasing number of factors. The old LCOE metric, long used to estimate the individual cost of a single asset, now faces new challenges. Utilities can no longer evaluate new generation resources purely on the cost of electricity produced. Rather, they must make planning and operational decisions between distributed energy resources (DERs) that affect each other and in turn are affected by a variety of market signals and operational data—on multiple timelines. A new, system-wide metric is needed; one that provides a more accurate valuation of the collection of resources within the actual environment and use-case it must serve.
Enter the system metric…
In the Austin SHINES project a new such metric is being developed. The “system LCOE to serve load” metric—called SLCOE—will provide a measure by which utilities and other power users can accurately evaluate the cost/benefits of solar within their entire system. The SLCOE metric is defined as the combined costs of all assets working together within the defined system boundary to reliably serve a unit of load demand. It is being developed collaboratively by Austin Energy and Doosan GridTech.
The U.S. Department of Energy Solar Energy Technologies Office (SETO) awarded Austin Energy $4.3 million for SHINES (Sustainable and Holistic Integration of Energy Storage and Solar PV). The project consists of DER including solar, smart inverters, electric vehicles and energy storage, plus a mix of forecasting tools, market signals, advance communications and an optimizer software platform.
Austin SHINES will field-prove a DER-management platform that optimizes both operational performance and economics. It aims to create value in five distinct use cases. Three are economic: energy arbitrage, real-time price dispatch and peak load reduction. Two are operational: voltage support and congestion management. In short, it must enable energy to be delivered to the system loads at the lowest possible cost, while maintaining grid reliability. The resulting SLCOE that will be demonstrated then becomes a tool that can be applied by any utility in any market with a high penetration of distributed energy resources.
Field-proving it at Austin SHINES
To establish a complex, real-world proving ground, Austin SHINES incorporated several different types of DERs and solutions from a number of partners and vendors. These include Doosan GridTech, Clean Power Research, ConnectDER, ERCOT, Landis+Gyr, LG Chem, Pecan Street, Samsung SDI, SolarEdge and Stem.
The diverse set of DERs (around 4.5 MW) being integrated is typical of the resources many utilities encounter. It includes utility-owned energy storage systems (ESS), community solar and distributed residential and commercial resources including rooftop solar, electric vehicles and energy storage on two separate distribution circuits.
These resources are managed and optimized by an overarching, intelligent system, Doosan GridTech’s DER Optimizer (DERO), which acts on data from multiple sources. This is the heart of the project, where SLCOE is worked out. DERO sits in the utility control room and acts to manage and optimize the entire fleet of DERs across the utility enterprise based on its analysis of data from all potential sources. While some distributed energy resource management systems (DERMS) may monitor and control utility assets from a purely operational perspective, DERO adds the ability to optimize the economic value. It determines which resource to deploy at which time—not only the best operational choice but the best economic one.
To fulfill this role, DERO needs to gather data, analyze it and act on it. The system architecture includes technical operational data coming up from DER, including from energy storage systems, customer meters, solar inverters and aggregators. It also incorporates enterprise data coming from the utility’s SCADA/ADMS. DERO also gathers economic data from multiple sources including ERCOT market signals and forecasting. The system uses open standards for both controls and communications, so it can readily integrate and add more elements as needed.
This is literally the “data deluge” utilities have seen coming since the first smart meters shook up the industry, transforming monthly usage data into every-15-minute data packets. Today’s data timescales are exponentially more complex. Data can arrive at the millisecond (like some PV/ESS PCS), at the second (cloud-induced solar volatility), by the minute (ERCOT forecasts every five minutes; economic settlement occurs every 15 minutes), by the hour (batteries that can discharge for several hours), by the season (variations in demand or output as weather changes), by the year or even by the decade (the lifetime of an ESS).
DERO receives, analyzes and acts on all this data and determines the highest value use cases at five-minute intervals.
Value in regulated and deregulated markets
Austin SHINES calculates value with information from the ERCOT market. That is an approach unique to this specific regional market today. Across the country, approaches to regulation of markets and the role of utilities in DER management vary widely and are still evolving. While value is measured differently in each, the concept of value is universal.
Under NY-REV, for example, utilities are experimenting with platforms into which all DERs connect, interact and transact. In such a scenario, value would be less about being compensated for capital assets and more performance-based. The challenge is to manage all the power on multiple planes, optimizing it in a real, ongoing way.
The lessons being learned at Austin SHINES on how to maximize value in high-penetration DER systems can act as an operational template to utilities in any market structure or region. The system levelized cost of energy (SLCOE) metric that emerges from the unique, DERO-driven approach being demonstrated there is an important tool. By establishing a system-wide way to measure value, one that can act on and analyze value in flexible and responsive ways, the SLCOE offers a key tool to advancing the holistic view of how DERs can provide value to utility systems and to the broader grid as it continues to evolve.
About the authors
Troy Nergaard – Director of Technical Product Management
As Doosan GridTech’s Director of Technical Product Management, Troy has overseen the installation of pioneering megawatt-scale battery systems and the deployment of the Doosan’s energy storage system fleet control and DER optimization software platform for Snohomish County Public Utility District and Austin Energy. Prior to Doosan, Troy was a Sr. Engineering Manager at Tesla Motors where he brought progressive software product developments forward for its emerging electric vehicle charging sector. Troy holds a BSEE from the University of Wisconsin-Madison and a MSEE, Power Electronics from Virginia Tech.
Bina Ansari, Ph.D. – Power Systems Engineer
Bina Ansari, Ph.D. is a power systems engineer with Doosan GridTech contributing to electric grid modeling and simulation/data processing and analytics, and developing solutions for the emerging industry of smart distributed grids. Prior to joining Doosan, she worked for New York Power Authority and NEC Laboratories America Inc. where her research analysis in renewable energy integration, energy storage and grid resilience contributed to several peer-reviewed, industry journal articles on advancements in energy management/modeling applications and demand response systems. She holds a B.S. degree in Electrical Engineering from Amirkabir University, a M.S. degree in Electrical Engineering from the University of Tehran and earned her Ph.D. degree in Electrical Engineering from the Colorado School of Mines.