Intermittent Renewable Management Pilot Phase 2

Problem definition: The rapid expansion of distributed energy resources (DERs) is one of the most significant changes to electricity systems around the world. Examples of DERs include solar panels, electric storage, thermal storage, and combined heat and power plants. Because of the small supply capacities of these DERs, it is impractical for them to participate directly in the wholesale electricity market. We study in this paper the question of how to integrate these DER supplies into the electricity market, with the objective of achieving full market efficiency. Methodology/results: We study four aggregation models, where there is an aggregator who, with the knowledge of DERs’ utility functions and generations, procures electricity from DERs, and sells them in the wholesale market. In the first aggregation model, a profit-maximizing aggregator announces a differential two-part pricing policy to the DER owners. We show that this model preserves full market efficiency, that is, the social welfare achieved by this model is the same as that when DERs participate directly in the wholesale market. In the second aggregation model, the profit-seeking aggregator is forced to impose a uniform two-part pricing policy to prosumers from the same location, and we numerically show that there can be large efficiency loss. In the third (fourth) aggregation model, a uniform (semiuniform) two-part pricing policy is applied to DER owners, whereas the aggregator becomes fully regulated but is guaranteed nonnegative (positive) profit. It is shown that these models again achieve full market efficiency. Furthermore, we show that DER aggregation also leads to a reduction in the market power of conventional generators. Managerial implications: DER aggregation via profit-seeking and/or regulated aggregators has been investigated by California Independent System Operator and New York Independent System Operator, among others, and the recent Federal Energy Regulatory Commission Order No. 2222 paved the way for aggregators to bid in the wholesale market. Our four aggregation models may shed light on how DERs should be included in the wholesale electricity market. Funding: This work was supported by the King Fahd University of Petroleum and Minerals [Grant INML2106] and the National Science Foundation [Grant 1832230]. Supplemental Material: The online appendices are available at https://doi.org/10.1287/msom.2021.0539 .

The Demand Response Spinning Reserve project is a pioneering demonstration showing that existing utility load-management assets can provide an important electricity system reliability resource known as spinning reserve. Using aggregated demand-side resources to provide spinning reserve as demonstrated in this project will give grid operators at the California Independent System Operator (CA ISO) and Southern California Edison (SCE) a powerful new tool to improve reliability, prevent rolling blackouts, and lower grid operating costs.In the first phase of this demonstration project, we target marketed SCE?s air-conditioning (AC) load-cycling program, called the Summer Discount Plan (SDP), to customers on a single SCE distribution feederand developed an external website with real-time telemetry for the aggregated loads on this feeder and conducted a large number of short-duration curtailments of participating customers? air-conditioning units to simulate provision of spinning reserve. In this second phase of the demonstration project, we explored four major elements that would be critical for this demonstration to make the transition to a commercial activity:1. We conducted load curtailments within four geographically distinct feeders to determine the transferability of target marketing approaches and better understand the performance of SCE?s load management dispatch system as well as variations in the AC use of SCE?s participating customers;2. We deployed specialized, near-real-time AC monitoring devices to improve our understanding of the aggregated load curtailments we observe on the feeders;3. We integrated information provided by the AC monitoring devices with information from SCE?s load management dispatch system to measure the time required for each step in the curtailment process; and4. We established connectivity with the CA ISO to explore the steps involved in responding to CA ISO-initiated requests for dispatch of spinning reserve.The major findings from the second phase of this demonstration are:1. Demand-response resources can provide full response significantly faster than required by NERC and WECC reliability rules.2. The aggregate impact of demand response from many small, individual sources can be estimated with varying degrees of reliability through analysis of distribution feeder loads.3. Monitoring individual AC units helps to evaluate the efficacy of the SCE load management dispatch system and better understand AC energy use by participating customers.4. Monitoring individual AC units provides an independent data source to corroborate the estimates of the magnitude of aggregate load curtailments and gives insight into results from estimation methods that rely solely on distribution feeder data.

Robust bidding strategy for aggregation of distributed prosumers in flexiramp market

This project develops an innovative, integrated, and transformative approach to mitigate the impact of wind ramping by providing flexible ramping products from wind power. The project will significantly contribute to the reduction of wind integration costs by making wind power dispatchable and allowing the efficient management of wind ramping characteristics. In addition, we collaborated with industry to test and validate the methodology, considering economic and reliability goals, by integrating the proposed methodology into the simulated market frameworks of two independent system operators: California Independent System Operator and the Electric Reliability Council of Texas.

There is a great need to identify prudent practices and share lessons learned from the California electric market restructuring effort. The changes of the electric wholesale and retail market have necessitated monumental change to the existing operating systems in California. Be assured of one thing, there is no "magical formula" for restructuring a wholesale and retail market or creating an independent system operator (ISO). Each nation, province, state, municipality, or location must best determine the course that is appropriate and functional in order to meet the respective needs. This paper deals with the issues, truths, and real problems arising from the restructuring in California from a perspective of system operation. The paper is intended to be a "mentor" to the would-be ISO, a tutor to diverse participants, and a refreshing touch with the reality and requirements of real-time operation.

Increasing share of variable nature wind energy sources impose several technical challenges to power system operation as it is difficult to forecast its power output due to wind turbine provides intermittent power. Compressed air energy storage (CAES) as a flexible source with high ramp rate could be an alternative solution to reduce wind power production uncertainty effect on power system operation cost. Also, California independent system operator (CAISO) has designed a new market for flexible ramping products in order to verify the reliability of power system processes, enough ramp ability should exist for meeting the variability of net load in real-time dispatch stages. This study introduces a problem of stochastic security-constrained unit commitment (SCUC) with the integration of CAES unit considering flexible ramping products to manage the variability of power generated by wind turbines. A six-bus system considered to perform numerical tests and show the high performance of the introduced model.

The cost and quality of regulation have been brought to the forefront of power system operations by renewable variability. We propose a regulation pricing methodology based on an idea of Berger and Schweppe: in the same manner that locational marginal prices are derived from the dual of economic dispatch, let regulation prices be the dual multipliers or costate of an optimal control problem. By specializing to the linear quadratic regulator, we formulate a regulation pricing policy, which in turn allows us to derive statistically correct payments such as imbalance fees. We then construct a Vickrey-Clarke-Groves mechanism to induce selfish agents to honestly report their private valuations and costs of regulation. Semidefinite programming descriptions of the formulation can be embedded within standard convex economic dispatch constraint sets, enabling cooptimization of base load and regulation pricing. The approach mechanistically produces prices for any dynamic scenario, and can therefore be used to consolidate diverse regulation services. We demonstrate this feature by combining traditional frequency regulation, area control error, and the California Independent System Operator's Flexible Ramping Product in an example.

In this report we compare the output of the California Independent System Operator (CAISO) 33% RPS Plexos model when run on various computing systems. Specifically, we compare the output resulting from running the model on CAISO's computers (Windows) and LLNL's computers (both Windows and Linux). We conclude that the differences between the three results are negligible in the context of the entire system and likely attributed to minor differences in Plexos version numbers as well as the MIP solver used in each case.

This paper describes the operation of the new realtime energy market at CAISO. The new real-time market utilizes the security constrained unit commitment (SCUC) and security constrained economic dispatch (SCED) programs to optimally determine resource commitments and dispatch schedules while observing resource and system real-time constraints [AI Cohen, et al., 1999]. The SCED calculates three prices: the dispatch interval ex-post market clearing price (MCP) and two weighted-average prices based on the dispatch interval ex-post MCP. This paper describes the scheduling activities of the CAISO new realtime market followed by the major scheduling applications. The scheduling market timeline and scheduling application interfaces are also described.

Over the past decade, there has been a resurgence of interest among system operators, policy makers and other grid stakeholders in the expanded utilization of energy storage (ES) and demand response resources (DRRs) to address power system economic and environmental concerns. In this work, we construct a general ES resource (ESR) model, which encompasses DRRs as a special case and explicitly represents the physical and economic attributes of integrated grid-scale ES and DRRs and aggregations of smaller-scale ES and DRRs. We deploy this model in a market simulation framework to perform a systematic side-by-side comparison of the economic and emission impacts of ES and DRRs in networks operated/controlled by an independent system operator/regional transmission organization and in its associated day-ahead markets. This analysis points out the limits to the penetrations below which an added MW of ES or DRR no longer brings about decreases in buyer payments and that the benefits that accrue to DRRs are disproportionately larger than the benefits to buyers and ESRs. Further, we find that ES and DRRs have little impact on reducing system-wide emissions. In fact, we find that their utilization may even result in emission increases in some cases. These findings provide insights into nature of the ES and DRR market impacts which are useful for grid stakeholders interested in the integration of appropriate penetrations of such resources.

The Resource Forecast and Ramp Visualization for Situational Awareness (RAVIS) is an open-source tool for visualizing variable renewable resource forecasts and ramp alerts for significant up/down ramps in renewable resource and the consequent net-load. The modular dashboard of RAVIS contains configurable panes for viewing- probabilistic time series forecasts, ramp event alerts on the look-ahead timeline, spatially resolved resource sites and forecasts, and system simulation and market clearing data such as transmission lines utilization, nodal prices and available generation flexibility. RAVIS uses a technology suite that is assembled to provide optimum visualization facility while maintaining a wide pool of potential deployment and client environments. The tool is designed to take advantage of web application technologies, open source visualization libraries and tooling. Utilizing this technology will enable deployment in any environment, using any operating system, and is scalable to much higher spatial and temporal scales of visualization. As a prototype of the tool and demonstrating a use case of variable renewable integration, RAVIS currently integrates site-specific solar power forecasts in the California Independent System Operator (CAISO) and Mid-continent ISO (MISO) footprint from the IBM WattSun forecasting platform, and also superimposes market simulation data for CAISO footprint from as in-house NREL market clearing tool. The tool has the ability to alert the viewer for excessive up or down ramps for both individual solar sites as well as regionally aggregated net-load ramps, and alerts can also be qualified with respect to available flexible generation. This report will provide an introduction to the RAVIS tool, and summarize the above mentioned capabilities, typical use cases and possible extensions of the tool. The RAVIS development team believes there are likely to be high economic and reliability benefits of integrating probabilistic forecasts of variable renewables into control center visualizations and improved ramp events situational awareness for system operators and forecasting teams in the ISOs and electric utilities in comparison with their business as usual practices.

In a re-structured environment, demand response (DR) programs are presented in a new style. The demand response program consists of demand-side management methods which answers to electricity price variations. With advent of electricity markets, the demand-side management programs was introduced into two categories: (1) energy efficiency program, (2) demand response program. This paper studies engagement of participants load in an electricity market having a grid with large and small loads interested to participate in the market, energy storage systems, micro-grids, and distributed generations. In the proposed scheme, it is supposed to have an aggregator which sends demand-side preferences including load curtailment, load shifting, onsite generation, and energy storage systems along with proposed value and prices and all respective system constraints to the independent system operator (ISO). In fact, load aggregators submit aggregated DR offers to the ISO in order to optimize final decisions on aggregators’ DR contributions in wholesale market. The main goal of this paper is to solve the operation problem considering demand-side, system, and pollution and reliability constraints. Compared to other methods, the results indicate that the explicit modeling of customer DR would provide ISOs with more flexible options for scheduling the available energy resources in day-ahead energy markets.

Decomposition based approaches are recalled from primal and dual point of view. The possibility of building partially disaggregated reduced master problems is investigated. This extends the idea of aggregated-versus-disaggregated formulation to a gradual choice of alternative level of aggregation. Partial aggregation is applied to the linear multicommodity minimum cost flow problem. The possibility of having only partially aggregated bundles opens a wide range of alternatives with different trade-offs between the number of iterations and the required computation for solving it. This trade-off is explored for several sets of instances and the results are compared with the ones obtained by directly solving the natural node-arc formulation. An iterative solution process to the route assignment problem is proposed, based on the well-known Frank Wolfe algorithm. In order to provide a first feasible solution to the Frank Wolfe algorithm, a linear multicommodity min-cost flow problem is solved to optimality by using the decomposition techniques mentioned above. Solutions of this problem are useful for network orientation and design, especially in relation with public transportation systems as the Personal Rapid Transit. A single-commodity robust network design problem is addressed. In this, an undirected graph with edge costs is given together with a discrete set of balance matrices, representing different supply/demand scenarios. The goal is to determine the minimum cost installation of capacities on the edges such that the flow exchange is feasible for every scenario. A set of new instances that are computationally hard for the natural flow formulation are solved by means of a new heuristic algorithm. Finally, an efficient decomposition-based heuristic approach for a large scale stochastic unit commitment problem is presented. The addressed real-world stochastic problem employs at its core a deterministic unit commitment planning model developed by the California Independent System Operator (ISO).

The entire project addresses the issue of mitigating additional intermittency and fast ramps that occur at higher penetration of intermittent resources, including wind genera-tion, in the Bonneville Power Administration (BPA) and the California Independent Sys-tem Operator (California ISO) control areas. The proposed Wide Area Energy Storage and Management System (WAEMS) will address the additional regulation requirement through the energy exchange between the participating control areas and through the use of energy storage and other generation resources. For the BPA and California ISO control centers, the new regulation service will look no different comparing with the traditional regulation resources. The proposed project will benefit the regulation service in these service areas, regardless of the actual degree of penetration of the intermittent resources in the regions. The project develops principles, algorithms, market integration rules, functional de-sign and technical specifications for the WAEMS system. The project is sponsored by BPA and supported in kind by California ISO, Beacon Power Corporation, and the Cali-fornia Energy Commission (CEC).

The state of California is leading the nation with respect to solar energy and storage. The California Energy Commission has mandated that starting in 2020 all new homes must be solar powered. In 2010 the California state legislature adopted an energy storage mandate AB 2514. This required California's three largest utilities to contract for an additiona11.3 GW of energy storage by 2020, coming online by 2024. Therefore, there is keen interest in the potential advantages of deploying solar combined with energy storage. This paper formulates the optimization problem to identify the maximum potential revenue from pairing storage with solar and participating in the California Independent System Operator (CAISO) day ahead market for energy. Using the optimization formulation, five years of historical market data (2014-2018) for 2,172 price nodes were analyzed to identify trends and opportunities for the deployment of solar plus storage.