Optimal use of energy storage systems with renewable energy sources

a b s t r a c t This article proposes a multi-period optimization to study the technical and economic effects of the placement and use of Renewable Energy Sources (RES) and Energy Storage Systems (ESS) in an electrical network. As the RES penetrations increase, their inherent variability affects the actual amounts of energy dispatched, their contribution to decrease emissions of pollutants and greenhouse gases, and the overall welfare effects they may have. Moreover, to better harness the energy from renewable sources, both new methodologies and technologies need to be adopted, counteracting the variability and uncertainty of these sources. A possible solution to the challenges of RES adoption is the coupling to energy storage sources, either as dedicated facilities on the supply side, or supporting the accommodation of loads to the available generation on the demand side. This paper suggests an algorithm for network dispatch, aimed at answering some of fundamental changes in the way the system is managed and discusses analytical characteristics of the optimal solution. The proposed methodology is applied to a case study. Four scenarios are analyzed in their dispatches, estimating the welfare effects on the participants in the wholesale market for a modified IEEE 30-bus network with wind energy as the RES in penetrations close to 15%. The policy implications from the results obtained prove that, first, ESS can decrease the ramping necessary for load following, but not necessarily increase the amount of wind energy used, and second, congestion patterns in the electrical network play a crucial role in the final effectiveness of the RES and ESS. These are important insights into an ongoing debate on how to direct storage and renewable energy investments for a low carbon economy

Shale Gas vs. Coal

Abstract: The aim of this paper is to examine the environmental impacts of shale gas, conventional gas and coal on air, water, and land in the United States. These factors decisively affect the quality of life (public health and safety) as well as local and global environmental protection. Comparing various lifecycle assessments, this paper will suggest that a shift from coal to shale gas would benefit public health, the safety of workers, local environmental protection, water consumption, and the land surface. Most likely, shale gas also comes with a smaller GHG footprint than coal. However, shale gas extraction can affect water safety. This paper also discusses related aspects that exemplify how shale gas can be more beneficial in the short and long term. First, there are technical solutions readily available to fix the most crucial problems of shale gas extraction, such as methane leakages and other geo-hazards. Second, shale gas is best equipped to smoothen the transition to an age of renewable energy. Finally, this paper will recommend tighter regulations

THE HIDDEN SYSTEM COSTS OF WIND GENERATION IN A DEREGULATED ELECTRICITY MARKET

WP 2011-01Earlier research has shown that adding wind capacity to a network can lower the total annual operating cost of meeting a given pattern of loads by displacing conventional generation. At the same time, the variability of wind generation and the need for higher levels of reserve generating capacity to maintain reliability standards impose additional costs on the system that should not be ignored. The important implication for regulators is that the capacity payments [“missing money”] for eachMW of peak system load is now much higher. Hence, the economic benefits to a network of using storage, controllable load and other mechanisms to reduce the peak system load will be higher with high penetrations of wind generation. These potential benefits are illustrated in a case study using a test network and a security constrained OPF with endogenous reserves (SuperOPF). The capabilities of the SuperOPF provide a consistent economic framework for evaluating Operating Reliability in real-time markets and System Adequacy for planning purposes. The scenarios considered make it possible to determine 1) the amount of conventional generating capacity needed to meet the peak system load and maintain System Adequacy, and the amount of wind dispatched, 2) total payments by customers in the Wholesale Market, and the amount of missing money paid to generators to maintain their Financial Adequacy, 3) changes in the congestion rents for transmission that are collected by the system operator, and finally, 4) the total annual system costs paid by customers directly in the Wholesale Market and, indirectly, as missing money. The results show that the benefits (i.e. the reduction in the total annual system costs) from making an investment in wind capacity and/of upgrading a tie line are very sensitive to 1) how much of the inherent variability of wind generation is mitigated, and 2) how the missing money paid to conventional generators is determined (e.g. comparing a regulated market with a deregulated market).This research was supported by the US Department of Energy through the Consortium for Electric Reliability Technology Solutions (CERTS) and by the Power Systems Engineering Research Center (PSERC)

Uncertainty-Informed Renewable Energy Scheduling: A Scalable Bilevel Framework

Accommodating the uncertainty of variable renewable energy sources (VRES) in electricity markets requires sophisticated and scalable tools to achieve market efficiency. To account for the uncertain imbalance costs in the real-time market while remaining compatible with the existing sequential market-clearing structure, our work adopts an uncertainty-informed adjustment toward the VRES contract quantity scheduled in the day-ahead market. This mechanism requires solving a bilevel problem, which is computationally challenging for practical large-scale systems. To improve the scalability, we propose a technique based on strong duality and McCormick envelopes, which relaxes the original problem to linear programming. We conduct numerical studies on both IEEE 118-bus and 1814-bus NYISO systems. Results show that the proposed relaxation can achieve good performance in accuracy (0.7%-gap in the system cost wrt. the least-cost stochastic clearing benchmark) and scalability (solving the NYISO system in minutes). Furthermore, the benefit of the uncertainty-informed VRES-quantity adjustment is more significant under higher levels of VRES (e.g., 70%), under which the system cost can be reduced substantially compared to a myopic day-ahead offer strategy of VRES.Comment: Submitted to IEEE PES general meeting 202

The Economic Value of Distributed Storage at Different Locations on an Electric Grid

Classified as relating to American Economic Association JEL Codes: L94, Q48, D40The objective of this article is to analyze the system benefits of distributed storage at different locations on a grid that has a high penetration of renewable generation. The chosen type of distributed storage modeled is deferrable demand (e.g., thermal storage) because it is relatively inexpensive to install compared to batteries and could potentially form a large component of the peak system load. The advantage of owning deferrable demand is that the purchase of energy from the grid can be decoupled from the delivery of an energy service to customers. Consequently, these customers can reduce costs by shifting their purchases from expensive peak periods to off-peak periods when electricity prices are low. In addition, deferrable demand can provide ramping services to the grid to mitigate the uncertainty of renewable generation. The primary economic issue addressed in this paper is to determine how the storage capacity is allocated between shifting load and providing ramping services. The basic economic tradeoff is between the benefit from shifting more load from peak periods to less expensive periods, and reserving some storage capacity for ramping to reduce the amount of conventional reserve capacity purchased. Our approach uses a new form of stochastic, multi-period Security Constrained Optimal Power Flow (SCOPF) that minimizes the expected system costs for energy and ancillary services over a 24-hour horizon. For each hour, five different levels of wind generation may be realized and these are treated as different system states with known probabilities of occurring. This model is applied to a reduction of the grid in New York State and New England and simulates the hourly load on a hot summer day, treating potential wind generation at different sites as stochastic inputs. The results determine the expected amount and location of conventional generating capacity dispatched, the reserve capacity committed to maintain operating reliability, the charging/discharging of storage capacity, and the amount of potential wind generation spilled. The results show there are major differences in how the deferrable demand at two large load centers, Boston and New York City, is managed, and we provide an explanation for these differences.This research was supported by the Lehigh Faculty Innovation Grant and the National Science Foundation through the CyberSEES grant #1442858

Integration of Stochastic Power Generation, Geographical Averaging and Load Response

WP 2011-09 February 2011The objective of this paper is to analyze how the variability of wind affects optimal dispatches and reserves in a daily optimization cycle. The Cornell SuperOPF1 is used to illustrate how the system costs can be determined for a reliable network (the amount of conventional generating capacity needed to maintain System Adequacy is determined endogenously). Eight cases are studied to illustrate the effects of geographical distribution, ramping costs and load response to customers payment in the wholesale market, and the amount of potential wind generation that is dispatched. The results in this paper use a typical daily pattern of load and capture the cost of ramping by including additions to the operating costs of the generating units associated with the hour-to-hour changes in their optimal dispatch. The proposed regulatory changes for electricity markets are 1) to establish a new market for ramping services, 2) to aggregate the loads of customers on a distribution network so that they can be represented as a single wholesale customer on the bulk-power transmission network and 3) to make use of controllable load and geographical distribution of wind to mitigate the variability of wind generation as an alternative to upgrading the capacity of the transmission network