Abstract
Due to the variable nature of wind resources, the increasing penetration level of wind power will have a significant impact on the operation and planning of the electric power system. Energy storage systems are considered an effective way to compensate for the variability of wind generation. This paper presents a detailed production cost simulation model to evaluate the economic value of compressed air energy storage (CAES) in systems with large-scale wind power generation. The co-optimization of energy and ancillary services markets is implemented in order to analyze the impacts of CAES, not only on energy supply, but also on system operating reserves. Both hourly and 5-minute simulations are considered to capture the economic performance of CAES in the day-ahead (DA) and real-time (RT) markets. The generalized network flow formulation is used to model the characteristics of CAES in detail. The proposed model is applied on a modified IEEE 24-bus reliability test system. The numerical example shows that besides the economic benefits gained through energy arbitrage in the DA market, CAES can also generate significant profits by providing reserves, compensating for wind forecast errors and intra-hour fluctuation, and participating in the RT market.
Highlights
IntroductionThere has been significant growth in wind capacity in the US because of advancements in wind generation technology, government subsidies, and other policy incentives [1]
In the last decade, there has been significant growth in wind capacity in the US because of advancements in wind generation technology, government subsidies, and other policy incentives [1].With the focus on promoting the use of renewable energy, the efficient and cost-effective integration of wind energy to the grid is becoming increasingly important.A number of studies have been carried out to evaluate the possibility of using various kinds of Energy Storage Systems (ESS) to offset the wind generation variability [2,3,4,5,6]
Compared with existing models used in previous ESS economic studies, the proposed model has several major advantages: (1) the energy and ancillary services markets are co-optimized to capture all sources of ESS’ profits; (2) hourly and sub-hourly (5-minute) simulations are conducted to represent the day-ahead and real-time market operations; (3) ESS is modeled using a generalized network flow formulation which captures the characteristics of ESS in detail; (4) the wind forecast errors between DA and RT
Summary
There has been significant growth in wind capacity in the US because of advancements in wind generation technology, government subsidies, and other policy incentives [1]. A production cost simulation model is proposed to evaluate the economic value of CAES in systems with high wind penetration levels. Several operational impacts should be considered when evaluating the viability of incorporating energy storage systems to address wind integration issues: load following, scheduling, reserve requirement, ramping requirement, and wind forecast errors and intra-hour fluctuation [5]. Compared with existing models used in previous ESS economic studies, the proposed model has several major advantages: (1) the energy and ancillary services markets are co-optimized to capture all sources of ESS’ profits; (2) hourly and sub-hourly (5-minute) simulations are conducted to represent the day-ahead and real-time market operations; (3) ESS is modeled using a generalized network flow formulation which captures the characteristics of ESS in detail; (4) the wind forecast errors between DA and RT markets and wind/demand intra-hour fluctuations are considered in the simulation process. The article concludes with a summary of the benefits of the proposed model and the results of the case study
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