Baseload wind energy: modeling the competition between gas turbines and compressed air energy storage for supplemental generation

Greenblatt, Jeffery B.; Succar, Samir; Denkenberger, David; Williams, Robert H.; Socolow, Robert H.

doi:10.1016/j.enpol.2006.03.023

Cited by 196 publications

(116 citation statements)

References 19 publications

(27 reference statements)

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“…How to design and use CAES for load levelling in the electricity supply has been analysed and discussed for several decades in academic literature [1][2][3][4]. In recent years, CAES has primarily been seen as a means of improving the integration of fluctuating wind power into the electricity supply [5][6][7][8][9] or it has been compared to other electricity storage options [10,11]. However, so far the optimisation of CAES operation on electricity spot markets has not been dealt with.…”

Section: Introductionmentioning

confidence: 99%

Optimal operation strategies of compressed air energy storage (CAES) on electricity spot markets with fluctuating prices

Lund

Salgi

Elmegaard

et al. 2009

Applied Thermal Engineering

220

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Section: Introductionmentioning

confidence: 99%

Optimal operation strategies of compressed air energy storage (CAES) on electricity spot markets with fluctuating prices

Lund

Salgi

Elmegaard

et al. 2009

Applied Thermal Engineering

220

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“…It has been shown that optimally sized electricity storage could result in more economic operation of both wind farms and the storage itself by taking advantage of arbitrage, ancillary services, and transmission and balancing costs (Korpaas et al, 2003b;Castronuovo and Lopes, 2004;Leou, 2008;Greenblatt et al, 2007;Lund et al, 2009;Kaldellis et al, 2009;Zafirakis and Kaldellis, 2009;Sioshansi, 2011;Tuohy and O'Malley, 2011). In addition, the distributed storage system has the potential to reduce the electricity cost of the household (Ahlert and Block, 2010).…”

Section: Introductionmentioning

confidence: 99%

The impact of electricity storage on wholesale electricity prices

Nyamdash

Denny

2013

Energy Policy

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This paper analyzes the impact of electricity storage on the production cost of a power system and the marginal cost of electricity (electricity price) using a unit commitment model. Also real world data has been analyzed to verify the effect of storage operation on the electricity price using econometric techniques. The unit commitment model found that the deployment of a storage system reduces the fuel cost of the power system but increases the average electricity price through its effect on the power system operation. However, the reduction in the production cost was found to be less than the increase in the consumer's cost of electricity resulting in a net increase in costs due to storage. Different storage and CO 2 price scenarios were investigated to study the sensitivity of these results. The regression analysis supports the unit commitment results and finds that the presence of storage increases average wholesale electricity prices for the case study system.

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“…A comparison between gas turbines and compressed air energy storage as competitors for supplemental generation has been performed by Greenblatt et al [7]. It has been shown that the wind+CAES system has the lowest dispatch cost of the alternatives considered (lower even than for coal power plants) above a green house gas (GHG) emissions price of $35/tCequiv., with good prospects for realizing a higher capacity factor and a lower total cost of energy than all the competing technologies over a wide range of effective fuel costs.…”

Section: Introductionmentioning

confidence: 99%

The effect of key parameters on the design of an optimized caes power plant

Assadi

Shamshirgaran

Rad³

2016

MATEC Web of Conferences

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Abstract. Due to the significant variations in electricity generation and its demand, the power plant owners are encountered with challenges of economic operation. Among all, Compressed air energy storage (CAES) technology has proposed itself as a reliable and efficient solution to match the two sides. This paper deals with a modeled compressed air energy storage power plant which has been optimized thermodynamically through an efficient genetic algorithm code. The results of this optimized model, considered as the base case, show that the power plant is technically and financially justifiable. In order to obtain a more tangible realization, it is necessary to verify the results against the variation of key parameters. In this study, the sensitivity analysis is performed based on main parameters including plant loading and ambient condition and the resultant trends of each case are presented. This approach will help the designers to analyze the quality of their designs in different situations.

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Baseload wind energy: modeling the competition between gas turbines and compressed air energy storage for supplemental generation

Cited by 196 publications

References 19 publications

Optimal operation strategies of compressed air energy storage (CAES) on electricity spot markets with fluctuating prices

Optimal operation strategies of compressed air energy storage (CAES) on electricity spot markets with fluctuating prices

The impact of electricity storage on wholesale electricity prices

The effect of key parameters on the design of an optimized caes power plant

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