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Reducing power system costs with thermal energy storage

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  • Naranjo Palacio, Santiago
  • Valentine, Keenan F.
  • Wong, Myra
  • Zhang, K. Max

Abstract

Thermal energy storage (TES) have been shown to be locally beneficial, helping building managers reduce their electricity bills. Due to increasing interest in TES, it is important for utilities and policy-makers alike to consider the economic implications of increasing TES penetration levels on to the power system. The aim of this paper is to show that TES can also bring significant benefits, and that these benefits are maximized when loads are properly controlled. This paper studies the effect of a heuristic optimal TES load allocation strategy on the New York Independent System Operator (NYISO) system’s load factor, peak-to-valley ratio, ramping, and operation costs. These results are also compared to different control methods in order to justify the need for such a model and also to justify the results. We first determine the total amount of cooling load that can be shifted in New York State through the use of TES technology by using data from various government agencies. Using a coefficient of performance (COP) model for the chiller to account for efficiency changes throughout the day, the flexible cooling demand for the system is estimated. A method to optimally allocate flexible cooling loads is then used with the goal of reducing the power system cost, while providing the necessary cooling load to keep buildings at comfortable temperature levels throughout the state. Power system cost is determined by using a wholesale energy cost model that was developed using NYISO market and load data for both the day-ahead and real-time wholesale markets. By flattening out the system load, increasing the electrical system’s load factor, and reducing system ramping, TES can reduce steady-state and ramping costs, thus reducing the overall power system’s operation costs.

Suggested Citation

  • Naranjo Palacio, Santiago & Valentine, Keenan F. & Wong, Myra & Zhang, K. Max, 2014. "Reducing power system costs with thermal energy storage," Applied Energy, Elsevier, vol. 129(C), pages 228-237.
    • Handle: RePEc:eee:appene:v:129:y:2014:i:c:p:228-237
    DOI: 10.1016/j.apenergy.2014.04.089
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    References listed on IDEAS

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    7. Alimohammadisagvand, Behrang & Jokisalo, Juha & Kilpeläinen, Simo & Ali, Mubbashir & Sirén, Kai, 2016. "Cost-optimal thermal energy storage system for a residential building with heat pump heating and demand response control," Applied Energy, Elsevier, vol. 174(C), pages 275-287.
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    10. Arteconi, Alessia & Ciarrocchi, Eleonora & Pan, Quanwen & Carducci, Francesco & Comodi, Gabriele & Polonara, Fabio & Wang, Ruzhu, 2017. "Thermal energy storage coupled with PV panels for demand side management of industrial building cooling loads," Applied Energy, Elsevier, vol. 185(P2), pages 1984-1993.
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