Linear Formulation for Short-Term Operational Scheduling of Energy Storage Systems in Power Grids

Yong-Gi Park, Jong-Bae Park, Namsu Kim and Kwang Y. Lee
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Yong-Gi Park: Research Center for Innovative Electricity Market Technology, Konkuk University, 120 Neungdong-ro, Gwangjin-gu, Seoul 05029, Korea
Jong-Bae Park: Department of Electrical Engineering, Konkuk University, 120 Neungdong-ro, Gwangjin-gu, Seoul 05029, Korea
Namsu Kim: Department of Mechanical Design and Production Engineering, Konkuk University, 120 Neungdong-ro, Gwangjin-gu, Seoul 05029, Korea
Kwang Y. Lee: Department of Electrical and Computer Engineering, Baylor University, Waco, TX 76798, USA

Energies, 2017, vol. 10, issue 2, 1-16

Abstract: This paper presents linear programming (LP) formulations for short-term energy time-shift operational scheduling with energy storage systems (ESSs) in power grids. In particular, it is shown that the conventional nonlinear formulations for electric bill minimization, peak shaving, and load leveling can be formulated in the LP framework. New variables for the peak and off-peak values are introduced in peak shaving and load leveling model, and the historical peak value for demand charge are considered in the electric bill minimization model. The LP formulations simplify computation while maintaining the accuracy for including linear technical constraints of ESSs, such as the state-of-charge, charging/discharging efficiency, output power range, and energy limit considering the life cycle of ESS. Proposed LP formulations have been implemented and verified in practical power systems and a large-scale industrial customer using historical data.

Keywords: electric bill minimization; energy arbitrage; energy storage systems (ESSs); linear programming (LP); load-leveling; peak-shaving; short-term optimal operational scheduling (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2017
References: View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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