Optimal Scheduling of Merchant-Owned Energy Storage Systems With Multiple Ancillary Services

C Opathella,Ayman Elkasrawy,Amr A Mohamed,B Venkatesh

doi:10.1109/oajpe.2019.2952811

C Opathella, Ayman Elkasrawy + Show 2 more

Open Access

https://doi.org/10.1109/oajpe.2019.2952811

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Abstract

Electrical energy storage (EES) can improve the flexibility and reliability of electric power systems. At the same time, they can supply different ancillary services. The profit of the energy storage operation can be maximized by deciding the best level of each service. Merchant-owned facilities require a profit-maximizing formulation for grid-connected energy storage systems with multiple ancillary services. This paper proposes a new linear profit-maximizing formulation for grid-connected merchant-owned energy storage systems operating with multiple ancillary services. All technical characteristics of EES have been modelled, including cycle life loss due to fast charge/discharge and low depth of discharge operations. A piece-wise linear model of an EES converter’s capability curve has also been included for reactive power modeling. The model was assessed considering a battery EES, a flywheel EES, and a compressed air EES, with the results demonstrating the benefits of the formulation. From case studies, it is clear that the merchant-owned battery EES and the flywheel EES can generate profits, especially from voltage regulation and frequency regulation services. The case studies prove that the proposed model can be used as an optimal planning and operation tool for any type or size of EES.

Highlights

VARIABLESRevenue from reserve power ($) Revenue from voltage regulation ancillary service contract ($) energy storage (EES) energy level at each hour (MWh) Required EES energy to maintain the black start service (MWh) Required EES energy to conduct the frequency regulation (MWh) Required EES energy to have reserve power service (MWh) Energy level which affects the lifetime degradation of the EES
E LECTRICAL energy storage (EES) is one of the most promising modern power systems research areas
The model is expected to help the EES owners in decision making regarding optimal capacities for their EES units. It could help regarding their operational decisions and the best way to invest in EES and gain maximum profits

Summary

VARIABLES

Revenue from reserve power ($) Revenue from voltage regulation ancillary service contract ($) EES energy level at each hour (MWh) Required EES energy to maintain the black start service (MWh) Required EES energy to conduct the frequency regulation (MWh) Required EES energy to have reserve power service (MWh) Energy level which affects the lifetime degradation of the EES. This is the energy level at the depth of discharge (DOD) (MWh)

INTRODUCTION

MAXIMIZING OVERALL PROFIT OF EES OPERATION

MAIN CONTRIBUTIONS

Findings

CONCLUSION