Optimization-based economic analysis of energy storage technologies in a coupled electricity and natural gas market

Abstract

This work presents a stochastic mixed-integer linear programming (MILP) optimization framework to investigate the optimal participation and economics of various energy storage technologies, such as pumped-hydro, advanced adiabatic and diabatic compressed air systems and li-ion battery, in a perfectly competitive coupled electricity and natural gas market. The clearing scheme pertains to energy-only markets, aiming to optimize dispatch and maximize social welfare for the integrated energy system, through a two-stage stochastic programming. The first stage presents the day-ahead market clearing procedure, while the second stage illustrates the integrated system operation in the real-time trading floor, through a set of plausible wind power generation realizations. The two markets mainly interact the bilateral operation of the diabatic compressed air energy storage system, both as an electricity producer and as natural gas consumer. The proposed algorithm is applied to a modified IEEE 24-bus power grid and a single-node gas network and provides a thorough analysis of the operational characteristics and profitability of each energy storage technology in the integrated energy system. Results illustrate that electricity storage systems can increase their overall profits under power transmission congestion and while wind power generation volatility increases from 5 % up to 52 %. In contrast, a decrease by 3.1 % in the social welfare is realized in the case of power congestion while this figure is approximately 2.54 % under wind power volatility increase.