On the Value of Energy Storage in Generation Cost Reduction

TL;DR

This paper quantifies how energy storage can reduce power system generation costs by optimizing storage scheduling and capacity, demonstrating at least a 2.5% cost reduction using real demand data.

Contribution

It introduces a two-stage optimization framework for determining optimal energy storage scheduling and capacity, providing lower bounds on cost savings.

Findings

Energy storage can reduce generation costs by at least 2.5%.

The framework provides a lower bound on cost savings.

Numerical validation with real-world demand data supports the approach.

Abstract

This work seeks to quantify the benefits of using energy storage toward the reduction of the energy generation cost of a power system. A two-fold optimization framework is provided where the first optimization problem seeks to find the optimal storage schedule that minimizes operational costs. Since the operational cost depends on the storage capacity, a second optimization problem is then formulated with the aim of finding the optimal storage capacity to be deployed. Although, in general, these problems are difficult to solve, we provide a lower bound on the cost savings for a parametrized family of demand profiles. The optimization framework is numerically illustrated using real-world demand data from ISO New England. Numerical results show that energy storage can reduce energy generation costs by at least 2.5 %.