Energy Storage for Power System Planning and Operation

5Unit Commitment with Energy Storage System

5.1 Introduction

Because load changes with time, the generating units should be properly committed in order to serve the load with the least cost while satisfying specified constraints. The constraints include unit technical constraints, system security, or reliability constraints, and so forth, depending on the generation mix, load–curve characteristics, and so on [1]. For a large‐scale power system with hundreds of units, the unit commitment (UC) problem is a complex large scale optimization problem and very difficult to solve. This challenging problem has attracted many researchers for decades and many literatures have been published [2–4].

Traditionally, the most common methods are priority list, dynamic programming, and Lagrange relaxation. A lot of modern heuristic optimization methods have been used to solve the UC problem, including genetic algorithm, simulated annealing, and tabu search, because they are easy to implement and powerful in searching for a global optimum [3]. With the development of mixed‐integer linear programming (MILP) algorithm, off‐the‐shelf optimization software, and enhanced computation power, MILP‐based methods are now widely used [5]. With the third edition of Power Generation, Operation, and Control [1], MILP is added as one of the most talked‐about techniques for the solution of the UC problem. Another important factor that promotes the application of MILP is the development of power markets. In reference ...