Solving a real-life large-scale energy management problem

TL;DR

This paper presents a three-phase heuristic for large-scale energy management and maintenance scheduling of nuclear power plants, effectively handling multiple scenarios and minimizing costs, with competitive results in a major international challenge.

Contribution

The paper introduces a novel three-phase heuristic approach specifically designed for complex, real-world energy management problems involving multiple scenarios and long-term planning.

Findings

Successfully solved all ten real-life instances

Solutions within 2.45% of best known solutions

Ranked highly in the ROADEF/EURO Challenge 2010

Abstract

This paper introduces a three-phase heuristic approach for a large-scale energy management and maintenance scheduling problem. The problem is concerned with scheduling maintenance and refueling for nuclear power plants up to five years into the future, while handling a number of scenarios for future demand and prices. The goal is to minimize the expected total production costs. The first phase of the heuristic solves a simplified constraint programming model of the problem, the second performs a local search, and the third handles overproduction in a greedy fashion. This work was initiated in the context of the ROADEF/EURO Challenge 2010, a competition organized jointly by the French Operational Research and Decision Support Society, the European Operational Research Society, and the European utility company Electricite de France. In the concluding phase of the competition our team ranked second in the junior category and sixth overall. After correcting an implementation bug in the program that was submitted for evaluation, our heuristic solves all ten real-life instances, and the solutions obtained are all within 2.45% of the currently best known solutions. The results given here would have ranked first in the original competition.