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.
The New York Power Authority (NYPA) wanted to develop a 10-year schedule for refueling its Indian Point 3 Nuclear Power Plant (IP3) that balanced fish protection, which occurs when IP3 is shut down for refueling, and the costs of buying and loading fuel. We developed a decision analysis model to compare alternative strategies for refueling. It explicitly considered key uncertainties associated with future operation: how well IP3 operates, how long it takes to refuel, and when New York State is likely to deregulate the electric utility industry. The NYPA decision makers used the model to reinforce their choice of a refueling strategy. They were not surprised that more fish protection occurred with strategies that restricted the starting date for refueling to the third week in May, rather than allowing the starting date to float throughout the period from May through August. However, the decision makers were surprised that the more restrictive strategies also resulted in lower costs.