Application of Markov Models for decision making under uncertainty in the electric utility industry

Abstract

Planning in the Power Systems distribution involves a formal decision-making process of identifying and prioritizing network improvement projects such as the construction of substations, interconnecting feeder links and general upgrade works, with the aim is of providing an efficient service to the customer without damage to the utility's equipment and customer's property or personnel. This task is plagued with uncertainties associated with load growth and demand due to changing weather conditions and other unforeseen developments, which affects the ability to maximize efficiency and utilization. This paper proposes the use of Markov Models as a more effective technique by utility planners and managers for their decision-making efforts under such uncertainties. The authors develop a load flow modeling approach that takes into consideration the stochastic nature of customer demand and uses the distribution network profiles as fitness values to be optimized. A ranking of the criteria of interest based on the decision makers preferences is the result of the optimization algorithm. This provides a formal process for decision making by the management of utility companies.