Multi-objective planning of Distributed Energy Resources with probabilistic constraints

Abstract

Distributed Energy Resources (DER) are recognized as one of the possible solutions for sustainable economic development. The optimal integration of DER is a multi-objective problem in which different technical and economical objectives must be achieved simultaneously, and where a compromise solution for different perspectives needs to be found. The stochastic nature of DER and demand increases the complexity of the problem. Advanced multi-objective planning methods with appropriate probabilistic models of DER are required. This paper presents a multi-objective analysis of the optimal integration of wind turbines. The analysis is based on the Strength Pareto Evolutionary Algorithm 2 (SPEA2) and considers technical and economical planning objectives. The unpredictable nature of DER production and demand is evaluated by means of stochastic simulation. Practical aspects of the framework's implementation are discussed, including the formulation of probabilistic constraints. Results demonstrate that the multi-objective approach proposed produces valuable information for different stakeholders involved in DER planning and development.