A multi-objective formulation for the optimal sizing and siting of embedded generation in distribution networks

The optimal power system planning is achieved when various objectives are simultaneously attained: in many cases, these objectives contradict each other and cannot be handled by conventional single optimisation techniques. The aim of this paper is to analyse sizing and siting problems, related to the presence of embedded generation (EG) in distribution networks, in order to achieve the best compromise between cost of network upgrading, cost of power losses, cost of energy not supplied, power quality cost (e.g. aging due to harmonic distortion), and the cost of energy required by the served customers. A multi-objective technique is used to minimise more than one objective simultaneously: the implemented genetic algorithm applies the ε-constrained technique to obtain a compromised non-inferior solution. Numerical examples are presented to demonstrate the properties of the proposed algorithm.