Renewable energy investment under power market conditions by employing novel scenario generation and reduction

A new investment planning in distributed generation (DG) units from the perspective of distribution company is presented in this paper. Stochastic programming is employed for modeling uncertainties associated with wind, solar and market price. The stochastic programming leads to huge numbers of scenarios which conventional scenario generation and reduction cannot handle the scenario reduction. Therefore, novel scenario generation and reduction is proposed and adaptive shuffled frog leaping algorithm is employed to solve the scenario reduction. The problem of investment planning is formulated as a mixed integer non-linear programming (MINLP) with the objective of maximizing DISCO's benefit by optimal sizing and placement of DGs. Improved shuffled frog leaping algorithm is applied to solve the optimal sizing and placement problem. The proposed approach has been applied to a nodes distribution system. The results show that a significant increase in DISCO's annual benefit is obtained.