Fossil fuel cost saving maximization: optimal allocation and sizing of Renewable-Energy Distributed Generation units considering uncertainty via Clonal Differential Evolution

Abstract

Renewable-Energy Distributed Generation Units (REDGs) are attractive alternative power sources to solve economic, environmental and fuel depletion problems. Maximizing their benefits, however, requires a proper size and location planning considering various aspects of the planning problem. This paper proposes a problem formulation of REDG location and size planning that considers various constraints, relevant uncertainties and load variations aiming at maximizing benefits of the distribution company in a distribution network where the company installs and owns REDGs. The main benefit is cost reduction that is achieved by replacing the power from fossil fuel-consuming main grid generators with power from REDGs. The fossil fuel cost saving is evaluated as the expected value due to the REDG output uncertainty. The constraints include the voltage limits, the REDG injection limit, the payback period limit, the REDG installation limit and the geographical constraint. An improved Differential Evolution (DE) with enhanced exploration capability, Clonal Differential Evolution (CDE), is introduced and applied to REDG planning for a 33-bus test system. The obtained plan satisfies all the constraints and highlights the importance of uncertainty consideration. The comparative studies have proven that the CDE is capable of speeding up the convergence, three times faster than ordinary DE.