Optimal allocation of active and reactive power of dispatchable distributed generators in a droop controlled islanded microgrid considering renewable generation and load demand uncertainties

Abstract

This paper proposes a novel sequential optimization strategy (SOS) for optimal allocation of both active and reactive power among dispatchable distributed generator (DDG) units present in a droop controlled islanded AC microgrid. Active power is optimally dispatched based on the simultaneous satisfaction of an economic objective of total operational cost (TOC) minimization, along with an environmental objective of total operational emission (TOE) minimization, as well as a network-related objective of total active power loss (Ploss) minimization. A fuzzy-embedded multi-objective particle swarm optimization (FMOPSO) technique is used to solve this optimization problem. Reactive power is optimally allocated depending on the objective of capacity based reactive power sharing, which is solved using the conventional particle swarm optimization (PSO) algorithm. Node voltage deviation index (NVDI) and total active power loss in the network (Ploss) are used as two main attributes to quantitatively measure the improvement in node voltage profile as a result of optimal sharing of reactive power among the dispatchable distributed generator units. The presence of local heat demand and uncertainties inherent in weather dependent load demand and renewable generation are taken into consideration. A novel mixed probabilistic–possibilistic scenario based approach (MPPSBA) is put forward to model the uncertainties associated with both the electrical and heat load demand and renewable distributed generator (RDG) output. The effectiveness of the proposed methods is demonstrated on a 33-node droop controlled islanded microgrid (DCIMG) test network.