Pareto Front-Based Multiobjective Optimization of Distributed Generation Considering the Effect of Voltage-Dependent Nonlinear Load Models

Single objective constant PQ load models were extensively considered for site and size of distributed generation (DG) shunt capacitor (SC) allocation. Which may lead to single non-dominated solution unpredictable misleading results about their size, loss reduction payback period. Therefore, primary this study is investigate the effects seven nonlinear voltage-dependent siting sizing DG SC considering various conflicting Multiobjective functions. These functions are minimization active power loss, voltage deviation, cost energy per year, total installed SC, emission. Three cases simultaneous optimization two three intended find optimal integration in standard 33 118-bus radial distribution network models. A new evolutionary algorithm (MOEA) called Bidirectional Coevolutionary (BiCo) applied proposed demonstrate impact model on Further, show superiority performance algorithm, six state-of-the-art MOEAs implemented statistically compared with using a representative hypervolume indicator (HVI). The maximum savings annual reaches 58.99% case1 model, 59.4% case 2 64.96% 3 industrial only allocation, whereas, 93.673% case1, 78.908% current case2 93.403% case3 SC. Simulation that adept suitable better trade-off between other recently designed MOEAs.