New hybrid multiverse optimisation approach for optimal accommodation of DGs in power distribution networks

Abstract

This work presents a new hybrid multiverse optimisation (HMVO) methodology to solve the optimal accommodation of distributed generations (OADGs) problem in power distribution networks. The HMVO method is formulated by incorporating the space transformation search (STS) technique, and piecewise linear chaotic map-based optimisation method. STS avoids the prior convergence and increases the possibility to find the solutions near the optimal global point. In contrast, the chaotic optimiser is extremely good at ergodicity and stochasticity, used around the transition of the exploration–exploitation phase. The objective functions to be optimised are as follows: minimisation of electrical energy losses, minimisation of overall node voltage deviation, maximisation of overall voltage stability margin, and minimisation of energy not served. Analytical hierarchy process method is employed to optimise the objective function weights, as the optimisation problem is solved by weighted sum method. The proposed methodology is demonstrated on radial power distribution networks of IEEE 33-bus and INDIAN 85-bus. The effectiveness of the proposed HMVO method is validated by comparing the results with studied algorithms and algorithms presented in the literature and found to be promising. Further, the OADG problem under uncertain environment is also investigated for long-term planning using self-adaptive polyhedral deterministic set.