Moth Search Optimization for Optimal DERs Integration in Conjunction to OLTC Tap Operations in Distribution Systems

Abstract

In this paper, a newly developed moth search optimization (MSO) technique is introduced to solve the complex distributed energy resources (DER) integration problems of distribution systems. In order to overcome some of the limitations observed in the standard variant of MSO, minor corrections are also suggested. On the other hand, a new optimization problem is formulated for optimal deployment of dispatchable distributed generations and shunt capacitors while simultaneously optimizing the tap positions of on-load tap-changing transformers, already deployed in grid substations. The objective of this work is to minimize the cost of annual energy loss and node voltage deviations over multiple load levels. The proposed model is implemented and solved for two benchmark test distribution networks of 33 and 118 buses. The suggested corrections are also validated by comparing the performance of the proposed approach with standard MSO and other available optimization methods. The simulation results show that the developed model optimally utilizes the existing distribution system resources and generates higher deployment benefits at lesser DER penetration as compared to the planning model which ignores these resources.

A Review of Metaheuristic Techniques for Optimal Integration of Electrical Units in Distribution Networks

“…The Flower Pollination Algorithm (FPA), which uses a Levy flight based on a heavy-tailed probability distribution to attain global optimal solution was implemented by [38] to reduce the total cost of installed capacitors while solving the optimal capacitor sizes in a distribution network. The Moth Search Algorithm (MSA), similarly uses the Levy flight approach and was proposed by [102] for regulating bus voltage while placing and sizing DG units in a distribution network.…”

Modified African Buffalo Optimization for Strategic Integration of Battery Energy Storage in Distribution Networks

“…On the other hand, the AI-based techniques can solve such complex engineering optimization problems efficiently but require high computations. Some of the popularly known AI-techniques adopted for DER integration can include genetic algorithm (GA) [4], [6], [9], [12], particle swarm optimization (PSO) [4], teaching-learning-base optimization (TLBO) [11], [20], moth search optimization (MSO) [21], etc. However, some problem specific limitations have been observed in many standard optimization techniques.…”

Modified Taguchi-Based Approach for Optimal Distributed Generation Mix in Distribution Networks

“…In [4]- [6], the ODGA problem is formulated to minimize the power loss in PDNs. In [7], [8], multiobjective ODGA problems are solved by considering power loss, node voltage deviation and voltage stability of distribution systems. A riskbased multiobjective ODGA model is also solved in [9].…”

“…A riskbased multiobjective ODGA model is also solved in [9]. The coordinated and simultaneous ODGA problems have been formulated and solved in [7], [10] by considering the effect of existing voltage regulators, i.e., on-load tap changer, already present in distribution systems. In [11], the optimal sites and sizes of DGs are determined to improve the reliability indices of large-scale PDNs.…”