Nodal Electricity Price Based Optimal Size and Location of DGs in Electrical Distribution Networks Using ANT LION Optimization Algorithm

Abstract

Distribution system has been the weakest link in the entire power system supply chain. It is also one of the most vital parts of the power system. However, a lot of methods have been developed to improve the condition of the distribution system. The use of distributed generations (DGs) is one such method where the generated power is closer to the load center, and the DG is also providing ancillary services to the grid. The nodal electricity price for DGs location is determined based on the Locational Marginal Price (LMP). LMP implies the price to buy and sell power at each node within electrical distribution markets. In the nodal electricity market (EM), the cost of energy is determined by the location of DG to which it is provided. This paper presents a novel approach that utilizes nodal electricity price for optimal sizing and location (OSL) of DGs. A multi-objective ANTLION optimization (MOALO) has been utilized as an optimization approach to compute the OSL of DGs units. ANTLION optimization (ALO) is based on the unique hunting behaviour of antlions. Optimization has been done for social welfare maximization, loss minimization, and voltage profile improvement in distribution networks (DNs). The results of the proposed technique have been evaluated for IEEE 33 bus DNs.

Optimal placement and sizing of custom power devices using APSO and JAYA optimization in radial distribution network

“…D. Buła et al [11] presented that comprehensive review on OSS of active power filter to minimize the losses. M. I. Ahmed et al [12] represented that OSS of distributed generation (DG) to minimize the cost using ANTLION optimization. A similar study has been carried out in [13] using analytical hybrid particle swarm optimization(AHPSO) for optimal sizing and sitting of DG in smart grid.…”