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access icon free Distribution system state estimation with stability assessment using bio-inspired computing

© The Institution of Engineering and Technology
Received 03/02/2020, Accepted 03/12/2020, Revised 23/11/2020, Published 08/01/2021

In the present day, there is an enormous demand in the supply of energy to all users. Since the voltage stability for the distribution system is not steady under any circumstances, therefore, to solve the problem of voltage instability the entire distribution system must simplified properly. Thus, some active support is provided for balancing the demand for electrical energy supply. Hence, the problem of voltage instability has been solved by considering phasor measuring units (PMUs) using antlion optimisation proposed in this study. The cost of PMU has been analysed along with other factors such as observability for effectively placing the PMUs with the identification of the weakest node. The problem is solved by using a non-linear model and the effectiveness of the proposed approach is tested using IEEE-15, IEEE-33, IEEE-69 Radial Distribution Systems and Croatia distribution grid. The result shows that the suggested algorithm is more effective in getting the optimal PMU placements considering multi-objective. Hence, the maiden state estimation values for distribution topologies are used.

Inspec keywords: phasor measurement; power grids; power distribution control; optimisation; power system state estimation; power system stability; power engineering computing

Other keywords: voltage stability; IEEE-33 radial distribution systems; stability assessment; active support; voltage instability; electrical energy supply; maiden state estimation values; distribution topologies; phasor measuring units; antlion optimisation; IEEE-69 radial distribution systems; distribution system state estimation; IEEE-15 radial distribution systems; PMU; bio-inspired computing

Subjects: Distribution networks; Optimisation techniques; Control of electric power systems; Power system control; Power system measurement and metering; Optimisation techniques; Power engineering computing

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