Combined Economic and Emission Dispatch Problem of Wind‐Thermal Power System Using Gravitational Particle Swarm Optimization Algorithm

Abstract

In this paper, a novel hybrid optimization approach, namely, gravitational particle swarm optimization algorithm (GPSOA), is introduced based on particle swarm optimization (PSO) and gravitational search algorithm (GSA) to solve combined economic and emission dispatch (CEED) problem considering wind power availability for the wind-thermal power system. e proposed algorithm shows an interesting hybrid strategy and perfectly integrates the collective behaviors of PSO with the Newtonian gravitation laws of GSA. GPSOA updates particle's velocity caused by the dependent random cooperation of GSA gravitational acceleration and PSO velocity. To describe the stochastic characteristics of wind speed and output power, Weibull-based probability density function (PDF) is utilized. e CEED model employed consists of the fuel cost objective and emission-level target produced by conventional thermal generators and the operational cost generated by wind turbines. e effectiveness of the suggested GPSOA is tested on the conventional thermal generator system and the modified wind-thermal power system. Results of GPSOA-based CEED problems by means of the optimal fuel cost, emission value, and best compromise solution are compared with the original PSO, GSA, and other state-of-the-art optimization approaches to reveal that the introduced GPSOA exhibits competitive performance improvements in finding lower fuel cost and emission cost and best compromise solution.

Optimasi Kombinasi Biaya Bahan Bakar dan Emisi Pembangkit Energi Listrik menggunakan Teknik Reduksi Tempat Kedudukan

“…Hasilnya menunjukkan bahwa biaya dari metoda PSO lebih rendah dibanding LM, baik untuk EED tanpa mempertimbangkan Valve-Point Effect (VPE) maupun ketika mempertimbangkan VPE. Sementara itu metoda Gravitational Particle Swarm Optimization Algorithm (GPSOA) untuk memecahkan masalah EED pada sistem tenaga hibrid antara tenaga angin dan tenaga termal, dan memberikan hasil terbaik bila dibandingkan dengan metoda GA, PSO, GSA, dan PSOGSA, baik dari sisi biaya bahan bakar maupun emisi yang dikeluarkan (Jiang, Zhang, Wu, & Chen, 2019).…”

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