Day-ahead combined economic and emission dispatch with spinning reserve consideration using moth swarm algorithm for...

Area of Science:

• Power Systems Engineering
• Optimization Algorithms
• Renewable Energy Integration

Background:

• Economic and emission dispatch are crucial for minimizing power generation costs and environmental impact.
• Integrating renewable energy sources like solar photovoltaic (PV) presents challenges due to intermittency.
• Optimal resource allocation requires balancing economic, environmental, and reliability factors.

Purpose of the Study:

• To propose and evaluate the Moth Swarm Algorithm (MSA) for solving the dynamic combined economic and emission dispatch problem.
• To assess the performance of MSA against other optimization algorithms in a hybrid power system.
• To investigate the optimal scheduling of solar PV and thermal generation, including spinning reserve allocation.

Main Methods:

• Implementation of the Moth Swarm Algorithm (MSA) for a 24-hour economic and emission dispatch.
• Modeling a hybrid power system comprising thermal and solar PV plants.
• Comparative analysis with Moth Flame Optimization, Whale Optimization Algorithm, Ant Lion Optimizer, and Tunicate Swarm Algorithm.
• Consideration of spinning reserve allocation to manage solar intermittency.

Main Results:

• The proposed MSA favored solar PV generation over thermal generation to minimize environmental impact.
• MSA effectively scheduled thermal generators to provide spinning reserves, ensuring system reliability.
• The algorithm demonstrated superior performance in optimizing fuel costs, emission costs, solar generation, and spinning reserve costs.

Conclusions:

• The Moth Swarm Algorithm is a highly effective tool for solving the dynamic combined economic and emission dispatch problem in hybrid power systems.
• MSA offers a robust solution for integrating renewable energy sources while ensuring grid stability and minimizing operational costs.
• The study highlights the potential of MSA for optimizing power system operations with significant solar PV penetration.