DYNAMIC ECONOMIC DISPATCH FOR ELECTRICAL SYSTEMS WITH RENEWABLE ENERGY INTEGRATION USING ARTIFICIAL INTELLIGENCE

Electricity is crucial to energy markets and Sustainable Hybrid Electrical Systems (SHEE) integrate thermoelectric and renewable sources for sustainability. Dynamic economic dispatch (DED) optimizes power generation but presents financial, technical and computational-related challenges. This study develops a hybrid method for combining genetic algorithms (GA), sequential quadratic programming (SQP) and interior point method (IP) to solve DED for a 10-generator system. The approach used increases accuracy and convergence speed, producing competitive results. The integration of GA, SQP, and IP addresses the complexities of DED effectively, promoting sustainable power generation in hybrid systems.