Optimal Power Flow of Multi-objective Combined Heat and Power with Wind-Solar-Electric Vehicle-Tidal Using Hybrid Evolutionary Approach

Determining effective power generation while reducing emissions, voltage deviations, and preserving transmission line voltage stability is the goal of the proposed effort. In this presentation, the combined heat and power of economic dispatch (CHPED) system is implemented in the IEEE-30 bus to assure the best possible power flow in the transmission line while fulfilling the load demand. As the source of fossil fuel is improvising day by day it is an important aspect to combine renewable energy sources for effective power generation. Renewable energy sources including wind, solar, electric vehicles, and tidal are integrated with proposed systems to lessen the need for fossil fuels in the production of electricity. The system became more complex as a result of the presence of wind uncertainty, valve point impact, and transmission losses. To enhance system performance in dealing with non-linearity, the multi-trial vector-based monkey king evolution technique uses training-based optimization to guide control choices. To improve the search capability of the proposed technique, the suggested method mixes chaotic-op-positional-based learning (COL) with MMKE (COMMKE). The suggested COMMKE algorithm has been tested for three distinct test systems for a proposed system with and without renewable sources. In terms of convergence rate and best possible solution to the objective functions, the proposed algorithm outperforms other optimization techniques. The robustness of the recommended optimization technique has been evaluated by statistical analysis. To make this scrutiny in a rigorous manner such that the robustness of the proposed technique can be judged more reliably, an analysis of variance (ANOVA) test is employed. To address the superiority of the intended method, a comparison with tried-and-true optimization strategies has been made.