| In recent years,energy and environmental issues have become increasingly prominent,and the single energy mix of the power system is not able to support the increasing demand for electricity.Economic dispatch(ED)refers to the dispatch of units to meet certain constraints in the operation of the grid.In the process of economic dispatch,conditions must be met such as safe operation of the grid system,power quality meeting national standards,and reserve capacity meeting certain requirements.In order to reduce energy consumption and carbon emissions,environmental issues are receiving more and more attention in the daily optimization of power systems.Environmental economic dispatch(EED)is a problem that takes into account both fuel costs and emissions in the power generation process,and finds the optimal balance between the two under various constraints,in order to achieve a reduction in fuel costs and emissions at the same time for a given power demand.For the classical economic dispatch problem,an Adaptive Evolutionary Strategy based on Dynamic Space Constraint and Adaptive Tradeoff Model(DSC-ATM-AES)is proposed to solve the economic scheduling problem.The space constraint technique is used to reduce the search space,and the search space is compressed by this technique to accelerate the convergence rate of the algorithm.The ATM is used to deal with constraints.When facing the semi-feasible region,it is not necessary to check the current feasible and infeasible solutions,but only to calculate the fitness according to the corresponding calculation rules.The ES algorithm is adopted to reduce the risk of inheriting poor information from the parental population to the offspring through differential variance.Compared with other algorithms,the improved DSC-ATM-AES algorithm shows better convergence and stability for both standard and nonlinear ED problems.For the environmental economic scheduling problem,A Multi-Verse Optimization algorithm based on Gridded Knee Points and Plane Measurement(GKPPM-MVO)is proposed to solve the environmental economic dispatch problems.The multi-verse optimization algorithm is used as the search algorithm.At the same time,the WEP operator is modified and the threshold parameter is removed to improve the transmission efficiency between the three holes.The updated WEP operator strengthens the mining ability of the algorithm for the candidate solution of the boundary.In order to improve the search quality,the gridding knee point and plane measurement technology are added in the search process.Gridding is used for optimization and retain the information of candidate schemes within each grid.The knee point and the maximum crowded distance point are considered as effective and potential solutions due to their special properties.Combining them as a new local search strategy not only preserves the solution with more information,but also avoids the precocious phenomenon caused by only relying on the global optimal solutions.The above two algorithms are analyzed and compared with other classical algorithms respectively,and the convergence,stability and optimization effects of the two improved algorithms are compared to arrive at a minimum value for balancing fuel cost and emissions,which provides a better solution to the environmental economic dispatch problem and indirectly achieves the purpose of reducing carbon emissions. |
