基于非合作博弈的布谷鸟搜索算法在微电网多目标优化中的应用

在微电网多目标优化过程中，不同目标之间往往相互影响，相互制约。随着可再生能源的高比例接入，必然会对电网造成冲击，降低其稳定运行水平；同时联络线功率波动也会影响清洁能源的并网比重，从而无法保证可再生能源的充分利用。作为同时需要优化的主体，两者具有一定的效益冲突。为实现两者利益的最大化，采用一种基于二人零和博弈模型的线性加权法，得出Nash稳定策略下的最佳权重系数，并将该系数应用于风-光-储协调的混合发电系统多目标优化模型中，将多目标问题转化为单目标问题，再应用布谷鸟搜索算法（CS）对该模型进行求解。结果表明，较之传统多目标算法，该方法可以使微电网整体获得更大收益，既提高了可再生能源渗透率，又有效抑制了联络线随机功率波动。

Application of Cuckoo Search Algorithm Based on Non-cooperative Game in Multi-objective Optimization of Microgrid

In the process of multi-objective optimization of microgrids,different targets often interact with and restrict each other.With the high proportion of renewable energy coming into the power grid,it will inevitably impact the power grid and reduce its stable operation level.The fluctuation of tie line power will also affect the proportion of clean energy grid connected,and thus can not guarantee the full use of renewable energy.As the main body that needs optimization at the same time,both have certain benefit conflicts.In order to maximize the two benefits,a linear weighting method based on the two person zero sum game model is adopted to get the best weight coefficient under the Nash stability strategy.This coefficient is applied to the multi-objective optimization model of hybrid power system (HPS),and the multi-objective problem is transformed into a single objective problem,and the Cuckoo Search algorithm (CS) is used to solve the model.The results show that compared with the traditional multi-objective algorithm,this method can make the micronet more profitable,which not only improves the permeability of renewable energy,but also effectively inhibits the random power fluctuation of the contact line.