An improved self-adaptive membrane computing optimization algorithm and its applications in residue hydrogenating model parameter estimation

In order to solve the non-linear and high-dimensional optimization problems more effectively, an improved self-adaptive membrane computing(ISMC) optimization algorithm was proposed. The proposed ISMC algorithm applied improved self-adaptive crossover and mutation formulae that can provide appropriate crossover operator and mutation operator based on different functions of the objects and the number of iterations. The performance of ISMC was tested by the benchmark functions. The simulation results for residue hydrogenating kinetics model parameter estimation show that the proposed method is superior to the traditional intelligent algorithms in terms of convergence accuracy and stability in solving the complex parameter optimization problems.

考虑安全性与可靠性的微电网电能优化调度

考虑微电网的安全与经济、节能与环保、效率与可靠等诸多因素,同时为消除间歇性发电设备出力、负荷以及系统设备的不确定因素带给微电网的影响,实现微电网的负荷最优分配,在满足系统约束条件下,建立考虑不确定因素下含低估或高估费用的微电网经济调度模型。模型中设置了满足系统安全性与可靠性的电压安全裕度与失负荷率的安全约束指标,同时利用改进的膜计算算法求解该数学模型。实际算例分析了微电网经济性与不同置信水平下安全、可靠约束指标的关系,验证了所提模型的正确性和求解方法的有效性。