With the widespread application of distributed systems, many problems need to be solved urgently. How to design distributed optimization strategies has become a research hotspot. This article focuses on the solution r...With the widespread application of distributed systems, many problems need to be solved urgently. How to design distributed optimization strategies has become a research hotspot. This article focuses on the solution rate of the distributed convex optimization algorithm. Each agent in the network has its own convex cost function. We consider a gradient-based distributed method and use a push-pull gradient algorithm to minimize the total cost function. Inspired by the current multi-agent consensus cooperation protocol for distributed convex optimization algorithm, a distributed convex optimization algorithm with finite time convergence is proposed and studied. In the end, based on a fixed undirected distributed network topology, a fast convergent distributed cooperative learning method based on a linear parameterized neural network is proposed, which is different from the existing distributed convex optimization algorithms that can achieve exponential convergence. The algorithm can achieve finite-time convergence. The convergence of the algorithm can be guaranteed by the Lyapunov method. The corresponding simulation examples also show the effectiveness of the algorithm intuitively. Compared with other algorithms, this algorithm is competitive.展开更多
碳达峰碳中和的背景下、主动配电网(active distribution network,ADN)下多主体间能源共享有助于消纳弃风弃光。但随着各微网内风机光伏容量日益增加,每日微网净负荷峰谷趋势变化明显。传统分时电价逐渐很难发挥对微网的削峰填谷作用。...碳达峰碳中和的背景下、主动配电网(active distribution network,ADN)下多主体间能源共享有助于消纳弃风弃光。但随着各微网内风机光伏容量日益增加,每日微网净负荷峰谷趋势变化明显。传统分时电价逐渐很难发挥对微网的削峰填谷作用。提出考虑主动配电网下多主体能源共享调度策略,以主动配电网向下级微网的售电收益减去向主网购电成本所得净收益最大为目标函数,充分考虑下级多微网在电网议价下以微网自身运行成本最低为目标的调度自主性,运用卡罗需-库恩-塔克(Karush-Kuhn-Tucker,KKT)条件将下级多主体电能共享联盟运行成本最低的目标转化为上级目标的约束条件。引入KKT乘子,同时运用大M法对非线性约束进行线性化处理,提高模型求解速度。在MATLAB的Gurobi环境下,对连续的上下层耦合变量乘积进行离散化处理。最后,在IEEE33节点的主动配电网算例中验证所提模型的有效性。展开更多
为了提高分布式能源系统(Distributed Energy System,DES)运行的经济性,以DES运行成本最小为目标函数,建立了基于改进灰狼优化(Improved Grey Wolf Optimization,IGWO)算法的分布式能源系统优化调度模型。采用Tent混沌映射和非线性调整...为了提高分布式能源系统(Distributed Energy System,DES)运行的经济性,以DES运行成本最小为目标函数,建立了基于改进灰狼优化(Improved Grey Wolf Optimization,IGWO)算法的分布式能源系统优化调度模型。采用Tent混沌映射和非线性调整收敛因子策略对灰狼优化算法(Grey Wolf Optimization,GWO)进行改进,提高了算法的性能。利用某综合大楼分布式能源系统进行算例分析,并与其他优化算法的求解结果进行对比,结果表明,IGWO算法收敛时的迭代次数更少,收敛时间更短,与其他三种算法相比,运行成本最低,各项指标均优于其他优化算法,在此调度方案下,各分布式电源出力合理,验证了本文DES优化调度模型的正确性和求解方法的有效性。展开更多
文摘With the widespread application of distributed systems, many problems need to be solved urgently. How to design distributed optimization strategies has become a research hotspot. This article focuses on the solution rate of the distributed convex optimization algorithm. Each agent in the network has its own convex cost function. We consider a gradient-based distributed method and use a push-pull gradient algorithm to minimize the total cost function. Inspired by the current multi-agent consensus cooperation protocol for distributed convex optimization algorithm, a distributed convex optimization algorithm with finite time convergence is proposed and studied. In the end, based on a fixed undirected distributed network topology, a fast convergent distributed cooperative learning method based on a linear parameterized neural network is proposed, which is different from the existing distributed convex optimization algorithms that can achieve exponential convergence. The algorithm can achieve finite-time convergence. The convergence of the algorithm can be guaranteed by the Lyapunov method. The corresponding simulation examples also show the effectiveness of the algorithm intuitively. Compared with other algorithms, this algorithm is competitive.
文摘碳达峰碳中和的背景下、主动配电网(active distribution network,ADN)下多主体间能源共享有助于消纳弃风弃光。但随着各微网内风机光伏容量日益增加,每日微网净负荷峰谷趋势变化明显。传统分时电价逐渐很难发挥对微网的削峰填谷作用。提出考虑主动配电网下多主体能源共享调度策略,以主动配电网向下级微网的售电收益减去向主网购电成本所得净收益最大为目标函数,充分考虑下级多微网在电网议价下以微网自身运行成本最低为目标的调度自主性,运用卡罗需-库恩-塔克(Karush-Kuhn-Tucker,KKT)条件将下级多主体电能共享联盟运行成本最低的目标转化为上级目标的约束条件。引入KKT乘子,同时运用大M法对非线性约束进行线性化处理,提高模型求解速度。在MATLAB的Gurobi环境下,对连续的上下层耦合变量乘积进行离散化处理。最后,在IEEE33节点的主动配电网算例中验证所提模型的有效性。
文摘为了提高分布式能源系统(Distributed Energy System,DES)运行的经济性,以DES运行成本最小为目标函数,建立了基于改进灰狼优化(Improved Grey Wolf Optimization,IGWO)算法的分布式能源系统优化调度模型。采用Tent混沌映射和非线性调整收敛因子策略对灰狼优化算法(Grey Wolf Optimization,GWO)进行改进,提高了算法的性能。利用某综合大楼分布式能源系统进行算例分析,并与其他优化算法的求解结果进行对比,结果表明,IGWO算法收敛时的迭代次数更少,收敛时间更短,与其他三种算法相比,运行成本最低,各项指标均优于其他优化算法,在此调度方案下,各分布式电源出力合理,验证了本文DES优化调度模型的正确性和求解方法的有效性。
