针对综合能源微网源荷不确定性给决策调度带来高风险性的问题,在考虑柔性负荷需求响应对平抑负荷波动性及提高系统能源利用效率作用的基础上,构建了计及主/被动需求响应与条件风险价值的微网2阶段经济调度模型。首先研究了用户主被动需...针对综合能源微网源荷不确定性给决策调度带来高风险性的问题,在考虑柔性负荷需求响应对平抑负荷波动性及提高系统能源利用效率作用的基础上,构建了计及主/被动需求响应与条件风险价值的微网2阶段经济调度模型。首先研究了用户主被动需求响应对负荷曲线的影响。在此基础上,为评估系统源荷不确定性带来的潜在调度风险,引入条件风险价值理论(conditional value at risk,CVaR),以微网系统的潜在风险成本以及考虑环保因素的综合运行成本最低为优化目标,建立了计及CVaR的微网经济调度模型。最后,为克服传统NSGAII算法易陷入局部最优解和求解效率低的不足,引入beta交叉算子和自适应交叉变异概率对原始NSGAII算法进行改进。以某地区微网系统作为仿真算例,并设置了5种对比场景,研究结果表明,主被动需求响应能在有效系统的运行经济性的同时,降低系统的潜在调度风险。CVaR理论能通过置信度的设置反映决策者对风险的厌恶态度,为系统调度决策提供参考。展开更多
Dynamic resource allocation(DRA) is a key technology to improve system performances in GEO multi-beam satellite systems. And, since the cache resource on the satellite is very valuable and limited, DRA problem under r...Dynamic resource allocation(DRA) is a key technology to improve system performances in GEO multi-beam satellite systems. And, since the cache resource on the satellite is very valuable and limited, DRA problem under restricted cache resources is also an important issue to be studied. This paper mainly investigates the DRA problem of carrier resources under certain cache constraints. What's more, with the aim to satisfy all users' traffic demands as more as possible, and to maximize the utilization of the bandwidth, we formulate a multi-objective optimization problem(MOP) where the satisfaction index and the spectrum efficiency are jointly optimized. A modified strategy SA-NSGAII which combines simulated annealing(SA) and non-dominated sorted genetic algorithm-II(NSGAII) is proposed to approximate the Pareto solution to this MOP problem. Simulation results show the effectiveness of the proposed algorithm in terms of satisfaction index, spectrum efficiency, occupied cache, and etc.展开更多
文摘针对综合能源微网源荷不确定性给决策调度带来高风险性的问题,在考虑柔性负荷需求响应对平抑负荷波动性及提高系统能源利用效率作用的基础上,构建了计及主/被动需求响应与条件风险价值的微网2阶段经济调度模型。首先研究了用户主被动需求响应对负荷曲线的影响。在此基础上,为评估系统源荷不确定性带来的潜在调度风险,引入条件风险价值理论(conditional value at risk,CVaR),以微网系统的潜在风险成本以及考虑环保因素的综合运行成本最低为优化目标,建立了计及CVaR的微网经济调度模型。最后,为克服传统NSGAII算法易陷入局部最优解和求解效率低的不足,引入beta交叉算子和自适应交叉变异概率对原始NSGAII算法进行改进。以某地区微网系统作为仿真算例,并设置了5种对比场景,研究结果表明,主被动需求响应能在有效系统的运行经济性的同时,降低系统的潜在调度风险。CVaR理论能通过置信度的设置反映决策者对风险的厌恶态度,为系统调度决策提供参考。
基金supported by the National Science and Technology Major Project under Grant 2018ZX03001016
文摘Dynamic resource allocation(DRA) is a key technology to improve system performances in GEO multi-beam satellite systems. And, since the cache resource on the satellite is very valuable and limited, DRA problem under restricted cache resources is also an important issue to be studied. This paper mainly investigates the DRA problem of carrier resources under certain cache constraints. What's more, with the aim to satisfy all users' traffic demands as more as possible, and to maximize the utilization of the bandwidth, we formulate a multi-objective optimization problem(MOP) where the satisfaction index and the spectrum efficiency are jointly optimized. A modified strategy SA-NSGAII which combines simulated annealing(SA) and non-dominated sorted genetic algorithm-II(NSGAII) is proposed to approximate the Pareto solution to this MOP problem. Simulation results show the effectiveness of the proposed algorithm in terms of satisfaction index, spectrum efficiency, occupied cache, and etc.
