面向越来越开放的能源交易市场,为充分调动用户侧资源,提出了一种考虑需求响应(demand response,DR)的电/热/气云储能(cloud energy storage,CES)优化配置策略。建立含电/热/气云储能能源集线器(energy hub,EH)结构,从参与云储能商业模...面向越来越开放的能源交易市场,为充分调动用户侧资源,提出了一种考虑需求响应(demand response,DR)的电/热/气云储能(cloud energy storage,CES)优化配置策略。建立含电/热/气云储能能源集线器(energy hub,EH)结构,从参与云储能商业模式的用户侧与云储能提供商出发,构建两主体双层优化模型。底层基于长短期记忆和贝叶斯神经网络的概率预测方法,刻画新能源出力的不确定性,建立考虑需求响应的用户侧云储能充放能模型,以用户总成本最小为目标优化决策用户侧充放能行为,并将决策信息传递到云储能提供商。顶层以云储能提供商的总成本最小为目标,集中优化决策实体储能功率和容量的配置问题。通过大M法对目标以及约束中的非线性部分进行松弛线性化,将其转化为混合整数线性规划模型。最后,建立4个典型应用场景,通过Matlab中的YALMIP工具箱调用CPLEX优化求解器对不同场景下的模型进行求解,联合对比在4种不同场景下的整体成本与收益,验证该策略在资源共享、节约系统整体成本等方面的优越性。展开更多
As part of the ongoing information revolution,smart power grid technology has become a key focus area for research into power systems.Intelligent electrical appliances are now an important component of power systems,p...As part of the ongoing information revolution,smart power grid technology has become a key focus area for research into power systems.Intelligent electrical appliances are now an important component of power systems,providing a smart power grid with increased control,stability,and safety.Based on the secure communication requirements of cloud energy storage systems,this paper presents the design and development of a node controller for a cloud energy storage network.The function division and system deployment processes were carried out to ensure the security of the communication network used for the cloud energy storage system.Safety protection measures were proposed according to the demands of the communication network,allowing the system to run safely and stably.Finally,the effectiveness of the system was verified through a client-side distributed energy storage demonstration project in Suzhou,China.The system was observed to operate safely and stably,demonstrating good peak-clipping and valley filling effects,and improving the system load characteristics.展开更多
文摘面向越来越开放的能源交易市场,为充分调动用户侧资源,提出了一种考虑需求响应(demand response,DR)的电/热/气云储能(cloud energy storage,CES)优化配置策略。建立含电/热/气云储能能源集线器(energy hub,EH)结构,从参与云储能商业模式的用户侧与云储能提供商出发,构建两主体双层优化模型。底层基于长短期记忆和贝叶斯神经网络的概率预测方法,刻画新能源出力的不确定性,建立考虑需求响应的用户侧云储能充放能模型,以用户总成本最小为目标优化决策用户侧充放能行为,并将决策信息传递到云储能提供商。顶层以云储能提供商的总成本最小为目标,集中优化决策实体储能功率和容量的配置问题。通过大M法对目标以及约束中的非线性部分进行松弛线性化,将其转化为混合整数线性规划模型。最后,建立4个典型应用场景,通过Matlab中的YALMIP工具箱调用CPLEX优化求解器对不同场景下的模型进行求解,联合对比在4种不同场景下的整体成本与收益,验证该策略在资源共享、节约系统整体成本等方面的优越性。
基金supported by the Technical Project of the State Grid Corporation of China(research and demonstration application of key technology of energy storage cloud for mobile energy storage application of electric vehicles 5419-201971217a-0-0-00)。
文摘As part of the ongoing information revolution,smart power grid technology has become a key focus area for research into power systems.Intelligent electrical appliances are now an important component of power systems,providing a smart power grid with increased control,stability,and safety.Based on the secure communication requirements of cloud energy storage systems,this paper presents the design and development of a node controller for a cloud energy storage network.The function division and system deployment processes were carried out to ensure the security of the communication network used for the cloud energy storage system.Safety protection measures were proposed according to the demands of the communication network,allowing the system to run safely and stably.Finally,the effectiveness of the system was verified through a client-side distributed energy storage demonstration project in Suzhou,China.The system was observed to operate safely and stably,demonstrating good peak-clipping and valley filling effects,and improving the system load characteristics.
