The integration of substantial renewable energy and controllable resources disrupts the supply-demand balance in distribution grids.Secure operations are dependent on the participation of user-side resources in demand...The integration of substantial renewable energy and controllable resources disrupts the supply-demand balance in distribution grids.Secure operations are dependent on the participation of user-side resources in demand response at both the day-ahead and intraday levels.Current studies typically overlook the spatial--temporal variations and coordination between these timescales,leading to significant day-ahead optimization errors,high intraday costs,and slow convergence.To address these challenges,we developed a multiagent,multitimescale aggregated regulation method for spatial--temporal coordinated demand response of user-side resources.Firstly,we established a framework considering the spatial--temporal coordinated characteristics of user-side resources with the objective to min-imize the total regulation cost and weighted sum of distribution grid losses.The optimization problem was then solved for two different timescales:day-ahead and intraday.For the day-ahead timescale,we developed an improved particle swarm optimization(IPSO)algo-rithm that dynamically adjusts the number of particles based on intraday outcomes to optimize the regulation strategies.For the intraday timescale,we developed an improved alternating direction method of multipliers(IADMM)algorithm that distributes tasks across edge distribution stations,dynamically adjusting penalty factors by using historical day-ahead data to synchronize the regulations and enhance precision.The simulation results indicate that this method can fully achieve multitimescale spatial--temporal coordinated aggregated reg-ulation between day-ahead and intraday,effectively reduce the total regulation cost and distribution grid losses,and enhance smart grid resilience.展开更多
为发挥多元用户侧资源协同作用,提高虚拟电厂(virtual power plant,VPP)参与电碳联合市场收益,降低风光及电价不确定性引起的风险,提出了一种市场环境下考虑多元用户侧资源协同的VPP低碳优化调度方法。首先,基于各种用户侧资源协同作用...为发挥多元用户侧资源协同作用,提高虚拟电厂(virtual power plant,VPP)参与电碳联合市场收益,降低风光及电价不确定性引起的风险,提出了一种市场环境下考虑多元用户侧资源协同的VPP低碳优化调度方法。首先,基于各种用户侧资源协同作用,形成了VPP参与电碳联合市场运行策略;然后,建立VPP奖惩阶梯型碳交易模型,根据碳交易量设定不同交易区间价格,实现了碳电耦合;最后,构建VPP参与电碳联合市场的低碳优化调度模型,在模型中引入条件风险价值,衡量市场收益与风险的关系,并将模型转换为混合整数线性规划问题求解。通过算例分析,证明了该方法可以发挥用户侧资源的协同作用,有效应对风光及电价的不确定性风险,实现VPP参与市场运行的经济性和低碳性。展开更多
基金supported by Science and Technology Program of China Southern Power Grid Corporation under grant number 036000KK52222004(GDKJXM20222117)National Key R&D Program of China for International S&T Cooperation Projects(2019YFE0118700).
文摘The integration of substantial renewable energy and controllable resources disrupts the supply-demand balance in distribution grids.Secure operations are dependent on the participation of user-side resources in demand response at both the day-ahead and intraday levels.Current studies typically overlook the spatial--temporal variations and coordination between these timescales,leading to significant day-ahead optimization errors,high intraday costs,and slow convergence.To address these challenges,we developed a multiagent,multitimescale aggregated regulation method for spatial--temporal coordinated demand response of user-side resources.Firstly,we established a framework considering the spatial--temporal coordinated characteristics of user-side resources with the objective to min-imize the total regulation cost and weighted sum of distribution grid losses.The optimization problem was then solved for two different timescales:day-ahead and intraday.For the day-ahead timescale,we developed an improved particle swarm optimization(IPSO)algo-rithm that dynamically adjusts the number of particles based on intraday outcomes to optimize the regulation strategies.For the intraday timescale,we developed an improved alternating direction method of multipliers(IADMM)algorithm that distributes tasks across edge distribution stations,dynamically adjusting penalty factors by using historical day-ahead data to synchronize the regulations and enhance precision.The simulation results indicate that this method can fully achieve multitimescale spatial--temporal coordinated aggregated reg-ulation between day-ahead and intraday,effectively reduce the total regulation cost and distribution grid losses,and enhance smart grid resilience.
文摘为发挥多元用户侧资源协同作用,提高虚拟电厂(virtual power plant,VPP)参与电碳联合市场收益,降低风光及电价不确定性引起的风险,提出了一种市场环境下考虑多元用户侧资源协同的VPP低碳优化调度方法。首先,基于各种用户侧资源协同作用,形成了VPP参与电碳联合市场运行策略;然后,建立VPP奖惩阶梯型碳交易模型,根据碳交易量设定不同交易区间价格,实现了碳电耦合;最后,构建VPP参与电碳联合市场的低碳优化调度模型,在模型中引入条件风险价值,衡量市场收益与风险的关系,并将模型转换为混合整数线性规划问题求解。通过算例分析,证明了该方法可以发挥用户侧资源的协同作用,有效应对风光及电价的不确定性风险,实现VPP参与市场运行的经济性和低碳性。
