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
The high penetration of variable renewable energy raises a flexibility challenge in the power system.This raises the necessity of considering the adequacy of flexibility in power system planning.However,the flexibilit...The high penetration of variable renewable energy raises a flexibility challenge in the power system.This raises the necessity of considering the adequacy of flexibility in power system planning.However,the flexibility of the power system covers a wide range of timescales,from seconds to months.This poses difficulties in planning of multi-timescale flexible resources.This paper proposes a new perspective on the modeling and planning of multi-timescale flexible resources in power systems with high penetration of variable renewable energy.The operational boundaries of flexible resources are transformed into a characteristic domain,where flexibility at different timescales can be added and the balance of flexible supply and demand can be expressed as algebraic equations.Such modeling facilitates rigorous multi-timescale flexibility balance metrics.Furthermore,a planning method for multi-timescale flexibility is proposed based on the model in the characteristic domain.The proposed planning method is tested using data from China's Xinjiang provincial power grid.Results show the proposed method can characterize multi-timescale flexibility with high accuracy,thus making it possible to fully account for flexibility at different timescales.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.
基金supported by the Science and Technology Project of State Grid Corporation of China"The technology and application of model refinement and aggregation to support multi-level,multiagent and multiperiod dispatch"(5100-202099497A-0-0-00).
文摘The high penetration of variable renewable energy raises a flexibility challenge in the power system.This raises the necessity of considering the adequacy of flexibility in power system planning.However,the flexibility of the power system covers a wide range of timescales,from seconds to months.This poses difficulties in planning of multi-timescale flexible resources.This paper proposes a new perspective on the modeling and planning of multi-timescale flexible resources in power systems with high penetration of variable renewable energy.The operational boundaries of flexible resources are transformed into a characteristic domain,where flexibility at different timescales can be added and the balance of flexible supply and demand can be expressed as algebraic equations.Such modeling facilitates rigorous multi-timescale flexibility balance metrics.Furthermore,a planning method for multi-timescale flexibility is proposed based on the model in the characteristic domain.The proposed planning method is tested using data from China's Xinjiang provincial power grid.Results show the proposed method can characterize multi-timescale flexibility with high accuracy,thus making it possible to fully account for flexibility at different timescales.
