Abstract-The ineffective utilization of power resources has attracted much attention in current years. This paper proposes a real-time distributed load scheduling algorithm considering constraints of power supply. Fir...Abstract-The ineffective utilization of power resources has attracted much attention in current years. This paper proposes a real-time distributed load scheduling algorithm considering constraints of power supply. Firstly, an objective function is designed based on the constraint, and a base load forecasting model is established when aggregating renewable generation and non-deferrable load into a power system, which aims to transform the problem of deferrable loads scheduling into a distributed optimal control problem. Then, to optimize the objective function, a real-time scheduling algorithm is presented to solve the proposed control problem. At every time step, the purpose is to minimize the variance of differences between power supply and aggregate load, which can thus ensure the effective utilization of power resources. Finally, simulation examples are provided to illustrate the effectiveness of the proposed algorithm.展开更多
With the promotion of“dual carbon”strategy,data center(DC)access to high-penetration renewable energy sources(RESs)has become a trend in the industry.However,the uncertainty of RES poses challenges to the safe and s...With the promotion of“dual carbon”strategy,data center(DC)access to high-penetration renewable energy sources(RESs)has become a trend in the industry.However,the uncertainty of RES poses challenges to the safe and stable operation of DCs and power grids.In this paper,a multi-timescale optimal scheduling model is established for interconnected data centers(IDCs)based on model predictive control(MPC),including day-ahead optimization,intraday rolling optimization,and intraday real-time correction.The day-ahead optimization stage aims at the lowest operating cost,the rolling optimization stage aims at the lowest intraday economic cost,and the real-time correction aims at the lowest power fluctuation,eliminating the impact of prediction errors through coordinated multi-timescale optimization.The simulation results show that the economic loss is reduced by 19.6%,and the power fluctuation is decreased by 15.23%.展开更多
为解决电力系统中不间断电源(Uninterruptible Power Supply,UPS)调度的自动化问题,提出一种基于分布式控制的UPS调度自动化算法。在深入分析电能需求的特性和系统可靠性要求的基础上,设计分布式控制架构,并选择适用于UPS调度的分布式算...为解决电力系统中不间断电源(Uninterruptible Power Supply,UPS)调度的自动化问题,提出一种基于分布式控制的UPS调度自动化算法。在深入分析电能需求的特性和系统可靠性要求的基础上,设计分布式控制架构,并选择适用于UPS调度的分布式算法,主要包括负载预测与动态调整、分布式能量管理和故障容忍性设计,并通过全面的性能评估,验证算法的可靠性和健壮性。所提算法为UPS调度自动化提供一套全面、可靠的解决方案,有望推动电力系统智能化和效率提升。展开更多
文摘Abstract-The ineffective utilization of power resources has attracted much attention in current years. This paper proposes a real-time distributed load scheduling algorithm considering constraints of power supply. Firstly, an objective function is designed based on the constraint, and a base load forecasting model is established when aggregating renewable generation and non-deferrable load into a power system, which aims to transform the problem of deferrable loads scheduling into a distributed optimal control problem. Then, to optimize the objective function, a real-time scheduling algorithm is presented to solve the proposed control problem. At every time step, the purpose is to minimize the variance of differences between power supply and aggregate load, which can thus ensure the effective utilization of power resources. Finally, simulation examples are provided to illustrate the effectiveness of the proposed algorithm.
文摘With the promotion of“dual carbon”strategy,data center(DC)access to high-penetration renewable energy sources(RESs)has become a trend in the industry.However,the uncertainty of RES poses challenges to the safe and stable operation of DCs and power grids.In this paper,a multi-timescale optimal scheduling model is established for interconnected data centers(IDCs)based on model predictive control(MPC),including day-ahead optimization,intraday rolling optimization,and intraday real-time correction.The day-ahead optimization stage aims at the lowest operating cost,the rolling optimization stage aims at the lowest intraday economic cost,and the real-time correction aims at the lowest power fluctuation,eliminating the impact of prediction errors through coordinated multi-timescale optimization.The simulation results show that the economic loss is reduced by 19.6%,and the power fluctuation is decreased by 15.23%.
文摘为解决电力系统中不间断电源(Uninterruptible Power Supply,UPS)调度的自动化问题,提出一种基于分布式控制的UPS调度自动化算法。在深入分析电能需求的特性和系统可靠性要求的基础上,设计分布式控制架构,并选择适用于UPS调度的分布式算法,主要包括负载预测与动态调整、分布式能量管理和故障容忍性设计,并通过全面的性能评估,验证算法的可靠性和健壮性。所提算法为UPS调度自动化提供一套全面、可靠的解决方案,有望推动电力系统智能化和效率提升。