针对主动配电网(active distribution network,ADN)中分布式电源和负荷随机波动的特点,提出了基于软常开开关(soft normally open point,SNOP)的主动配电系统多时间尺度控制策略。考虑SNOP的运行工作特性,提出了在长时间尺度上通过配电...针对主动配电网(active distribution network,ADN)中分布式电源和负荷随机波动的特点,提出了基于软常开开关(soft normally open point,SNOP)的主动配电系统多时间尺度控制策略。考虑SNOP的运行工作特性,提出了在长时间尺度上通过配电网全局优化策略实现对SNOP输出进行控制,在短时间尺度上通过引入电压波动迟滞控制实现对SNOP输出参考值的动态调整,以维持线路电压平稳,提升分布式电源的消纳能力。在改进的IEEE 33节点系统中,进行了长时间尺度全局优化、短时间尺度动态调整分析,并对SNOP的安装位置、容量和数量进行了讨论。结果表明,基于SNOP的主动配电系统多时间尺度优化策略是有效可行的,且统一潮流控制器(unified power flow controller,UPFC)型SNOP较背靠背(back to back,B2B)型有更小的容量需求。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
文摘针对主动配电网(active distribution network,ADN)中分布式电源和负荷随机波动的特点,提出了基于软常开开关(soft normally open point,SNOP)的主动配电系统多时间尺度控制策略。考虑SNOP的运行工作特性,提出了在长时间尺度上通过配电网全局优化策略实现对SNOP输出进行控制,在短时间尺度上通过引入电压波动迟滞控制实现对SNOP输出参考值的动态调整,以维持线路电压平稳,提升分布式电源的消纳能力。在改进的IEEE 33节点系统中,进行了长时间尺度全局优化、短时间尺度动态调整分析,并对SNOP的安装位置、容量和数量进行了讨论。结果表明,基于SNOP的主动配电系统多时间尺度优化策略是有效可行的,且统一潮流控制器(unified power flow controller,UPFC)型SNOP较背靠背(back to back,B2B)型有更小的容量需求。
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%.
