Optimization control of active distribution network based on Photovoltaic forecast information
With the cost declining of Photovoltaic (PV) power generation and the support of government, it can be expected that a large number of PV systems will be accessed to the distribution network in the future. The development of active distribution network provides a good solution to improve the intermittent energy consumptive ability of distribution network. Active distribution network is able to control the controllable units flexibly and effectively. Thus it can achieve optimal operation ensuring system stability and power quality. Based on the existing optimization strategies, this paper proposed two kind optimal strategies according to time scale, long-term comprehensive optimization (in 24 hours) and short-term real-time optimization (in 15 to 30 minutes), to achieve the most economical operation within one day with real-time error correction. Here considering PV power generation as one kind intermittent energy source accessed to the distribution network, long-term optimization needs daily loads and PV systems daily forecast information and short-term real-time optimization needs the ultra short-term forecast of the PV system. Considering the computing time and prediction accuracy, this paper applied PV system grey prediction methods (GM (1, 1)). At last, this paper verified the economical and effective characters of the optimization control strategy by a proper case.