Abstract
A multi-time scale optimal dispatch model based on the scenario method and model predictive control (MPC) in the AC/DC distribution network is established due to the uncertainty of wind and load. A Markov chain dynamic scenario method is proposed, which generates scenarios by characterizing the forecast error via empirical distribution. Considering the time correlation of the forecast error, Markov chain is adopted in the Markov chain dynamic method to simulate the uncertainty and variability in wind and load with time. A multi-time scale optimal dispatch strategy based on MPC is proposed. The operation scheduling of operation units is solved in day-ahead and intraday optimal dispatch by minimizing the expected value of total cost in each scenario. In the real-time optimal dispatch, the stability and robustness of system operation are considered. MPC is adopted in the real-time optimal dispatch, taking the intraday scheduling as reference and using the roll optimization method to compute real-time optimal dispatch scheduling to smooth the output power. The simulation results in a 50-node system with uncontrollable distributed energy demonstrate that the proposed model and strategy can effectively eliminate fluctuations in wind and load in AC/DC distribution networks.
Highlights
In order to better deal with the uncertainty of wind power and improve the prediction precision, a multi-time scale optimal dispatch model based on Markov chain dynamic scenario method and model predictive control (MPC) for the AC/DC distribution network is proposed in this paper, and the main contributions are as follows: (1) e distribution of the forecast error is generally assumed as normal distribution and beta distribution, which is a relatively simple way to simulate the uncertainty of wind power without using historical error data
A multi-time scale optimal dispatch model of an AC/DC distribution network based on the Markov chain dynamic scenario method and MPC is proposed. e Markov chain dynamic method is proposed to generate a scenario to address with the fluctuation of uncontrollable energy, and the output power of the unit is solved by adopting roll optimization in intraday optimal dispatch based on MPC, realizing the coordination of day-ahead, intraday, and realtime optimization and the consumption of wind turbine
(1) As the correlation of the forecast error state with time is considered, the scenario generated by the Markov chain dynamic scenario method has a higher coverage ratio than the scenario generated by the dynamic scenario method when the time scale is long and the solved dispatch schedule using the Markov chain dynamic method has less fluctuations, which improves the stability of the AC/DC distribution network and ensures the safe operation of the system
Summary
Unlike the traditional time scale subdivision, model predictive control (MPC) adopts the roll optimization method to subdivide the time scale and considers the feedback correction of the control process, which can address the fluctuation of controllable distributed energy well. In order to better deal with the uncertainty of wind power and improve the prediction precision, a multi-time scale optimal dispatch model based on Markov chain dynamic scenario method and MPC for the AC/DC distribution network is proposed in this paper, and the main contributions are as follows:. Erefore, in real-time optimal dispatch, it is only necessary to adjust the output power of fast response device appropriately based on the expected value according to the measured wind power, which can meet the load power of system and solve the problem of volatility of DG power, improving the stability of system In the day-ahead and intraday dispatch, the scenariobased method is adopted to deal with the uncertainty of wind power. e on-off state of device, the grid purchase decision, the output power of regular device, and the expected power of the fast response device are solved in day-ahead and intraday optimal dispatch by minimizing the expected value of total cost in each scenario. e system stability is mainly considered in real-time optimal dispatch since most of the costs have been optimized. e expected power of the fast response device solved in the dayahead and intraday dispatch is taken as the reference to minimize the difference between the solved control variables and the expected value by roll optimization and feedback correction. erefore, in real-time optimal dispatch, it is only necessary to adjust the output power of fast response device appropriately based on the expected value according to the measured wind power, which can meet the load power of system and solve the problem of volatility of DG power, improving the stability of system
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