Day-ahead optimal dispatch of an integrated energy system considering time-frequency characteristics of renewable energy source output. (15th October 2020) - Zheng, Lingwei; Zhou, Xingqiu; Qiu, Qi; Yang, Lan
Abstract: The intermittency and uncertainty output of renewable energy source (RES) poses a challenge for the optimal dispatch of an integrated energy system (IES). Many current studies focus on the time-domain characteristics of the RES prediction, while ignoring the time-frequency characteristics of the prediction, thus the operation is usually scheduled on a uniform time-step. Based on this context, an adaptive hybrid dispatch time-step (AHDT) determination method based on the time-frequency characteristics of the prediction is proposed. Different from the traditional time-step, AHDT is non-uniform. Firstly, the Hilbert-Huang transform is used to convert the predicted RES output data to the time-frequency. Next, a time-step function which reflects the mapping of time-step and instantaneous frequency is constructed to suggest an adaptive time-step in each dispatch segment. Then, an optimal day-ahead dispatch model of a typical IES with AHDT, which is essentially a mixed integer quadratic programming (MIQP) problem, is established. Finally, the day-ahead schedules of each unit are obtained by solving the MIQP problem. The simulations are conducted in a total of twenty randomly selected days. The results show that the AHDT method is superior to the uniform time-step method for its effect in reducing the operating cost and the optimization-calculating time cost. Highlights: An adaptive hybrid dispatch time-step (AHDT) determination method is proposed. AHDT based on time-frequency features of predicted data is non-uniform. Time-frequency features of predicted renewable source output is extracted by HHT. The method is proposed for day-ahead dispatch of integrated energy systems. The simulations conducted in 20 random days show the performance in cost-saving.