Energy Reports (Nov 2022)
A low-carbon peak-load regulation trading strategy for large-scale wind power integration using information gap decision theory
Abstract
It is critical for power system to uphold operation security while considering the cooperation of thermal power and new flexible resources, such as energy storage and demand response (DR). This paper investigates the integration of carbon emission trading with peak-load regulation trading to analyze the effects of carbon change generated using thermal power, energy storage, and demand response, and builds a deterministic multisource low-carbon peak-load regulation trading optimization model. To describe wind power uncertainty, we apply information gap decision theory (IGDT) to quantify the information gap between the predicted and actual data of wind power; subsequently, we construct a multisource low-carbon peak-load regulation trading optimization model based on IGDT considering the uncertainty. Finally, a local power grid in Northwest China is considered as a case study, and we establish regular, low-carbon, stochastic and comprehensive four peak-load regulation scenarios to analyze the impact of carbon emissions trading, energy storage, and DR involved in wind power peak-load regulation trading. The results show the following. (1) The individual application of the energy storage system (ESS) and DR can reduce peak-load regulation cost by 4.64% and 7.68%, respectively, whereas a 8.38% reduction is achieved when they are applied together. (2) When considering the uncertainty of wind power, the grid connected power of wind power is reduced by 2.15% and the total peak shaving cost is increased by 10%. With the increase in uncertainty, the cost of peak shaving trading scheme is always lower than the expected value, indicating that the IGDT method is effective. (3) When the price of the carbon emission trading ranges from 85–95 CN¥/t, the peak-load regulation cost of thermal power units are compensated; moreover, the peak-load regulation cost of wind power and allowable uncertainty reach optimum values when the acceptable price is less than 80 CN¥/t in the worst scenario. In summary, the ESS and DR can enhance the flexibility of the system for peak-load regulation, thus increasing wind power grid connection, and carbon emissions trading can improve the net economy of peak-load regulation of thermal power units. The IGDT method can describe the uncertainty risk of wind power output and establish a peak-load regulation trading scheme that satisfies the expectations of decision makers with different risk attitudes. The peak-load regulation trading scheme must carefully consider the carbon emission trading price: if the carbon emission trading price is excessively high, it will result in a retaliatory grid connection of wind power to compensate for the carbon trading costs, and the system cost will increase rapidly.
