Optimal energy management for prosumers and power plants considering transmission congestion based on carbon emission flow

With the rapid development of high-efficiency, long-distance, and large-capacity power interaction in multiple communities, prosumers in each community who can participate in three markets, i.e., green power market, electricity market and carbon market, may make decisions based on incomplete rational behaviors. The behaviors, e.g., purchasing plenty of power from the power plants through the independent system operator (ISO) at a certain time slot, may cause the problem that a certain power line cannot transmit the power since the amount of power intended to transmit via the power line is beyond the constraint of the physical network, which is regarded as the transmission congestion. How to realize the optimization of energy management for the prosumers and power plants in three markets considering transmission congestion arouse the public concern. In this paper, an optimal energy management method is proposed for the power plants and prosumers with community energy storage considering transmission congestion based on carbon emission flow. It is constructed with a three-level structure, i.e., prosumer level, ISO level and power plant level. At the first level, i.e., prosumer level, based on the cumulative prospect theory, an incomplete rational behavior model is developed for the prosumers who can store the excess power in community energy storage for backup. Due to the existing prosumer peer-to-peer energy trading approach, all prosumers in the same community can be aggregated into a community agent to participate in the three markets, which can deliver the power demand from the prosumers to the ISO at the second level. At the third level, power plant level, two energy trading models of power plants are established, which can deliver the power supply from the power plants to the ISO at the second level, i.e., ISO level, as well. One is presented for the coal-fired power plants according to the cost-benefit function theory, the other one is constructed for the renewable power plants considering the uncertainty of renewable output power. Then, at the second level, an energy management method considering transmission congestion is developed in respect of the power demand from the first-level behavior and the power supply from the third level. Finally, the optimization of energy management is solved under the Lagrange multiplier method with the improved differential evolution algorithm, which is verified in numerical simulations with the effectiveness of the proposed method.