Optimal Combined Heat and Power Scheduling of Virtual Power Plants Considering Carbon Capture Technology under Carbon Trading Market

The current carbon accounting and carbon price mechanisms in the carbon trading market provide an endogenous incentive for virtual power plant (VPP) to operate in a low carbon economy by introducing carbon capture equipment in combined heat and power operations to participate in carbon trading. The amount of carbon captured by carbon capture equipment is often not fully controllable due to carbon concentration, flue gas, etc. For this reason, the carbon capture quantity is considered as the sum of the baseline value and the random value obeying the boxed uncertainty set, and brought into the traditional VPP optimal scheduling model considering demand response and thermal decoupling, which effectively balances the robustness, low carbon and economic of the scheduling plan. At the same time, in order to reduce the negative impact of the random value of carbon capture on the heat and power supply of the industrial park, the proposed scheduling model imposes independent constraints on heat and power to avoid the impact of the rough heat and power conversion on the energy supply of the park in the traditional "heat-determined power" mode. The algorithm is designed with reference to the composition of the actual industrial park and relying on credible data sources. The proposed model with random values is converted into a deterministic model by robust peer-to-peer conversion, and the extreme scenario boundaries are scaled by different robust parameters, and a control scenario is designed around whether the carbon capture is random and whether the thermoelectricity is decoupled.