考虑碳-绿证耦合机制的电-气-热综合能源系统分布式鲁棒低碳经济调度

为了保护综合能源系统中不同运营主体的信息隐私，权衡系统运行低碳性和经济性，解决天然气网络鲁棒模型难以求解的问题，提出了考虑碳-绿证耦合机制的电-气-热综合能源系统分布式鲁棒低碳经济调度方法。考虑天然气网络和热力网络的动态特性、碳-绿证耦合机制，构建综合能源系统动态低碳经济调度模型；为了保护各网络运营商的数据隐私，根据能量耦合关系对综合能源系统解耦，建立电-气-热网络的分布式协同优化模型；在此基础上，考虑风电出力和多能负荷的不确定性，提出基于一致性交替方向乘子法的分布式鲁棒优化框架，并利用二阶锥对偶理论与交替优化方法实现含二阶锥约束和二元变量的鲁棒子问题求解。以修改的IEEE 39节点电力网络、比利时20节点天然气网络和15节点热力网络为算例进行仿真分析，验证所提方法能够在源荷不确定性条件下实现综合能源系统各网络分散自治运行，同时兼顾系统运行的低碳性和经济性。

Distributionally robust low-carbon economic dispatch of electricity-gas-heat integrated energy system considering carbon-green certificate coupling mechanism

In order to protect the information privacy of different operators in the integrated energy system(IES),balance the low-carbon and economy of the system operation and solve the problem that the robust model of natural gas network is difficult to solve, a distributionally robust low-carbon economic dispatch method of electricity-gas-heat IES considering the carbon-green certificate coupling mechanism is proposed. Considering the dynamic characteristics of natural gas and heat networks and the carbon-green certificate coupling mechanism, the dynamic low-carbon economic dispatch model of IES is constructed. In order to protect the data privacy of each network operator, a distributed collaborative optimization model of the electricity-gas-heat IES is constructed by decoupling the IES according to the energy coupling relationship. On this basis, considering the uncertainties of wind power output and multi-energy load, a distributionally robust optimization framework based on the consensus-based alternating direction method of multipliers is proposed. And the robust sub-problems with second-order cone constraints and binary variables are solved by using the second-order cone dual theory and alternative optimization method. A modified IEEE 39-bus electricity network, Belgium 20-node natural gas network and a 15-node heat network are taken as examples for simulation analysis. It is verified that the proposed method can realize the decentralized autonomous operation of each network in IES under the condition of uncertain source and load, while balancing the low-carbon and economy of system operation.