Low-carbon Optimal Energy Management of Integrated Electricity-Natural Gas Systems Considering Uncertainties

As global warming becomes increasingly severe, Integrated energy systems play an important role in carbon peaking and carbon neutrality goals. On the one hand, it can improve the security and reliability of energy supply through multi-energy complementary, on the other hand, it can also improve energy utilization efficiency and reduce carbon emissions through energy conversion at the same time. So, we propose a low-carbon scheduling model for the integrated electricity-natural gas energy systems that take into account the uncertainty output of renewable energy and demand response. Firstly, we construct the framework of the systems considering asynchronous mechanism, the second-order cone relaxation method is used for the non-convex network topology constraints, Secondly, demand response consisting curtailable loads and transferrable loads are introduced to the integrated systems. Finally, distributionally robust chance constraint model is used to solve the renewable energy output uncertainty problems. Case study shows the calculation efficiency of the second-order cone relaxation method is improved by 78.9% compared with the traditional segmental linearization, and the higher proportion of transferable loads, the lower carbon emissions and cost of the whole systems, finally, the balance of safety, economy and low-carbon of the system can be achieved when the risk tolerance factor about 0.1.