Multiple stage stochastic planning of integrated electricity and gas system based on distributed approximate dynamic programming

With the increasing coupling of integrated electricity and gas systems, it's essential to implement a proper planning scheme. The planning of the integrated electricity and gas systems usually consists of multiple planning stages and various uncertainties, making the problem difficult to solve. In this paper, combining the approximate dynamic programming method and the alternating direction multiplier method, a distributed approximate dynamic programming based multiple stage stochastic planning scheme is proposed for the integrated electricity and gas systems. The multiple stage stochastic planning scheme realizes the coordination of new installation and expansion of power grid lines, natural gas pipelines, substations, city gates, photovoltaics, wind turbines, gas turbines and energy storage devices, while considering both the long-term and the short-term uncertainties. The multiple stage stochastic planning model is reformulated as a Markov decision process with a sequential decision strategy, in which the investment variables are decided stage by stage with long-term uncertainties gradually revealed in the planning period. The distributed approximate dynamic programming algorithm is used to solve the multiple stage stochastic planning model, which is in the form of the Markov decision process, by decoupling in both temporal and spatial dimensions. Numerical tests on the test system with a 24-node power grid and a 30node natural gas network verify the effectiveness of the multiple stage stochastic planning model.

Automated summary

To achieve the coordinated development of electricity and gas systems, a distributed approximate dynamic programming based multiple stage stochastic planning scheme is proposed in this paper. The scheme combines the approximate dynamic programming method and the alternating direction multiplier method to coordinate the planning of power grid, natural gas pipelines, substations, photovoltaics, wind turbines, gas turbines, and energy storage devices. The scheme considers both long-term and short-term uncertainties, and is validated through numerical tests.