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Synchronously Decentralized Adaptive Robust Planning Method for Multi-Stakeholder Integrated Energy Systems

机译:用于多利益相关者综合能源系统的同步分散的自适应稳健规划方法

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摘要

In the future integrated energy market, the traditional centralized planning method cannot solve the planning problem for multi-stakeholder integrated energy systems (MSIESs). To cope with this problem, this paper proposes a synchronously decentralized adaptive robust programming (SDARP) model for MSIESs based on the analytical target cascading (ATC) algorithm. In this model, different stakeholders are planned in parallel under the source-load uncertainties, aiming at minimizing the annual investment and operation costs and fully taking into account the interactive heating/cooling power transmitted by the district heating/cooling network. In each stakeholder, the column-and-constraint generation algorithm is used to address the robustness problems in the three-layer adaptive robust programming model. In addition, a tractable alternating optimization procedure is used to solve the non-convex SDARP model with finite convergence. Case studies verify the superiority and effectiveness of the SDARP method in dealing with the planning problem of MSIESs.
机译:在未来的综合能源市场中,传统的集中式规划方法无法解决多利益相关者综合能源系统(MSIESS)的规划问题。要应对这个问题,本文提出了一种基于分析目标级联(ATC)算法的MSIESS同步分散的自适应鲁棒编程(SDARP)模型。在该模型中,不同的利益相关者在源负荷的不确定性下并行计划,旨在最大限度地减少年度投资和运营成本,并完全考虑到区域供热/冷却网络传输的交互式加热/冷却功率。在每个利益相关者中,列和约束生成算法用于解决三层自适应鲁棒编程模型中的鲁棒性问题。此外,还用于解决具有有限收敛的非凸的SDARP模型的易旧的交替优化过程。案例研究验证了SDARP方法在处理MSIES的规划问题方面的优势和有效性。

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