Linfeng Yang

A Fully Adaptive DRO Multistage Framework Based on MDR for Generation Scheduling under Uncertainty

  • Yingyang
  • Linfeng Yang
  • Zhaoyang Dong
    • Categories Applications - OR and Management Sciences Tags , , , , ,

    The growing proliferation of wind power into the power grid achieves a low-cost sustainable electricity supply while introducing technical challenges with associated intermittency. This paper proposes a fully adaptive distributionally robust multistage framework based on mixed decision rules (MDR) for generation scheduling under uncertainty to adapt wind power respecting non-anticipativity in quick-start unit status decision … Read more

    Multiple-Periods Locally-Facet-Based MIP Formulations for the Unit Commitment Problem

  • Linfeng Yang
  • Shifei Chen
  • Zhaoyang Dong
    • Categories (Mixed) Integer Nonlinear Programming, Applications - OR and Management Sciences, Polyhedra Tags , , , , , , ,

    The thermal unit commitment (UC) problem has historically been formulated as a mixed integer quadratic programming (MIQP), which is difficult to solve efficiently, especially for large-scale systems. The tighter characteristic reduces the search space, therefore, as a natural consequence, significantly reduces the computational burden. In literatures, many tightened formulations for a single unit with parts … Read more

    High Dimensional Three-Periods Locally Ideal MIP Formulations for the UC Problem

  • Beihua Fang
  • Wei Li
  • Yan Xu
  • Linfeng Yang
  • Cuo Zhang
    • Categories (Mixed) Integer Nonlinear Programming, Energy, Scheduling Tags , , , ,

    The thermal unit commitment (UC) problem often can be formulated as a mixed integer quadratic programming (MIQP), which is difficult to solve efficiently, especially for large-scale instances. The tighter characteristic re-duces the search space, therefore, as a natural conse-quence, significantly reduces the computational burden. In the literature, many tightened formulations for single units with parts … Read more

    A fully mixed-integer linear programming formulation for economic dispatch with valve-point effects, transmission loss and prohibited operating zones

  • Huangyue Chen
  • Jinbao Jian
  • Shanshan Pan
  • Linfeng Yang
    • Categories (Mixed) Integer Linear Programming, Applications - Science and Engineering Tags , , , , ,

    Economic dispatch (ED) problem considering valve-point effects (VPE), transmission loss and prohibited operating zones (POZ) is a very challenging issue due to its intrinsic non-convex, non-smooth and non-continuous natures. To achieve a near globally solution, a fully mixed-integer linear programming (FMILP) formulation is proposed for such an ED problem. Since the original loss function is … Read more

    Solution for short-term hydrothermal scheduling with a logarithmic size MILP formulation

  • Jinbao Jian
  • Shanshan Pan
  • Linfeng Yang
    • Categories Applications - Science and Engineering Tags , , , ,

    Short-term hydrothermal scheduling (STHS) is a non-convex and non-differentiable optimization problem that is difficult to solve efficiently. One of the most popular strategy is to reformulate the complicated STHS by various linearization techniques that makes the problem easy to solve. However, in this process, a large number of extra continuous variables, binary variables and constraints … Read more

    A Fully Distributed Dual Consensus ADMM Based on Partition for DC-OPF with Carbon Emission Trading

  • Zhaoyang Dong
  • Jiangyao Luo
  • Yan Xu
  • Linfeng Yang
  • Zhenrong Zhang
    • Categories Applications - Science and Engineering, Energy Tags , , , ,

    This paper presents a novel fully distributed alternating direction method of multipliers (ADMM) approach for solving the direct current optimal power flow with carbon emission trading (DC-OPF-CET) problem. Different from the other ADMM-based distributed approaches which disclosing boundary buses and branches information among adjacent subsystems, our proposed method adopts a new strategy by using ADMM … Read more