Energy

KDE Robust Satisficing for Optimal Load Shedding Under Renewable Uncertainty

  • Min Xin Shu
  • Wei Li
  • Bo Yu
    • Categories Applications - Science and Engineering, Energy, Robust Optimization Tags , , , ,

    Abstract—Renewable-driven direct-current optimal load shedding (DC-OLS) requires a model that is interpretable to operators, data driven under continuous forecast errors, sensitive to severe security failures, and computationally tractable. This paper develops a budgeted KDE-ϕ-HMCR-RS-OLS framework for that purpose. Robust satisficing (RS) replaces ambiguity-radius tuning with an admissible shedding budget. A one-dimensional KDE reference family with … Read more

    Context-Aware Cluster-Based Multi-Uncertainty-Set Distributionally Robust Chance-Constrained DC Optimal Power Flow

  • Qiao Yi Wang
  • Wei Liu
  • Bo Yu
    • Categories Applications - Science and Engineering, Energy, Robust Optimization Tags , , , , ,

    本文提出了一种上下文感知的多不确定性集分鲁棒机会约束直流最优潮流模型。该模型利用气象特征将非凸误差支撑集分解为上下文相关的条件局部模糊集，并通过核回归推断条件权重。极小极大问题被重新表述为一个有限维二阶锥规划问题，并证明了其渐近一致性。对IEEE 30节点系统和RBTS系统的样本外测试表明，所提出的模型在接近预设可靠性水平的情况下具有较高的经验可行性，并避免了全局凸近似导致的过度保守性。 ArticleDownload View PDF

    Time-of-Use Pump Scheduling for Flow Transmission

  • Yuzhen Feng
    • Categories Energy, Scheduling

    We study time-of-use pump scheduling to deliver a required volume using a finite set of pump combinations with empirical flow–power performance, subject to per-shift caps on pump switches. We prove a structural theorem: partitioning the horizon into maximal intervals with constant tariff and shift (atoms), there always exists an optimal schedule with at most one … Read more

    Modeling Adversarial Wildfires for Power Grid Disruption

  • Matthew Brun
  • Xu Andy Sun
  • Jean-Paul Watson
    • Categories (Mixed) Integer Nonlinear Programming, Energy, Second-Order Cone Programming Tags , , , ,

    Electric power infrastructure faces increasing risk of damage and disruption due to wildfire. Operators of power grids in wildfire-prone regions must consider the potential impacts of unpredictable fires. However, traditional wildfire models do not effectively describe worst-case, or even high-impact, fire behavior. To address this issue, we propose a mixed-integer conic program to characterize an … Read more

    Chance-Constrained Linear Complementarity Problems

  • René Henrion
  • Martin Schmidt
    • Categories Complementarity and Variational Inequalities, Energy, Stochastic Programming Tags , , , , ,

    We study linear complementarity problems (LCPs) under uncertainty, which we model using chance constraints. Since the complementarity condition of the LCP is an equality constraint, it is required to consider relaxations, which naturally leads to optimization problems in which the relaxation parameters are minimized for given probability levels. We focus on these optimization problems and … Read more

    Potential-Based Flows – An Overview

  • Marc E. Pfetsch
  • Martin Schmidt
  • Martin Skutella
  • Johannes Thürauf
    • Categories Energy, Network Optimization

    Potential-based flows provide an algebraic way to model static physical flows in networks, for example, in gas, water, and lossless DC power networks. The flow on an arc in the network depends on the difference of the potentials at its end-nodes, possibly in a nonlinear way. Potential-based flows have several nice properties like uniqueness and … Read more

    A Marginal Reliability Impact Based Accreditation Framework for Capacity Markets

  • Feng Zhao
    • Categories Energy Tags , , , , , , ,

    This paper presents a Marginal Reliability Impact (MRI) based resource accreditation framework for capacity market design. Under this framework, a resource is accredited based on its marginal impact on system reliability, thus aligning the resource’s accreditation value with its reliability contribution. A key feature of the MRI-based accreditation is that the accredited capacities supplied by … Read more

    Machine Learning–Enhanced Column Generation for Large-Scale Capacity Planning Problems

  • Felipe Keim
  • Victor Bucarey
  • Qi Zhang
  • Angela Flores-Quiroz
    • Categories (Mixed) Integer Linear Programming, Energy, Facility Planning and Design Tags , ,

    Capacity Planning problems are a class of optimization problems used in diverse industries to improve resource allocation and make investment decisions. Solving real-world instances of these problems typically requires significant computational effort. To tackle this, we propose machine-learning-aided column generation methods for solving large-scale capacity planning problems. Our goal is to accelerate column generation by … Read more

    An Optimal Solution is Not Enough: Alternative Solutions and Optimal Power Systems

  • Matthew Viens
  • jkskolf
  • William E. Hart
  • Michael C. Ferris
    • Categories Applications - Science and Engineering, Energy, Optimization Software and Modeling Systems Tags , , , ,

    Power systems modeling and planning has long leveraged mathematical programming for its ability to provide optimality and feasibility guarantees. One feature that has been recognized in the optimization literature since the 1970s is the existence and meaning of multiple exact optimal and near-optimal solutions, which we call alternative solutions. In power systems modeling, the use … Read more

    Stronger cuts for Benders’ decomposition for stochastic Unit Commitment Problems based on interval variables

  • Azema
  • Vincent Leclère
  • Wim van Ackooij
    • Categories (Mixed) Integer Linear Programming, Energy, Stochastic Programming Tags , ,

    The Stochastic Unit Commitment (SUC) problem models the scheduling of power generation units under uncertainty, typically using a two-stage stochastic program with integer first-stage and continuous second-stage variables. We propose a new Benders decomposition approach that leverages an extended formulation based on interval variables, enabling decomposition by both unit and time interval under mild technical … Read more