Adaptive robust economic dispatch and real-time control of distribution system considering controllable inverter air-conditioner clusters

With a tremendous number of renewable energy sources (RES) integrated into the distribution system, the inherent uncertainty of RES power generation brings about significant challenges in distribution and power balance within the distribution system. This article proposes an adaptive robust economic dispatch (ARED) model and a real-time control strategy for distribution systems as countermeasures, which make full use of the adjustable capabilities of controllable inverter air-conditioner (IAC) clusters. Firstly, the concept of the adjustable capacity curve (ACC) is developed to accurately quantify the adjustable capacity of an IAC cluster. Afterward, a two-stage adaptive robust optimization is formulated for ARED, which comprehensively takes the adjustable capacity of the IAC cluster and the uncertainty of RES into consideration. Meanwhile, the solution methodology of ARED is also designed based on the column and constraint generation (C&CG) algorithm, where the master problem is quadratic programming with quadratic constraints (QCQP), and the max-min sub-problem is reformulated to a mixed integer linear programming (MILP) form by taking advantage of linear duality theory and big-M method. Finally, a novel real-time decentralized control strategy for IAC clusters is also proposed for purpose of hedging against stochastic RES power fluctuation after every round of ARED decisions. The results of the case study validate the effectiveness of ARED model and real-time control strategy under different uncertainty scenarios of RES power generation.

[1]  Wenchuan Wu,et al.  Chance-Constrained Economic Dispatch Considering Curtailment Strategy of Renewable Energy , 2021, IEEE Transactions on Power Systems.

[2]  Chuangxin Guo,et al.  Distributed Robust Dynamic Economic Dispatch of Integrated Transmission and Distribution Systems , 2021, IEEE Transactions on Industry Applications.

[3]  Pierluigi Siano,et al.  Game-Theoretic Demand Side Management of Thermostatically Controlled Loads for Smoothing Tie-Line Power of Microgrids , 2021, IEEE Transactions on Power Systems.

[4]  Fabrizio Sossan,et al.  Characterizing the Reserve Provision Capability Area of Active Distribution Networks: A Linear Robust Optimization Method , 2020, IEEE Transactions on Smart Grid.

[5]  Haiwang Zhong,et al.  Estimating the Robust P-Q Capability of a Technical Virtual Power Plant Under Uncertainties , 2020, IEEE Transactions on Power Systems.

[6]  Jinyu Wen,et al.  Stochastic Optimization of Economic Dispatch for Microgrid Based on Approximate Dynamic Programming , 2019, IEEE Transactions on Smart Grid.

[7]  Xinyuan Liu,et al.  Two-Stage Robust Security-Constrained Unit Commitment Model Considering Time Autocorrelation of Wind/Load Prediction Error and Outage Contingency Probability of Units , 2019, IEEE Access.

[8]  Liu Junyong,et al.  A Distributionally Robust Reactive Power Optimization Model for Active Distribution Network Considering Reactive Power Support of DG and Switch Reconfiguration , 2019, Energy Procedia.

[9]  Yi Ding,et al.  Equivalent Modeling of Inverter Air Conditioners for Providing Frequency Regulation Service , 2019, IEEE Transactions on Industrial Electronics.

[10]  Lingfeng Wang,et al.  Decentralized Energy Management for Networked Microgrids in Future Distribution Systems , 2018, IEEE Transactions on Power Systems.

[11]  Daniel Kirschen,et al.  Model-Free Renewable Scenario Generation Using Generative Adversarial Networks , 2017, IEEE Transactions on Power Systems.

[12]  Fengqi You,et al.  Data-Driven Stochastic Robust Optimization: General Computational Framework and Algorithm Leveraging Machine Learning for Optimization under Uncertainty in the Big Data Era , 2017, Comput. Chem. Eng..

[13]  Mohammad Shahidehpour,et al.  Security-Constrained Unit Commitment With Flexible Uncertainty Set for Variable Wind Power , 2017, IEEE Transactions on Sustainable Energy.

[14]  Mohammad Shahidehpour,et al.  Decentralized Multiarea Robust Generation Unit and Tie-Line Scheduling Under Wind Power Uncertainty , 2015, IEEE Transactions on Sustainable Energy.

[15]  Raquel García-Bertrand,et al.  Robust Transmission Network Expansion Planning Under Correlated Uncertainty , 2015, IEEE Transactions on Power Systems.

[16]  Long Zhao,et al.  Solving two-stage robust optimization problems using a column-and-constraint generation method , 2013, Oper. Res. Lett..

[17]  Steven H. Low,et al.  Branch Flow Model: Relaxations and Convexification—Part I , 2012, IEEE Transactions on Power Systems.

[18]  Hybrid flow model of cyber physical distribution network and an instantiated decentralized control application , 2022, CSEE Journal of Power and Energy Systems.

[19]  Peichao Zhang,et al.  Unified Control Strategy of Heterogeneous Thermostatically Controlled Loads with Market-based Mechanism , 2020, Journal of Modern Power Systems and Clean Energy.