Joint Load Scheduling and Voltage Regulation in the Distribution System With Renewable Generators

By equipping with the advanced smart meters and two-way communications infrastructure, smart grids, as a key component of future smart cities, are able to improve the energy efficiency and reduce the energy cost through real-time monitoring and customer load scheduling. However, the high penetration of intermittent renewable energy such as solar power may cause frequent overvoltage and undervoltage problems at certain buses, making the load scheduling face new challenges on voltage regulation. In this paper, we investigate the impact of voltage constraints on load scheduling by power flow analysis in a power distribution system with renewable generators. A voltage regulator (VR) is introduced to regulate the voltage of buses in the distribution system and assist load scheduling. To jointly minimize the cost and stabilize the voltages of the distribution system, we propose a grid-customer coordinated load scheduling strategy, which simultaneously determines the tap changes of the VR and scheduling of customer electricity loads in each time slot. Finally, we evaluate the performance of the proposed strategy based on realistic power demand and renewable energy generation datasets. Extensive numerical results demonstrate that the proposed strategy can remarkably reduce the energy cost and stabilize the voltage fluctuation of distribution systems.

[1]  Jiming Chen,et al.  Residential Energy Consumption Scheduling: A Coupled-Constraint Game Approach , 2014, IEEE Transactions on Smart Grid.

[2]  Yingsong Huang,et al.  Adaptive Electricity Scheduling in Microgrids , 2014, IEEE Transactions on Smart Grid.

[3]  T. Funabashi,et al.  Optimal Distribution Voltage Control and Coordination With Distributed Generation , 2008, IEEE Transactions on Power Delivery.

[4]  Hany E. Farag,et al.  A Two Ways Communication-Based Distributed Control for Voltage Regulation in Smart Distribution Feeders , 2012, IEEE Transactions on Smart Grid.

[5]  Toshihisa Funabashi,et al.  Optimal Power Scheduling for Smart Grids Considering Controllable Loads and High Penetration of Photovoltaic Generation , 2014, IEEE Transactions on Smart Grid.

[6]  Ju Ren,et al.  Joint Channel Access and Sampling Rate Control in Energy Harvesting Cognitive Radio Sensor Networks , 2019, IEEE Transactions on Emerging Topics in Computing.

[7]  Mianxiong Dong,et al.  QoS-Aware and Load-Balance Routing for IEEE 802.11s Based Neighborhood Area Network in Smart Grid , 2016, Wireless Personal Communications.

[8]  Yan Zhang,et al.  Demand Response Management With Multiple Utility Companies: A Two-Level Game Approach , 2014, IEEE Transactions on Smart Grid.

[9]  Mo-Yuen Chow,et al.  Joint Scheduling of Large-Scale Appliances and Batteries Via Distributed Mixed Optimization , 2015 .

[10]  Magdy M. A. Salama,et al.  Probabilistic Distribution Load Flow With Different Wind Turbine Models , 2013, IEEE Transactions on Power Systems.

[11]  Hamed Mohsenian Rad,et al.  Achieving Optimality and Fairness in Autonomous Demand Response: Benchmarks and Billing Mechanisms , 2013, IEEE Transactions on Smart Grid.

[12]  Weihua Zhuang,et al.  Stochastic information management for voltage regulation in smart distribution systems , 2014, IEEE INFOCOM 2014 - IEEE Conference on Computer Communications.

[13]  Jiming Chen,et al.  Load scheduling with price uncertainty and temporally-coupled constraints in smart grids , 2015, 2015 IEEE Power & Energy Society General Meeting.

[14]  Ju Ren,et al.  Serving at the Edge: A Scalable IoT Architecture Based on Transparent Computing , 2017, IEEE Network.

[15]  Hao Liang,et al.  Mobility-Aware Coordinated Charging for Electric Vehicles in VANET-Enhanced Smart Grid , 2014, IEEE Journal on Selected Areas in Communications.

[16]  J. Aghaei,et al.  Demand response in smart electricity grids equipped with renewable energy sources: A review , 2013 .

[17]  Quanyan Zhu,et al.  Demand Response Management in the Smart Grid in a Large Population Regime , 2016, IEEE Transactions on Smart Grid.

[18]  Wen-Zhan Song,et al.  Optimal Pricing and Energy Scheduling for Hybrid Energy Trading Market in Future Smart Grid , 2015, IEEE Transactions on Industrial Informatics.

[19]  Magdy M. A. Salama,et al.  Novel Coordinated Voltage Control for Smart Distribution Networks With DG , 2011, IEEE Transactions on Smart Grid.

[20]  Pengcheng You,et al.  Joint Scheduling of Large-Scale Appliances and Batteries Via Distributed Mixed Optimization , 2015, IEEE Transactions on Power Systems.

[21]  Martin Maier,et al.  Smart Microgrids: Optimal Joint Scheduling for Electric Vehicles and Home Appliances , 2014, IEEE Transactions on Smart Grid.

[22]  Yoshiaki Tanaka,et al.  Markov-Decision-Process-Assisted Consumer Scheduling in a Networked Smart Grid , 2017, IEEE Access.

[23]  Sumit Paudyal,et al.  Optimal Energy Management of Distribution Systems and Industrial Energy Hubs in Smart Grids , 2012 .

[24]  Grigoris K. Papagiannis,et al.  A Nearly Decentralized Voltage Regulation Algorithm for Loss Minimization in Radial MV Networks With High DG Penetration , 2016, IEEE Transactions on Sustainable Energy.

[25]  Chen Jiang A Probabilistic Bottom-up Technique for Modeling and Simulation of Residential Distributed Harmonic Sources , 2012 .

[26]  Kevin Tomsovic,et al.  Load following functions using distributed energy resources , 2000, 2000 Power Engineering Society Summer Meeting (Cat. No.00CH37134).

[27]  G. Ault,et al.  Supporting high penetrations of renewable generation via implementation of real-time electricity pricing and demand response , 2010 .

[28]  George B. Dantzig,et al.  Linear programming and extensions , 1965 .

[29]  M.R. Iravani,et al.  Power Management Strategies for a Microgrid With Multiple Distributed Generation Units , 2006, IEEE Transactions on Power Systems.

[30]  Georgios B. Giannakis,et al.  Residential Load Control: Distributed Scheduling and Convergence With Lost AMI Messages , 2012, IEEE Transactions on Smart Grid.

[31]  Jiming Chen,et al.  Fast Distributed Demand Response With Spatially and Temporally Coupled Constraints in Smart Grid , 2015, IEEE Transactions on Industrial Informatics.

[32]  Saifur Rahman,et al.  Demand Response as a Load Shaping Tool in an Intelligent Grid With Electric Vehicles , 2011, IEEE Transactions on Smart Grid.

[33]  Pierluigi Siano,et al.  Demand response and smart grids—A survey , 2014 .

[34]  S. M. Shahidehpour,et al.  Probabilistic production costing for photovoltaics-utility systems with battery storage , 1997 .

[35]  Jiming Chen,et al.  Maximizing Network Utility of Rechargeable Sensor Networks With Spatiotemporally Coupled Constraints , 2016, IEEE Journal on Selected Areas in Communications.

[36]  Juan M. Morales,et al.  Real-Time Demand Response Model , 2010, IEEE Transactions on Smart Grid.