Optimal Operation Scheduling of a Microgrid Incorporating Battery Swapping Stations

This paper proposes optimal operation scheduling of a Microgrid (MG) and battery swapping stations (BSSs) as two independent stakeholders with inherently conflicting objectives. In this regard, a bi-level scheduling framework for optimal decision making of MG and BSSs is presented. Moreover, battery degradation cost is explicitly modeled based on the depth of discharge and the cycle life's intrinsic behavior of batteries. In order to tackle both historical data-based and human-related uncertainties under incomplete information including load demand of MG, photovoltaic generation, wholesale market prices, and swapping requests, a hybrid probabilistic-possibilistic approach considering correlation among uncertainties has been developed. To solve the proposed MG-BSS optimization problem, alternative direction method of multipliers (ADMM) with restart algorithm in a fully decentralized fashion is implemented. The effectiveness of the proposed model is demonstrated on a real-test MG system under different scenarios. Moreover, to compare the computational complexity of the proposed algorithm with the standard ADMM and investigate the scalability of the algorithm, extensive simulations are carried out on different standard test system.

[1]  Hedayat Saboori,et al.  Multi-objective optimum charging management of electric vehicles through battery swapping stations , 2018, Energy.

[2]  Zhi Zhou,et al.  Energy Storage Arbitrage Under Day-Ahead and Real-Time Price Uncertainty , 2018, IEEE Transactions on Power Systems.

[3]  MengChu Zhou,et al.  Centralized Charging Strategy and Scheduling Algorithm for Electric Vehicles Under a Battery Swapping Scenario , 2016, IEEE Transactions on Intelligent Transportation Systems.

[4]  Jianhua Zhang,et al.  Real-Time Optimal Energy and Reserve Management of Electric Vehicle Fast Charging Station: Hierarchical Game Approach , 2018, IEEE Transactions on Smart Grid.

[5]  Danny H. K. Tsang,et al.  Optimal Charging Operation of Battery Swapping and Charging Stations With QoS Guarantee , 2018, IEEE Transactions on Smart Grid.

[6]  Hao Wu,et al.  An Optimization Model for Electric Vehicle Battery Charging at a Battery Swapping Station , 2018, IEEE Transactions on Vehicular Technology.

[7]  Zhao Yang Dong,et al.  Electric Vehicle Battery Charging/Swap Stations in Distribution Systems: Comparison Study and Optimal Planning , 2014, IEEE Transactions on Power Systems.

[8]  Bala Venkatesh,et al.  Short-term scheduling of thermal generators and battery storage with depth of discharge-based cost model , 2015, 2016 IEEE Power and Energy Society General Meeting (PESGM).

[9]  Jie Chen,et al.  The Energy Management and Optimized Operation of Electric Vehicles Based on Microgrid , 2014, IEEE Transactions on Power Delivery.

[10]  Yaming Ren,et al.  On the O(1/n) Convergence Rate of the Auxiliary Problem Principle for Separable Convex Programming and Its Application to the Power Systems Multi-Area Economic Dispatch Problem , 2016 .

[11]  Andrea Michiorri,et al.  Robust optimization for day-ahead market participation of smart-home aggregators , 2018, Applied Energy.

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

[13]  Dan Wang,et al.  Multi-objective distributed generation planning in distribution network considering correlations among uncertainties , 2018, Applied Energy.

[14]  Li Yao,et al.  Economic dispatch for microgrid with electric vehicles in plug-in charging and battery swapping modes , 2016, 2016 IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC).

[15]  Xuan Wei,et al.  Hybrid probabilistic-possibilistic approach for capacity credit evaluation of demand response considering both exogenous and endogenous uncertainties , 2018, Applied Energy.

[16]  Chongqing Kang,et al.  Optimal Bidding Strategy of Battery Storage in Power Markets Considering Performance-Based Regulation and Battery Cycle Life , 2016, IEEE Transactions on Smart Grid.

[17]  Jie Liu,et al.  A Charging Strategy for PV-Based Battery Switch Stations Considering Service Availability and Self-Consumption of PV Energy , 2015, IEEE Transactions on Industrial Electronics.

[18]  Quyen Ho,et al.  Necessary and sufficient KKT optimality conditions in non-convex optimization , 2017, Optim. Lett..

[19]  Stephen P. Boyd,et al.  Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers , 2011, Found. Trends Mach. Learn..

[20]  Feng Zhao,et al.  Stochastic Modeling and Forecasting of Load Demand for Electric Bus Battery-Swap Station , 2014, IEEE Transactions on Power Delivery.

[21]  Geert Deconinck,et al.  Dual-decomposition-based peer-to-peer voltage control for distribution networks , 2017 .

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

[23]  Amin Kargarian,et al.  Decentralized Implementation of Unit Commitment With Analytical Target Cascading: A Parallel Approach , 2018, IEEE Transactions on Power Systems.

[24]  Chengxiong Mao,et al.  ADMM-Based Multiperiod Optimal Power Flow Considering Plug-In Electric Vehicles Charging , 2018, IEEE Transactions on Power Systems.

[25]  Yang Wang,et al.  Toward Urban Electric Taxi Systems in Smart Cities: The Battery Swapping Challenge , 2018, IEEE Transactions on Vehicular Technology.

[26]  Henrik Sandberg,et al.  A Survey of Distributed Optimization and Control Algorithms for Electric Power Systems , 2017, IEEE Transactions on Smart Grid.

[27]  Richard G. Baraniuk,et al.  Fast Alternating Direction Optimization Methods , 2014, SIAM J. Imaging Sci..

[28]  Amjad Anvari-Moghaddam,et al.  Optimal simultaneous day-ahead scheduling and hourly reconfiguration of distribution systems considering responsive loads , 2019, International Journal of Electrical Power & Energy Systems.

[29]  Fei Wang,et al.  Short-Term Solar Irradiance Forecasting Model Based on Artificial Neural Network Using Statistical Feature Parameters , 2012 .

[30]  Grantham Pang,et al.  A charging-scheme decision model for electric vehicle battery swapping station using varied population evolutionary algorithms , 2017, Appl. Soft Comput..