Optimal sizing of battery energy storage system in smart microgrid considering virtual energy storage system and high photovoltaic penetration

Abstract In the smart microgrid system, the optimal sizing of battery energy storage system (BESS) considering virtual energy storage system (VESS) can minimize system cost and keep system stable operation. This paper proposes a two-layer BESS optimal sizing strategy considering dispatch of VESS in a smart microgrid with high photovoltaic (PV) penetration. In the first layer, VESS modelling and aggregation are established, and the initial size of BESS is determined by considering VESS participation in demand response program. In the second layer, the optimal sizing of BESS is studied and the optimal energy resources dispatching strategy is formulated via considering various constraints in the system. The mean-variance Markowitz theory is applied to assess the risk of system cost variability due to the presence of PV and load uncertainties. With the ratio of load varies from 70% to 130%, and PV generation ratio from 40% to 100%, sensitivity analysis reveals the optimal size of BESS is less impacted by PV generation change. Also with VaR(95%) the risk of system cost variability can be further reduced through VESS participation.

[1]  Lina Yang,et al.  Cooling load reduction by using thermal mass and night ventilation , 2008 .

[2]  Dan Wang,et al.  Performance evaluation of controlling thermostatically controlled appliances as virtual generators using comfort-constrained state-queueing models , 2014 .

[3]  David J. Hill,et al.  Multi-Agent Optimal Allocation of Energy Storage Systems in Distribution Systems , 2017, IEEE Transactions on Sustainable Energy.

[4]  Tao Yang,et al.  Optimal Coordination of Building Loads and Energy Storage for Power Grid and End User Services , 2018, IEEE Transactions on Smart Grid.

[5]  Chenxi Zhang,et al.  Coordinated planning of distributed WT, shared BESS and individual VESS using a two-stage approach , 2020 .

[6]  Xin Ma,et al.  Low carbon roadmap of residential building sector in China: Historical mitigation and prospective peak , 2020 .

[7]  Mohammad SHAHIDEHPOUR,et al.  Optimal sizing of PV and battery-based energy storage in an off-grid nanogrid supplying batteries to a battery swapping station , 2018, Journal of Modern Power Systems and Clean Energy.

[8]  X. Xia,et al.  Minimum cost solution of photovoltaic–diesel–battery hybrid power systems for remote consumers , 2013 .

[9]  Loi Lei Lai,et al.  Optimal Sizing of Battery Energy Storage System in Smart Microgrid with Air-conditioning Resources , 2020, 2020 IEEE International Smart Cities Conference (ISC2).

[10]  Canbing Li,et al.  Optimal Sizing of PV and BESS for a Smart Household Considering Different Price Mechanisms , 2018, IEEE Access.

[11]  Hedayat Saboori,et al.  Stochastic optimal battery storage sizing and scheduling in home energy management systems equipped with solar photovoltaic panels , 2017 .

[12]  Loi Lei Lai,et al.  Two-stage optimal scheduling of air conditioning resources with high photovoltaic penetrations , 2019 .

[13]  Tarek AlSkaif,et al.  Optimal energy management in all-electric residential energy systems with heat and electricity storage , 2019, Applied Energy.

[14]  Loi Lei Lai,et al.  A comprehensive review on large-scale photovoltaic system with applications of electrical energy storage , 2017 .

[15]  Tao Jiang,et al.  Dynamic economic dispatch of a hybrid energy microgrid considering building based virtual energy storage system , 2017 .

[16]  David J. Hill,et al.  Multi-Timescale Coordinated Voltage/Var Control of High Renewable-Penetrated Distribution Systems , 2017, IEEE Transactions on Power Systems.

[17]  Ke Meng,et al.  Two-stage energy management for networked microgrids with high renewable penetration , 2018, Applied Energy.

[18]  Chang Liu,et al.  Optimal Scheduling Method for a Regional Integrated Energy System Considering Joint Virtual Energy Storage , 2019, IEEE Access.

[19]  Sean P. Meyn,et al.  Experimental Evaluation of Frequency Regulation From Commercial Building HVAC Systems , 2015, IEEE Transactions on Smart Grid.

[20]  Zhao Yang Dong,et al.  Coordinated Dispatch of Virtual Energy Storage Systems in LV Grids for Voltage Regulation , 2018, IEEE Transactions on Industrial Informatics.

[21]  Minda Ma,et al.  Decoupling or delusion? Mapping carbon emission per capita based on the human development index in Southwest China. , 2020, The Science of the total environment.

[22]  Nikolaos G. Paterakis,et al.  Implementation of large-scale Li-ion battery energy storage systems within the EMEA region , 2020 .

[23]  Hongjie Jia,et al.  Energy storage capacity optimization for autonomy microgrid considering CHP and EV scheduling , 2018 .

[24]  Joshua N. Cooper,et al.  Parameter identification and model based predictive control of temperature inside a house , 2011 .

[25]  Zhao Yang Dong,et al.  Optimal scheduling of distributed energy resources as a virtual power plant in a transactive energy framework , 2017 .

[26]  Yue Song,et al.  Optimal Operation of Battery Energy Storage System Considering Distribution System Uncertainty , 2018, IEEE Transactions on Sustainable Energy.

[27]  W. V. Sark,et al.  Techno-economic analysis of household and community energy storage for residential prosumers with smart appliances , 2018 .

[28]  Dalia Streimikiene,et al.  Multi-criteria ranking of energy generation scenarios with Monte Carlo simulation , 2017 .

[29]  Cristian Perfumo,et al.  Model-Based Estimation of Energy Savings in Load Control Events for Thermostatically Controlled Loads , 2014, IEEE Transactions on Smart Grid.

[30]  H. Bludszuweit,et al.  A Probabilistic Method for Energy Storage Sizing Based on Wind Power Forecast Uncertainty , 2011, IEEE Transactions on Power Systems.

[31]  Santiago Grijalva,et al.  Modeling for Residential Electricity Optimization in Dynamic Pricing Environments , 2012, IEEE Transactions on Smart Grid.

[32]  Chun Sing Lai,et al.  Sizing of Stand-Alone Solar PV and Storage System With Anaerobic Digestion Biogas Power Plants , 2017, IEEE Transactions on Industrial Electronics.

[33]  Giorgio Locatelli,et al.  A Financial Model for Lithium-Ion Storage in a Photovoltaic and Biogas Energy System , 2019, Applied Energy.

[34]  Xiandong Xu,et al.  Hierarchical microgrid energy management in an office building , 2017 .

[35]  Prabir Barooah,et al.  On the Round-Trip Efficiency of an HVAC-Based Virtual Battery , 2018, IEEE Transactions on Smart Grid.

[36]  Xiaofeng Yin,et al.  Optimal battery sizing of smart home via convex programming , 2017 .

[37]  Andor Jasper,et al.  Risk-based determination of heat demand for central and district heating by a probability theory approach , 2016 .

[38]  Kaining Luan,et al.  Virtual energy storage model of air conditioning loads for providing regulation service , 2020 .

[39]  Xianming Ye,et al.  Battery energy storage sizing optimisation for different ownership structures in a peer-to-peer energy sharing community , 2020, Applied Energy.

[40]  Mohammad Rasol Jannesar,et al.  Optimal placement, sizing, and daily charge/discharge of battery energy storage in low voltage distribution network with high photovoltaic penetration , 2018, Applied Energy.

[41]  Jianzhong Wu,et al.  Benefits of using virtual energy storage system for power system frequency response , 2017 .

[42]  Rainer Storn,et al.  Differential Evolution – A Simple and Efficient Heuristic for global Optimization over Continuous Spaces , 1997, J. Glob. Optim..