A unified model to optimize configuration of battery energy storage systems with multiple types of batteries

Aiming to minimize the total cost of hybrid power system (HPS), a mathematical model for the configuration of battery energy storage system (BESS) with multiple types of batteries was proposed. The effects of battery types and capacity degradation characteristics on the optimal capacity configurations of the BESS and power scheduling schemes of the HPS were investigated. The effectiveness of the proposed model was verified and illustrated through a case study of a HPS with photovoltaic-wind-biomass-batteries. Results show that the optimal configuration of the BESS can be obtained by solving the proposed model, including the types and the capacities of batteries, and the power scheduling schemes of the batteries. For the integration of the HPS, the BESS with multiple types of batteries has certain economic advantages when compared with the BESS with a single type of batteries. In addition, the types and capacities of batteries in the BESS and the relative power scheduling schemes would change with the electricity curtailment rate of the renewable energy supply of HPS. The total cost of the HPS can be reduced at the expense of a certain amount of renewable energy supply.

[1]  Rangan Banerjee,et al.  Sizing of hybrid energy storage system for a PV based microgrid through design space approach , 2018 .

[2]  Yiping Dai,et al.  Capacity allocation of a hybrid energy storage system for power system peak shaving at high wind power penetration level , 2015 .

[3]  Marc A. Rosen,et al.  Optimization with a simulated annealing algorithm of a hybrid system for renewable energy including battery and hydrogen storage , 2018, Energy.

[4]  Kevin G. Gallagher,et al.  Impact of battery degradation on energy arbitrage revenue of grid-level energy storage , 2017 .

[5]  David Kendrick,et al.  GAMS, a user's guide , 1988, SGNM.

[6]  Xiaohua Xia,et al.  Optimal power flow management for distributed energy resources with batteries , 2015 .

[7]  Sebastian Günther,et al.  Theoretical dimensioning and sizing limits of hybrid energy storage systems , 2018 .

[8]  Behnam Mohammadi-Ivatloo,et al.  Optimal battery technology selection and incentive-based demand response program utilization for reliability improvement of an insular microgrid , 2019, Energy.

[9]  Xiaofeng Yin,et al.  Stochastic Optimal Energy Management of Smart Home With PEV Energy Storage , 2018, IEEE Transactions on Smart Grid.

[10]  John E. Fletcher,et al.  Multi-Timescale Model Predictive Control of Battery Energy Storage System Using Conic Relaxation in Smart Distribution Grids , 2018, IEEE Transactions on Power Systems.

[11]  Joao P. S. Catalao,et al.  Modelling and sizing of NaS (sodium sulfur) battery energy storage system for extending wind power performance in Crete Island , 2015 .

[12]  Iftekhar Ahmad,et al.  Quantifying economic benefits of second life batteries of gridable vehicles in the smart grid , 2014 .

[13]  Dongpu Cao,et al.  Condition Monitoring in Advanced Battery Management Systems: Moving Horizon Estimation Using a Reduced Electrochemical Model , 2018, IEEE/ASME Transactions on Mechatronics.

[14]  Myung-Hyun Ryou,et al.  Semi-empirical long-term cycle life model coupled with an electrolyte depletion function for large-format graphite/LiFePO 4 lithium-ion batteries , 2017 .

[15]  Xiaosong Hu,et al.  Optimal integration of a hybrid solar-battery power source into smart home nanogrid with plug-in electric vehicle , 2017 .

[16]  Michael R. Bussieck,et al.  MINLP Solver Software , 2011 .

[17]  Jihong Wang,et al.  Overview of current development in electrical energy storage technologies and the application potential in power system operation , 2015 .

[18]  Dirk Uwe Sauer,et al.  Optimization of an off-grid hybrid PV-Wind-Diesel system with different battery technologies using genetic algorithm , 2013 .

[19]  Jay F. Whitacre,et al.  Comparative techno-economic analysis of hybrid micro-grid systems utilizing different battery types , 2016 .

[20]  Nooshin Bigdeli,et al.  Optimal management of hybrid PV/fuel cell/battery power system: A comparison of optimal hybrid approaches , 2015 .

[21]  Ahmet Aktas,et al.  Dynamic energy management for photovoltaic power system including hybrid energy storage in smart grid applications , 2018, Energy.

[22]  Meihong Wang,et al.  Energy storage technologies and real life applications – A state of the art review , 2016 .

[23]  G. Yin,et al.  Multi-stress factor model for cycle lifetime prediction of lithium ion batteries with shallow-depth discharge , 2015 .

[24]  Sharifah Rafidah Wan Alwi,et al.  New graphical tools for process changes via load shifting for hybrid power systems based on Power Pinch Analysis , 2013, Clean Technologies and Environmental Policy.

[25]  Andrew W. Thompson Economic implications of lithium ion battery degradation for Vehicle-to-Grid (V2X) services , 2018, Journal of Power Sources.

[26]  Vahid Sohrabi Tabar,et al.  Energy management in hybrid microgrid with considering multiple power market and real time demand response , 2019, Energy.

[27]  Thilo Bocklisch,et al.  Hybrid energy storage approach for renewable energy applications , 2016 .

[28]  Wei-hsin Chen,et al.  Thermal and solid electrolyte interphase characterization of lithium-ion battery , 2019, Energy.

[29]  Zonghai Chen,et al.  Degradation model and cycle life prediction for lithium-ion battery used in hybrid energy storage system , 2019, Energy.

[30]  Ralph E. White,et al.  Review of Models for Predicting the Cycling Performance of Lithium Ion Batteries , 2006 .

[31]  Jianqiu Li,et al.  The battery-supercapacitor hybrid energy storage system in electric vehicle applications: A case study , 2018, Energy.

[32]  Christos N. Markides,et al.  Integrated optimisation of photovoltaic and battery storage systems for UK commercial buildings , 2017 .

[33]  Christoph H. Glock,et al.  Operating a storage-augmented hybrid microgrid considering battery aging costs , 2018, Journal of Cleaner Production.

[34]  Andreas Jossen,et al.  Economic Optimization of Component Sizing for Residential Battery Storage Systems , 2017 .

[35]  Ali Elkamel,et al.  Plug-in electric vehicle batteries degradation modeling for smart grid studies: Review, assessment and conceptual framework , 2018 .

[36]  Yang Li,et al.  Technological Developments in Batteries: A Survey of Principal Roles, Types, and Management Needs , 2017, IEEE Power and Energy Magazine.

[37]  Cheng-Liang Chen,et al.  Transshipment model-based MILP (mixed-integer linear programming) formulation for targeting and design of hybrid power systems , 2014 .