Energy Storage System Analysis Review for Optimal Unit Commitment

Energy storage systems (ESSs) are essential to ensure continuity of energy supply and maintain the reliability of modern power systems. Intermittency and uncertainty of renewable generations due to fluctuating weather conditions as well as uncertain behavior of load demand make ESSs an integral part of power system flexibility management. Typically, the load demand profile can be categorized into peak and off-peak periods, and adding power from renewable generations makes the load-generation dynamics more complicated. Therefore, the thermal generation (TG) units need to be turned on and off more frequently to meet the system load demand. In view of this, several research efforts have been directed towards analyzing the benefits of ESSs in solving optimal unit commitment (UC) problems, minimizing operating costs, and maximizing profits while ensuring supply reliability. In this paper, some recent research works and relevant UC models incorporating ESSs towards solving the abovementioned power system operational issues are reviewed and summarized to give prospective researchers a clear concept and tip-off on finding efficient solutions for future power system flexibility management. Conclusively, an example problem is simulated for the visualization of the formulation of UC problems with ESSs and solutions.

[1]  Tomonobu Senjyu,et al.  Smart house-based optimal operation of thermal unit commitment for a smart grid considering transmission constraints , 2018 .

[2]  Javier Contreras,et al.  Stochastic Unit Commitment in Isolated Systems With Renewable Penetration Under CVaR Assessment , 2016, IEEE Transactions on Smart Grid.

[3]  Kyung Soo Kook,et al.  Control Strategy of BESS for Providing Both Virtual Inertia and Primary Frequency Response in the Korean Power System , 2019, Energies.

[4]  Ahmad Sadeghi Yazdankhah,et al.  Integration of Demand Response and Hydrogen Storage System in Security Constrained Unit Commitment with High Penetration of Wind Energy , 2018, Electrical Engineering (ICEE), Iranian Conference on.

[5]  K. Manivannan,et al.  Neural Based Tabu Search method for solving unit commitment problem , 2002 .

[6]  Anna Scaglione,et al.  A Dynamic Multistage Stochastic Unit Commitment Formulation for Intraday Markets , 2018, IEEE Transactions on Power Systems.

[7]  Sishaj P. Simon,et al.  Nodal ant colony optimization for solving profit based unit commitment problem for GENCOs , 2012, Appl. Soft Comput..

[8]  Wencong Su,et al.  A Literature Review of Stochastic Programming and Unit Commitment , 2015 .

[9]  Scott Samuelsen,et al.  Impact of electricity deregulation in the state of California , 2017 .

[10]  Dilip Datta,et al.  Optimization of unit commitment problem with ramp-rate constraint and wrap-around scheduling , 2019 .

[11]  D. P. Kothari,et al.  A solution to the unit commitment problem—a review , 2013 .

[12]  Jan Kleissl,et al.  Energy dispatch schedule optimization for demand charge reduction using a photovoltaic-battery storage system with solar forecasting , 2014 .

[13]  Anastasios G. Bakirtzis,et al.  A genetic algorithm solution to the unit commitment problem , 1996 .

[14]  Yog Raj Sood,et al.  Market-based participation of energy storage scheme to support renewable energy sources for the procurement of energy and spinning reserve , 2019 .

[15]  Dipti Srinivasan,et al.  A genetic algorithm - differential evolution based hybrid framework: Case study on unit commitment scheduling problem , 2016, Inf. Sci..

[16]  Abbas Khosravi,et al.  Incorporating Wind Power Forecast Uncertainties Into Stochastic Unit Commitment Using Neural Network-Based Prediction Intervals , 2015, IEEE Transactions on Neural Networks and Learning Systems.

[17]  Tomonobu Senjyu,et al.  Optimal Thermal Unit Commitment for Solving Duck Curve Problem by Introducing CSP, PSH and Demand Response , 2018, IEEE Access.

[18]  Tomonobu Senjyu,et al.  Thermal Units Commitment Integrated with Reactive Power Scheduling for the Smart Grid Considering Voltage Constraints , 2015 .

[19]  Tomonobu Senjyu,et al.  Distributed generation incorporated with the thermal generation for optimum operation of a smart grid considering forecast error , 2015 .

[20]  Rajesh Kumar,et al.  Binary whale optimization algorithm: a new metaheuristic approach for profit-based unit commitment problems in competitive electricity markets , 2019 .

[21]  Tomonobu Senjyu,et al.  Multi-Objective Optimal Capacity Planning for 100% Renewable Energy-Based Microgrid Incorporating Cost of Demand-Side Flexibility Management , 2019, Applied Sciences.

[22]  Tomonobu Senjyu,et al.  A technique for unit commitment with energy storage system , 2007 .

[23]  Shabbir Ahmed,et al.  Multistage Stochastic Unit Commitment Using Stochastic Dual Dynamic Integer Programming , 2019, IEEE Transactions on Power Systems.

[24]  Jaspreet Singh Dhillon,et al.  Multi-objective combined heat and power unit commitment using particle swarm optimization , 2019, Energy.

[25]  Ali Mohammad Ranjbar,et al.  Resilient Transactive Control for Systems With High Wind Penetration Based on Cloud Computing , 2018, IEEE Transactions on Industrial Informatics.

[26]  Jana Heckenbergerova,et al.  Sensitivity analysis of PCA method for wind ramp event detection , 2016, 2016 IEEE 16th International Conference on Environment and Electrical Engineering (EEEIC).

[27]  S. M. Shahidehpour,et al.  Unit commitment using a hybrid model between Lagrangian relaxation and genetic algorithm in competitive electricity markets , 2004 .

[28]  Dipti Srinivasan,et al.  Multi-agent modeling for solving profit based unit commitment problem , 2013, Appl. Soft Comput..

[29]  Ahmet Onen,et al.  Assessment of Battery Storage Technologies for a Turkish Power Network , 2019, Sustainability.

[30]  Augusto Q. Novais,et al.  Symmetry breaking in MILP formulations for Unit Commitment problems , 2016, Comput. Chem. Eng..

[31]  Eiichi Tanaka,et al.  An Evolutionary Programming Solution to the Unit Commitment Problem , 1997 .

[32]  Hiroyuki Mori,et al.  Strategic Tabu Search for Unit Commitment in Power Systems , 2003 .

[33]  Chuntian Cheng,et al.  A mixed integer linear programming model for unit commitment of thermal plants with peak shaving operation aspect in regional power grid lack of flexible hydropower energy , 2019, Energy.

[34]  Jaspreet Singh Dhillon,et al.  Profit based unit commitment using hybrid optimization technique , 2018 .

[35]  Nilay Shah,et al.  Optimization and control of offshore wind farms with energy storage systems , 2018 .

[36]  C. C. A. Rajan,et al.  A hybrid approach based on PSO and EP for proficient solving of Unit Commitment Problem , 2011, International Conference and Utility Exhibition on Green Energy for Sustainable Development.

[37]  J. S. Dhillon,et al.  Profit based unit commitment using memetic binary differential evolution algorithm , 2019, Appl. Soft Comput..

[38]  Tomonobu Senjyu,et al.  Critical Boundary Index (CBI) based on active and reactive power deviations , 2018, International Journal of Electrical Power & Energy Systems.

[39]  Sishaj P. Simon,et al.  Profit based unit commitment: A parallel ABC approach using a workstation cluster , 2012, Comput. Electr. Eng..

[40]  Koji Shimada,et al.  Evolution from the renewable portfolio standards to feed-in tariff for the deployment of renewable energy in Japan , 2017 .

[41]  Tomonobu Senjyu,et al.  Distributed generation integrated with thermal unit commitment considering demand response for energy storage optimization of smart grid , 2016 .

[42]  Cristobal Gallego-Castillo,et al.  A review on the recent history of wind power ramp forecasting , 2015 .

[43]  Nitai Pal,et al.  Modeling of an intelligent battery controller for standalone solar-wind hybrid distributed generation system , 2020 .

[44]  Tomonobu Senjyu,et al.  Optimal Unit Commitment with Concentrated Solar Power and Thermal Energy Storage in Afghanistan Electrical System , 2019 .

[45]  Anna Scaglione,et al.  Continuous Time Multi-Stage Stochastic Reserve and Unit Commitment , 2018, 2018 Power Systems Computation Conference (PSCC).

[46]  Pierre Courbin,et al.  Smoothing of renewable energy generation using Gaussian-based method with power constraints , 2017 .

[47]  Francisco D. Galiana,et al.  Unit commitment by simulated annealing , 1990 .

[48]  Ross Baldick,et al.  Ramp Event Forecast Based Wind Power Ramp Control With Energy Storage System , 2016, IEEE Transactions on Power Systems.

[49]  Yi Lin,et al.  Unit Commitment Accommodating Large Scale Green Power , 2019 .

[50]  D. P. Kothari,et al.  Solution to profit based unit commitment problem using particle swarm optimization , 2010, Appl. Soft Comput..

[51]  Lu Yuan,et al.  A Mixed-Integer Convex Programming Algorithm for Security-Constrained Unit Commitment of Power System with 110-kV Network and Pumped-Storage Hydro Units , 2019, Energies.

[52]  Javier Jiménez,et al.  Contribution of a pumped-storage hydropower plant to reduce the scheduling costs of an isolated power system with high wind power penetration , 2016 .

[53]  Danli Long,et al.  A stochastic optimization modeling and algorithmic strategy for the security constrained unit commitment with wind farm , 2014, 2014 China International Conference on Electricity Distribution (CICED).

[54]  Leszek Kasprzyk,et al.  Effects of binary variables in mixed integer linear programming based unit commitment in large-scale electricity markets , 2018 .

[55]  Chawalit Jeenanunta,et al.  Stochastic unit commitment model for power system with renewable energy , 2017, 2017 International Electrical Engineering Congress (iEECON).

[56]  Qian Zhou,et al.  Minimum Frequency and Voltage Stability Constrained Unit Commitment for AC/DC Transmission Systems , 2019, Applied Sciences.

[57]  Andreas Jossen,et al.  Ageing and Efficiency Aware Battery Dispatch for Arbitrage Markets Using Mixed Integer Linear Programming , 2019, Energies.

[58]  C. Christober Asir Rajan,et al.  An evolutionary programming based simulated annealing method for solving the unit commitment problem , 2007 .

[59]  Prakash Kumar Hota,et al.  Gravitational Search Algorithm for Optimal Economic Dispatch , 2012 .

[60]  Mohammad SHAHIDEHPOUR,et al.  Integration of power-to-hydrogen in day-ahead security-constrained unit commitment with high wind penetration , 2017 .

[61]  Tomonobu Senjyu,et al.  Multi objective unit commitment with voltage stability and PV uncertainty , 2018, Applied Energy.

[62]  Chang Song Li,et al.  Study on Unit Commitment Problem Considering Large-Scale Superconducting Magnetic Energy Storage Systems , 2016, IEEE Transactions on Applied Superconductivity.

[63]  Mehrdad Tarafdar Hagh,et al.  Security Constrained Unit Commitment (SCUC) formulation and its solving with Modified Imperialist Competitive Algorithm (MICA) , 2017, Journal of King Saud University - Engineering Sciences.

[64]  Daren Yu,et al.  Overview of wind power intermittency: Impacts, measurements, and mitigation solutions , 2017 .

[65]  Hamdi Abdi,et al.  A novel priority-based stochastic unit commitment considering renewable energy sources and parking lot cooperation , 2018, Energy.

[66]  James E. Price.  Evaluation of stochastic unit commitment for renewable integration in California's energy markets , 2015, 2015 IEEE Power & Energy Society General Meeting.

[67]  Hani Mavalizadeh,et al.  Robust hydrothermal unit commitment: A mixed-integer linear framework , 2018, Energy.

[68]  Koichi Nara,et al.  LAGRANGIAN RELAXATION METHOD FOR LONG-TERM UNIT COMMITMENT , 1990 .

[69]  Suttichai Premrudeepreechacharn,et al.  An Improved DA-PSO Optimization Approach for Unit Commitment Problem , 2019, Energies.

[70]  Ignacio Blanco,et al.  An Efficient Robust Solution to the Two-Stage Stochastic Unit Commitment Problem , 2016, IEEE Transactions on Power Systems.

[71]  David L. Woodruff,et al.  Stochastic Unit Commitment Performance Considering Monte Carlo Wind Power Scenarios , 2018, 2018 IEEE International Conference on Probabilistic Methods Applied to Power Systems (PMAPS).

[72]  Gonzalo E. Alvarez,et al.  Optimization of the integration among traditional fossil fuels, clean energies, renewable sources, and energy storages: An MILP model for the coupled electric power, hydraulic, and natural gas systems , 2020, Comput. Ind. Eng..

[73]  Zhou Qian,et al.  Two-stage stochastic model of unit commitment with wind farm , 2014, 2014 China International Conference on Electricity Distribution (CICED).

[74]  Dong-Jun Won,et al.  Implementation of Optimal Scheduling Algorithm for Multi-Functional Battery Energy Storage System , 2019 .

[75]  Tomonobu Senjyu,et al.  Optimal Consumer Efforts and Operational Costs Based Analysis for a Smart Grid , 2019, Electric Power Components and Systems.

[76]  Hamid Khayyam,et al.  A probabilistic unit commitment model for optimal operation of plug-in electric vehicles in microgrid , 2016 .

[77]  Jianhui Wang,et al.  Stochastic Optimization for Unit Commitment—A Review , 2015, IEEE Transactions on Power Systems.

[78]  C. Y. Chung,et al.  Power System Operational Adequacy Evaluation With Wind Power Ramp Limits , 2018, IEEE Transactions on Power Systems.

[79]  R. Hemmati,et al.  Short-term bulk energy storage system scheduling for load leveling in unit commitment: modeling, optimization, and sensitivity analysis. , 2016, Journal of advanced research.

[80]  Kit Po Wong,et al.  Unit commitment considering probabilistic wind generation , 2012 .

[81]  Tao Li,et al.  Cost of Reliability Analysis Based on Stochastic Unit Commitment , 2008, IEEE Transactions on Power Systems.

[82]  Daniel Kirschen,et al.  A hybrid stochastic/interval approach to transmission-constrained unit commitment , 2015, 2015 IEEE Power & Energy Society General Meeting.

[83]  R. Naresh,et al.  Binary fish swarm algorithm for profit-based unit commitment problem in competitive electricity market with ramp rate constraints , 2015 .

[84]  Hoay Beng Gooi,et al.  Corrective economic dispatch and operational cycles for probabilistic unit commitment with demand response and high wind power , 2016 .

[85]  Paul Deane,et al.  Thermal power plant operating regimes in future British power systems with increasing variable renewable penetration , 2015 .

[86]  Coriolano Salvini,et al.  A Memetic Computing Approach for Unit Commitment with Energy Storage Systems , 2017 .

[87]  Xueqing Zhang,et al.  Unit commitment using Lagrangian relaxation and particle swarm optimization , 2014 .

[88]  Li Han,et al.  A coordinated dispatch method for energy storage power system considering wind power ramp event , 2019, Appl. Soft Comput..

[89]  Yasunori Mitani,et al.  Self-Adaptive Virtual Inertia Control-Based Fuzzy Logic to Improve Frequency Stability of Microgrid With High Renewable Penetration , 2019, IEEE Access.

[90]  Tomonobu Senjyu,et al.  Security-constrained optimal utility-scale solar PV investment planning for weak grids: Short reviews and techno-economic analysis , 2019, Applied Energy.

[91]  K. Lakshmi,et al.  Genco's Profit Based Unit Commitment Using Artificial Immune System in Day Ahead Competitive Electricity Markets , 2014 .

[92]  Neng Fan,et al.  Contingency-constrained unit commitment with post-contingency corrective recourse , 2014, Ann. Oper. Res..

[93]  Tomonobu Senjyu,et al.  Development of renewable energy resources in Afghanistan for economically optimized cross-border electricity trading , 2017 .

[94]  A. H. Mantawy,et al.  Unit commitment by tabu search , 1998 .

[95]  David Pozo,et al.  Stochastic Unit Commitment of a Distribution Network with Non-ideal Energy Storage , 2019, 2019 International Conference on Smart Energy Systems and Technologies (SEST).

[96]  Ahad Kazemi,et al.  A Benders decomposition approach for a combined heat and power economic dispatch , 2013 .

[97]  Alfons Kather,et al.  Effect of Different Interval Lengths in a Rolling Horizon MILP Unit Commitment with Non-Linear Control Model for a Small Energy System , 2019, Energies.

[98]  Tomonobu Senjyu,et al.  Duck curve problem solving strategies with thermal unit commitment by introducing pumped storage hydroelectricity & renewable energy , 2017, 2017 IEEE 12th International Conference on Power Electronics and Drive Systems (PEDS).

[99]  Sukhdeo Sao,et al.  An Improved TLBO Algorithm to Solve Profit Based Unit Commitment Problem under Deregulated Environment , 2016 .

[100]  Rajesh Kumar,et al.  Binary fireworks algorithm for profit based unit commitment (PBUC) problem , 2016 .

[101]  Tomonobu Senjyu,et al.  Operational Cost Based UC by Introducing HCSP in Case of PVs Power Uncertainty , 2018, 2018 4th International Conference on Electrical Engineering and Information & Communication Technology (iCEEiCT).

[102]  Xiaofei Wang,et al.  Two-stage stochastic optimization for unit commitment considering wind power based on scenario analysis , 2016, 2016 China International Conference on Electricity Distribution (CICED).

[103]  Jinwen Wang,et al.  Hydropower unit commitment with nonlinearity decoupled from mixed integer nonlinear problem , 2018 .

[104]  Gonzalo E. Alvarez,et al.  Security constrained unit commitment scheduling: A new MILP formulation for solving transmission constraints , 2018, Comput. Chem. Eng..

[105]  Mohd Wazir Mustafa,et al.  Recent approaches of unit commitment in the presence of intermittent renewable energy resources: A review , 2017 .