Stochastic optimization for price-based unit commitment in renewable energy-based personal rapid transit systems in sustainable smart cities

Abstract Power resources scheduling and planning have a great impact on today’s sustainable cities. The conventional power plants as well as renewable energy resources should be committed to considering social, technical, economic, and environmental sustainability optimally. On the other hand, transportation electrification is one of the key pillars of today’s smart cities. In this paper, the generation capacity is scheduled to meet system’s loadability using a new personal rapid transit system, which is carried out utilizing a price-based unit commitment (PBUC) that maximizes profit based on price signals in the context of a stochastic optimization scheme. The personal rapid transit system at the University of West Virginia is considered as a case study based on several prescribed planning scenarios. Wind power energy, as one of the popular renewable energy sources, is considered for power generation. The integrated simulation and optimization results confirm the effectiveness and robustness of the proposed PBUC methodology.

[1]  Sarika Khushalani Solanki,et al.  Price based unit commitment with wind generation and market clearing price variations , 2015, 2015 International Conference on Smart Cities and Green ICT Systems (SMARTGREENS).

[2]  I. S. Amiri,et al.  A modified backward and forward sweep method for microgrid load flow analysis under different electric vehicle load mathematical models , 2019, Electric Power Systems Research.

[3]  Mohamed Marzouk,et al.  Planning utility infrastructure requirements for smart cities using the integration between BIM and GIS , 2020, Sustainable Cities and Society.

[4]  Sishaj P. Simon,et al.  Profit based unit commitment for GENCOs using parallel NACO in a distributed cluster , 2013, Swarm Evol. Comput..

[5]  Ali Elkamel,et al.  Techno-economic evaluation of PEVs energy storage capability in wind distributed generations planning , 2020 .

[6]  A. L. Diniz,et al.  Feasibility and optimality cuts for the MultiStage benders decomposition approach: Application to the network constrained hydrothermal scheduling , 2009, 2009 IEEE Power & Energy Society General Meeting.

[7]  Ali Ahmadian,et al.  A Review on Plug-in Electric Vehicles: Introduction, Current Status, and Load Modeling Techniques , 2020, Journal of Modern Power Systems and Clean Energy.

[8]  Ned Djilali,et al.  Electric Vehicle Participation in Transactive Power Systems Using Real-Time Retail Prices , 2016, 2016 49th Hawaii International Conference on System Sciences (HICSS).

[9]  Tingting Yao,et al.  Are smart cities more ecologically efficient? Evidence from China , 2020 .

[10]  Mohammad Kazem Sheikh-El-Eslami,et al.  Decision making of a virtual power plant under uncertainties for bidding in a day-ahead market using point estimate method , 2013 .

[11]  J. F. Benders.  Partitioning procedures for solving mixed-variables programming problems , 1962 .

[12]  Jose Villar,et al.  Energy management and planning in smart cities , 2016 .

[13]  Fadi Al-Turjman,et al.  Fog computing for sustainable smart cities in the IoT era: Caching techniques and enabling technologies - an overview , 2020, Sustainable Cities and Society.

[14]  Krischonme Bhumkittipich,et al.  Impact of Plug-in Electric Vehicles Integrated into Power Distribution System Based on Voltage-Dependent Power Flow Analysis , 2018 .

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

[16]  Bijaya K. Panigrahi,et al.  Binary grey wolf optimizer models for profit based unit commitment of price-taking GENCO in electricity market , 2019, Swarm Evol. Comput..

[17]  Dipti Srinivasan,et al.  Generation and storage scheduling of combined heat and power , 2017 .

[18]  Henrik W. Bindner,et al.  Application of Network-Constrained Transactive Control to Electric Vehicle Charging for Secure Grid Operation , 2017, IEEE Transactions on Sustainable Energy.

[19]  Ali Elkamel,et al.  Stochastic SCUC considering compressed air energy storage and wind power generation: A techno-economic approach with static voltage stability analysis , 2018 .

[20]  Alfred Baghramian,et al.  An ICA based approach for solving profit based unit commitment problem market , 2016, Appl. Soft Comput..

[21]  Pierluigi Siano,et al.  Optimal day ahead scheduling of combined heat and power units with electrical and thermal storage considering security constraint of power system , 2017 .

[22]  Benjamin D. Leibowicz,et al.  Decarbonizing power and transportation at the urban scale: An analysis of the Austin, Texas Community Climate Plan , 2018, Sustainable Cities and Society.

[23]  Hongtao Wang,et al.  The power system dispatching rolling optimization model based on the coordination of day-ahead and within-day wind-power prediction , 2011, 2011 4th International Conference on Electric Utility Deregulation and Restructuring and Power Technologies (DRPT).

[24]  Mehdi Abapour,et al.  Goal Programming Application for Contract Pricing of Electric Vehicle Aggregator in Join Day-Ahead Market , 2020, Energies.

[25]  Ali Elkamel,et al.  Two-stage stochastic home energy management strategy considering electric vehicle and battery energy storage system: An ANN-based scenario generation methodology , 2020 .

[26]  Mohamed A. Ahmed,et al.  Fuzzy Logic Weight Based Charging Scheme for Optimal Distribution of Charging Power among Electric Vehicles in a Parking Lot , 2020, Energies.

[27]  Tanveer Ahmad,et al.  A review on renewable energy and electricity requirement forecasting models for smart grid and buildings , 2020 .

[28]  Amirhossein Khazali,et al.  A stochastic–probabilistic energy and reserve market clearing scheme for smart power systems with plug-in electrical vehicles , 2015 .

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

[30]  Mehdi Abapour,et al.  A novel economic structure to improve the energy label in smart residential buildings under energy efficiency programs , 2020 .

[31]  Ali Elkamel,et al.  Cost-Benefit Analysis of V2G Implementation in Distribution Networks Considering PEVs Battery Degradation , 2018, IEEE Transactions on Sustainable Energy.

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

[33]  Antonio J. Conejo,et al.  Network-Constrained AC Unit Commitment Under Uncertainty: A Benders’ Decomposition Approach , 2016, IEEE Transactions on Power Systems.

[34]  Vassilios G. Agelidis,et al.  Optimal Robust Unit Commitment of CHP Plants in Electricity Markets Using Information Gap Decision Theory , 2017, IEEE Transactions on Smart Grid.