Look-ahead risk-constrained scheduling for an energy hub integrated with renewable energy

Abstract Energy hubs or multi-energy systems facilitate an improvement in their efficiency and flexibility for different energy supplies. However, the application of energy hubs results in scheduling challenges for the entire system due to the mutual impact of various energy forms and the increase in the number of uncertain variables. One of the parameters of an energy storage system, which is an indispensable component of an energy hub, is the state-of-charge at the end of the first day of scheduling. This parameter is crucial because its final state represents the initial state-of-charge for the second day, which has an effect on the operational cost of the second day. Based on a look-ahead risk-constrained technique, this work investigates the optimal scheduling of an energy hub for two days with the aim of minimizing the total operational cost. The state-of-charges of an energy storage system at the end of the first day is optimized by considering the scheduling result on the second day. The uncertainties of the two days are demonstrated via various scenarios. Additionally, a demand response program is adopted to reduce the total operational cost and increase the system flexibility. The results validate the feasibility of using look-ahead risk-constrained scheduling in an energy hub and indicate that a reduction in the total operational cost is achieved.

[1]  Mahdi Pourakbari-Kasmaei,et al.  A risk-based optimal self-scheduling of smart energy hub in the day-ahead and regulation markets , 2021 .

[2]  Qi Huang,et al.  Economic feasibility of a wind-battery system in the electricity market with the fluctuation penalty , 2020 .

[3]  Sayyad Nojavan,et al.  Stochastic energy procurement of large electricity consumer considering photovoltaic, wind-turbine, micro-turbines, energy storage system in the presence of demand response program , 2015 .

[4]  Haiguo Tang,et al.  A new wind power prediction method based on ridgelet transforms, hybrid feature selection and closed-loop forecasting , 2018, Adv. Eng. Informatics.

[5]  Peng Wang,et al.  Optimum design of a multi-form energy hub by applying particle swarm optimization , 2020 .

[6]  Di Cao,et al.  Designing a standalone wind-diesel-CAES hybrid energy system by using a scenario-based bi-level programming method , 2020 .

[7]  Pierluigi Mancarella,et al.  Matrix modelling of small-scale trigeneration systems and application to operational optimization , 2009 .

[8]  Behnam Mohammadi-Ivatloo,et al.  Stochastic optimization of energy hub operation with consideration of thermal energy market and demand response , 2017 .

[9]  Bin Wang,et al.  Robust Look-Ahead Power Dispatch With Adjustable Conservativeness Accommodating Significant Wind Power Integration , 2015, IEEE Transactions on Sustainable Energy.

[10]  Pengfei Zhao,et al.  Two-Stage Distributionally Robust Optimization for Energy Hub Systems , 2020, IEEE Transactions on Industrial Informatics.

[11]  Shahab Bahrami,et al.  Efficient operation of energy hubs in time-of-use and dynamic pricing electricity markets , 2016 .

[12]  Mohammad Ghiasi,et al.  Extracting Appropriate Nodal Marginal Prices for All Types of Committed Reserve , 2019 .

[13]  Mehdi Hosseinzadeh,et al.  A framework to expedite joint energy-reserve payment cost minimization using a custom-designed method based on Mixed Integer Genetic Algorithm , 2018, Eng. Appl. Artif. Intell..

[14]  Hamdi Abdi,et al.  A general model for energy hub economic dispatch , 2017 .

[15]  Manijeh Alipour,et al.  Stochastic Scheduling of Renewable and CHP-Based Microgrids , 2015, IEEE Transactions on Industrial Informatics.

[16]  Mohammad Sadegh Ghazizadeh,et al.  Sustainable energy hub design under uncertainty using Benders decomposition method , 2018 .

[17]  Noradin Ghadimi,et al.  A new prediction model of battery and wind-solar output in hybrid power system , 2019, J. Ambient Intell. Humaniz. Comput..

[18]  Chongqing Kang,et al.  Review and prospect of integrated demand response in the multi-energy system , 2017 .

[19]  Mahmood Shafiee,et al.  Privacy-preserving mechanism for collaborative operation of high-renewable power systems and industrial energy hubs , 2021, Applied Energy.

[20]  Lingfeng Wang,et al.  A robust optimization approach for optimal load dispatch of community energy hub , 2020 .

[21]  Yingzhong Gu,et al.  Stochastic Look-Ahead Economic Dispatch With Variable Generation Resources , 2017, IEEE Transactions on Power Systems.

[22]  Nima Amjady,et al.  Optimal operation strategy for multi-carrier energy systems including various energy converters by multi-objective information gap decision theory and enhanced directed search domain method , 2019, Energy Conversion and Management.

[23]  Behnam Mohammadi-Ivatloo,et al.  Look-ahead risk-constrained scheduling of wind power integrated system with compressed air energy storage (CAES) plant , 2018, Energy.

[24]  Hossein Ahmadisedigh,et al.  Combined heating and cooling networks with waste heat recovery based on energy hub concept , 2019, Applied Energy.

[25]  Elaheh Mashhour,et al.  A comprehensive model for self-scheduling an energy hub to supply cooling, heating and electrical demands of a building , 2016 .

[26]  S. S. Mortazavi,et al.  Stochastic effects of ice storage on improvement of an energy hub optimal operation including demand response and renewable energies , 2020 .

[27]  Noradin Ghadimi,et al.  Multi-objective energy management in a micro-grid , 2018, Energy Reports.

[28]  Qie Sun,et al.  The impact of electric vehicle penetration and charging patterns on the management of energy hub – A multi-agent system simulation , 2018, Applied Energy.

[29]  Thomas X. Wu,et al.  Standardised modelling and optimisation of a system of interconnected energy hubs considering multiple energies—Electricity, gas, heating, and cooling , 2020 .

[30]  Qing Lu,et al.  Optimal household energy management based on smart residential energy hub considering uncertain behaviors , 2020 .

[31]  Wei Wang,et al.  Electricity load forecasting by an improved forecast engine for building level consumers , 2017 .

[32]  Enrico Fabrizio,et al.  A model to design and optimize multi-energy systems in buildings at the design concept stage , 2010 .

[33]  David C. Yu,et al.  Optimal sizing of hybrid PV/diesel/battery in ship power system ☆ , 2015 .

[34]  G. Andersson,et al.  Optimal Power Flow of Multiple Energy Carriers , 2007, IEEE Transactions on Power Systems.

[35]  Mehdi Abapour,et al.  Robust scheduling of hydrogen based smart micro energy hub with integrated demand response , 2020 .

[36]  Mark Z. Jacobson,et al.  Optimal operational strategy for an offgrid hybrid hydrogen/electricity refueling station powered by solar photovoltaics , 2020 .

[37]  Albert Moser,et al.  Uncertainty modeling in optimal operation of energy hub in presence of wind, storage and demand response , 2014 .

[38]  Pengcheng You,et al.  Distributed planning of electricity and natural gas networks and energy hubs , 2021 .

[39]  Daniel S. Kirschen,et al.  Look-Ahead Bidding Strategy for Energy Storage , 2017, IEEE Transactions on Sustainable Energy.

[40]  Hoay Beng Gooi,et al.  Micro-generation dispatch in a smart residential multi-carrier energy system considering demand forecast error , 2016 .

[41]  Mehdi Abapour,et al.  Risk-based scheduling strategy for electric vehicle aggregator using hybrid Stochastic/IGDT approach , 2020 .

[42]  Miadreza Shafie-khah,et al.  Adjustable robust optimization approach for two-stage operation of energy hub-based microgrids , 2021 .

[43]  Sarah Busche,et al.  Power systems balancing with high penetration renewables: The potential of demand response in Hawaii , 2013 .

[44]  Javier Contreras,et al.  A Stochastic Bilevel Model for the Energy Hub Manager Problem , 2017, IEEE Transactions on Smart Grid.

[45]  Na Luo,et al.  Data analytics and optimization of an ice-based energy storage system for commercial buildings , 2017 .

[46]  Kankar Bhattacharya,et al.  Optimal design of electric vehicle charging stations considering various energy resources , 2017 .

[47]  Yi Wang,et al.  Mixed-integer linear programming-based optimal configuration planning for energy hub: Starting from scratch , 2018 .

[48]  Mohammad Reza Mohammadi,et al.  Optimal management of energy hubs and smart energy hubs – A review , 2018, Renewable and Sustainable Energy Reviews.

[49]  Fangcheng He,et al.  Multi-objective problem based operation and emission cots for heat and power hub model through peak load management in large scale users , 2018, Energy Conversion and Management.

[50]  Zhao Yang Dong,et al.  Optimal operation of DES/CCHP based regional multi-energy prosumer with demand response , 2016 .

[51]  M. Hosseini-Firouz Optimal offering strategy considering the risk management for wind power producers in electricity market , 2013 .

[52]  G. Andersson,et al.  Energy hubs for the future , 2007, IEEE Power and Energy Magazine.

[53]  Filip Johnsson,et al.  Tailoring large-scale electricity production from variable renewable energy sources to accommodate baseload generation in europe , 2018, Renewable Energy.