IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v162y2016icp1074-1088.html
   My bibliography  Save this article

A multi-objective model for the day-ahead energy resource scheduling of a smart grid with high penetration of sensitive loads

Author

Listed:
  • Soares, João
  • Fotouhi Ghazvini, Mohammad Ali
  • Vale, Zita
  • de Moura Oliveira, P.B.

Abstract

In this paper, a multi-objective framework is proposed for the daily operation of a Smart Grid (SG) with high penetration of sensitive loads. The Virtual Power Player (VPP) manages the day-ahead energy resource scheduling in the smart grid, considering the intensive use of Distributed Generation (DG) and Vehicle-To-Grid (V2G), while maintaining a highly reliable power for the sensitive loads. This work considers high penetration of sensitive loads, i.e. loads such as some industrial processes that require high power quality, high reliability and few interruptions. The weighted-sum approach is used with the distributed and parallel computing techniques to efficiently solve the multi-objective problem. A two-stage optimization method is proposed using a Particle Swarm Optimization (PSO) and a deterministic technique based on Mixed-Integer Linear Programming (MILP). A realistic mathematical formulation considering the electric network constraints for the day-ahead scheduling model is described. The execution time of the large-scale problem can be reduced by using a parallel and distributed computing platform. A Pareto front algorithm is applied to determine the set of non-dominated solutions. The maximization of the minimum available reserve is incorporated in the mathematical formulation in addition to the cost minimization, to take into account the reliability requirements of sensitive and vulnerable loads. A case study with a 180-bus distribution network and a fleet of 1000 gridable Electric Vehicles (EVs) is used to illustrate the performance of the proposed method. The execution time to solve the optimization problem is reduced by using distributed computing.

Suggested Citation

  • Soares, João & Fotouhi Ghazvini, Mohammad Ali & Vale, Zita & de Moura Oliveira, P.B., 2016. "A multi-objective model for the day-ahead energy resource scheduling of a smart grid with high penetration of sensitive loads," Applied Energy, Elsevier, vol. 162(C), pages 1074-1088.
    • Handle: RePEc:eee:appene:v:162:y:2016:i:c:p:1074-1088
    DOI: 10.1016/j.apenergy.2015.10.181
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261915014312
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2015.10.181?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Niknam, Taher & Azizipanah-Abarghooee, Rasoul & Narimani, Mohammad Rasoul, 2012. "An efficient scenario-based stochastic programming framework for multi-objective optimal micro-grid operation," Applied Energy, Elsevier, vol. 99(C), pages 455-470.
    2. Blumsack, Seth & Fernandez, Alisha, 2012. "Ready or not, here comes the smart grid!," Energy, Elsevier, vol. 37(1), pages 61-68.
    3. Pavić, Ivan & Capuder, Tomislav & Kuzle, Igor, 2015. "Value of flexible electric vehicles in providing spinning reserve services," Applied Energy, Elsevier, vol. 157(C), pages 60-74.
    4. Fotouhi Ghazvini, M.A. & Morais, Hugo & Vale, Zita, 2012. "Coordination between mid-term maintenance outage decisions and short-term security-constrained scheduling in smart distribution systems," Applied Energy, Elsevier, vol. 96(C), pages 281-291.
    5. Dufo-López, Rodolfo & Bernal-Agustín, José L. & Yusta-Loyo, José M. & Domínguez-Navarro, José A. & Ramírez-Rosado, Ignacio J. & Lujano, Juan & Aso, Ismael, 2011. "Multi-objective optimization minimizing cost and life cycle emissions of stand-alone PV–wind–diesel systems with batteries storage," Applied Energy, Elsevier, vol. 88(11), pages 4033-4041.
    6. Aghaei, Jamshid & Alizadeh, Mohammad-Iman, 2013. "Multi-objective self-scheduling of CHP (combined heat and power)-based microgrids considering demand response programs and ESSs (energy storage systems)," Energy, Elsevier, vol. 55(C), pages 1044-1054.
    7. Osório, G.J. & Rodrigues, E.M.G. & Lujano-Rojas, J.M. & Matias, J.C.O. & Catalão, J.P.S., 2015. "New control strategy for the weekly scheduling of insular power systems with a battery energy storage system," Applied Energy, Elsevier, vol. 154(C), pages 459-470.
    8. Canizes, Bruno & Soares, João & Vale, Zita & Khodr, H.M., 2012. "Hybrid fuzzy Monte Carlo technique for reliability assessment in transmission power systems," Energy, Elsevier, vol. 45(1), pages 1007-1017.
    9. Korkas, Christos D. & Baldi, Simone & Michailidis, Iakovos & Kosmatopoulos, Elias B., 2015. "Intelligent energy and thermal comfort management in grid-connected microgrids with heterogeneous occupancy schedule," Applied Energy, Elsevier, vol. 149(C), pages 194-203.
    10. Soares, J. & Silva, M. & Sousa, T. & Vale, Z. & Morais, H., 2012. "Distributed energy resource short-term scheduling using Signaled Particle Swarm Optimization," Energy, Elsevier, vol. 42(1), pages 466-476.
    11. Motevasel, Mehdi & Seifi, Ali Reza & Niknam, Taher, 2013. "Multi-objective energy management of CHP (combined heat and power)-based micro-grid," Energy, Elsevier, vol. 51(C), pages 123-136.
    12. João Soares & Bruno Canizes & Cristina Lobo & Zita Vale & Hugo Morais, 2012. "Electric Vehicle Scenario Simulator Tool for Smart Grid Operators," Energies, MDPI, vol. 5(6), pages 1-19, June.
    13. Alanne, Kari & Saari, Arto, 2006. "Distributed energy generation and sustainable development," Renewable and Sustainable Energy Reviews, Elsevier, vol. 10(6), pages 539-558, December.
    14. Sousa, Tiago & Morais, Hugo & Soares, João & Vale, Zita, 2012. "Day-ahead resource scheduling in smart grids considering Vehicle-to-Grid and network constraints," Applied Energy, Elsevier, vol. 96(C), pages 183-193.
    15. Wissner, Matthias, 2011. "The Smart Grid - A saucerful of secrets?," Applied Energy, Elsevier, vol. 88(7), pages 2509-2518, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Niloofar Ghanbari & Hossein Mokhtari & Subhashish Bhattacharya, 2018. "Optimizing Operation Indices Considering Different Types of Distributed Generation in Microgrid Applications," Energies, MDPI, vol. 11(4), pages 1-12, April.
    2. Mohammad Mohammadi Roozbehani & Ehsan Heydarian-Forushani & Saeed Hasanzadeh & Seifeddine Ben Elghali, 2022. "Virtual Power Plant Operational Strategies: Models, Markets, Optimization, Challenges, and Opportunities," Sustainability, MDPI, vol. 14(19), pages 1-23, September.
    3. Geng, Zhaowei & Conejo, Antonio J. & Chen, Qixin & Xia, Qing & Kang, Chongqing, 2017. "Electricity production scheduling under uncertainty: Max social welfare vs. min emission vs. max renewable production," Applied Energy, Elsevier, vol. 193(C), pages 540-549.
    4. Rahmani-Dabbagh, Saeed & Sheikh-El-Eslami, Mohammad Kazem, 2016. "A profit sharing scheme for distributed energy resources integrated into a virtual power plant," Applied Energy, Elsevier, vol. 184(C), pages 313-328.
    5. Kumar, K. Prakash & Saravanan, B., 2017. "Recent techniques to model uncertainties in power generation from renewable energy sources and loads in microgrids – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 71(C), pages 348-358.
    6. Shanmugarajah Vinothine & Lidula N. Widanagama Arachchige & Athula D. Rajapakse & Roshani Kaluthanthrige, 2022. "Microgrid Energy Management and Methods for Managing Forecast Uncertainties," Energies, MDPI, vol. 15(22), pages 1-22, November.
    7. Solanke, Tirupati U. & Khatua, Pradeep K. & Ramachandaramurthy, Vigna K. & Yong, Jia Ying & Tan, Kang Miao, 2021. "Control and management of a multilevel electric vehicles infrastructure integrated with distributed resources: A comprehensive review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 144(C).
    8. Ba Hung, Nguyen & Jaewon, Sung & Lim, Ocktaeck, 2017. "A study of the effects of input parameters on the dynamics and required power of an electric bicycle," Applied Energy, Elsevier, vol. 204(C), pages 1347-1362.
    9. Motalleb, Mahdi & Thornton, Matsu & Reihani, Ehsan & Ghorbani, Reza, 2016. "A nascent market for contingency reserve services using demand response," Applied Energy, Elsevier, vol. 179(C), pages 985-995.
    10. Javidsharifi, Mahshid & Niknam, Taher & Aghaei, Jamshid & Mokryani, Geev, 2018. "Multi-objective short-term scheduling of a renewable-based microgrid in the presence of tidal resources and storage devices," Applied Energy, Elsevier, vol. 216(C), pages 367-381.
    11. Asaad Mohammad & Ramon Zamora & Tek Tjing Lie, 2020. "Integration of Electric Vehicles in the Distribution Network: A Review of PV Based Electric Vehicle Modelling," Energies, MDPI, vol. 13(17), pages 1-20, September.
    12. Zheng, Yanchong & Shang, Yitong & Shao, Ziyun & Jian, Linni, 2018. "A novel real-time scheduling strategy with near-linear complexity for integrating large-scale electric vehicles into smart grid," Applied Energy, Elsevier, vol. 217(C), pages 1-13.
    13. Lucrezia Manservigi & Mattia Cattozzo & Pier Ruggero Spina & Mauro Venturini & Hilal Bahlawan, 2020. "Optimal Management of the Energy Flows of Interconnected Residential Users," Energies, MDPI, vol. 13(6), pages 1-21, March.
    14. João Soares & Nuno Borges & Zita Vale & P.B. De Moura Oliveira, 2016. "Enhanced Multi-Objective Energy Optimization by a Signaling Method," Energies, MDPI, vol. 9(10), pages 1-23, October.
    15. Yan, Jie & Menghwar, Mohan & Asghar, Ehtisham & Kumar Panjwani, Manoj & Liu, Yongqian, 2019. "Real-time energy management for a smart-community microgrid with battery swapping and renewables," Applied Energy, Elsevier, vol. 238(C), pages 180-194.
    16. Leszczyński, Jacek S. & Gryboś, Dominik & Markowski, Jan, 2023. "Analysis of optimal expansion dynamics in a reciprocating drive for a micro-CAES production system," Applied Energy, Elsevier, vol. 350(C).
    17. Wagner, Lukas Peter & Reinpold, Lasse Matthias & Kilthau, Maximilian & Fay, Alexander, 2023. "A systematic review of modeling approaches for flexible energy resources," Renewable and Sustainable Energy Reviews, Elsevier, vol. 184(C).
    18. Terlouw, Tom & AlSkaif, Tarek & Bauer, Christian & van Sark, Wilfried, 2019. "Multi-objective optimization of energy arbitrage in community energy storage systems using different battery technologies," Applied Energy, Elsevier, vol. 239(C), pages 356-372.
    19. Ju, Liwei & Zhao, Rui & Tan, Qinliang & Lu, Yan & Tan, Qingkun & Wang, Wei, 2019. "A multi-objective robust scheduling model and solution algorithm for a novel virtual power plant connected with power-to-gas and gas storage tank considering uncertainty and demand response," Applied Energy, Elsevier, vol. 250(C), pages 1336-1355.
    20. Chou, Jui-Sheng & Ngo, Ngoc-Tri, 2016. "Time series analytics using sliding window metaheuristic optimization-based machine learning system for identifying building energy consumption patterns," Applied Energy, Elsevier, vol. 177(C), pages 751-770.
    21. Li, Pei-Hao & Pye, Steve, 2018. "Assessing the benefits of demand-side flexibility in residential and transport sectors from an integrated energy systems perspective," Applied Energy, Elsevier, vol. 228(C), pages 965-979.
    22. Perera, A.T.D. & Nik, Vahid M. & Mauree, Dasaraden & Scartezzini, Jean-Louis, 2017. "Electrical hubs: An effective way to integrate non-dispatchable renewable energy sources with minimum impact to the grid," Applied Energy, Elsevier, vol. 190(C), pages 232-248.
    23. Muqaddas Naz & Zafar Iqbal & Nadeem Javaid & Zahoor Ali Khan & Wadood Abdul & Ahmad Almogren & Atif Alamri, 2018. "Efficient Power Scheduling in Smart Homes Using Hybrid Grey Wolf Differential Evolution Optimization Technique with Real Time and Critical Peak Pricing Schemes," Energies, MDPI, vol. 11(2), pages 1-25, February.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. João Soares & Nuno Borges & Zita Vale & P.B. De Moura Oliveira, 2016. "Enhanced Multi-Objective Energy Optimization by a Signaling Method," Energies, MDPI, vol. 9(10), pages 1-23, October.
    2. Javidsharifi, Mahshid & Niknam, Taher & Aghaei, Jamshid & Mokryani, Geev, 2018. "Multi-objective short-term scheduling of a renewable-based microgrid in the presence of tidal resources and storage devices," Applied Energy, Elsevier, vol. 216(C), pages 367-381.
    3. Fontenot, Hannah & Dong, Bing, 2019. "Modeling and control of building-integrated microgrids for optimal energy management – A review," Applied Energy, Elsevier, vol. 254(C).
    4. Sousa, Tiago & Vale, Zita & Carvalho, Joao Paulo & Pinto, Tiago & Morais, Hugo, 2014. "A hybrid simulated annealing approach to handle energy resource management considering an intensive use of electric vehicles," Energy, Elsevier, vol. 67(C), pages 81-96.
    5. Chen, Yizhong & He, Li & Li, Jing, 2017. "Stochastic dominant-subordinate-interactive scheduling optimization for interconnected microgrids with considering wind-photovoltaic-based distributed generations under uncertainty," Energy, Elsevier, vol. 130(C), pages 581-598.
    6. Izadbakhsh, Maziar & Gandomkar, Majid & Rezvani, Alireza & Ahmadi, Abdollah, 2015. "Short-term resource scheduling of a renewable energy based micro grid," Renewable Energy, Elsevier, vol. 75(C), pages 598-606.
    7. Syed Ali Abbas Kazmi & Muhammad Khuram Shahzad & Akif Zia Khan & Dong Ryeol Shin, 2017. "Smart Distribution Networks: A Review of Modern Distribution Concepts from a Planning Perspective," Energies, MDPI, vol. 10(4), pages 1-47, April.
    8. Deihimi, Ali & Keshavarz Zahed, Babak & Iravani, Reza, 2016. "An interactive operation management of a micro-grid with multiple distributed generations using multi-objective uniform water cycle algorithm," Energy, Elsevier, vol. 106(C), pages 482-509.
    9. Nosratabadi, Seyyed Mostafa & Hooshmand, Rahmat-Allah & Gholipour, Eskandar, 2017. "A comprehensive review on microgrid and virtual power plant concepts employed for distributed energy resources scheduling in power systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 341-363.
    10. Funcke, Simon & Bauknecht, Dierk, 2016. "Typology of centralised and decentralised visions for electricity infrastructure," Utilities Policy, Elsevier, vol. 40(C), pages 67-74.
    11. Kovacic, Zora & Giampietro, Mario, 2015. "Empty promises or promising futures? The case of smart grids," Energy, Elsevier, vol. 93(P1), pages 67-74.
    12. Li, Xiao Hui & Hong, Seung Ho, 2014. "User-expected price-based demand response algorithm for a home-to-grid system," Energy, Elsevier, vol. 64(C), pages 437-449.
    13. Weitzel, Timm & Glock, Christoph H., 2018. "Energy management for stationary electric energy storage systems: A systematic literature review," European Journal of Operational Research, Elsevier, vol. 264(2), pages 582-606.
    14. Gruber, J.K. & Huerta, F. & Matatagui, P. & Prodanović, M., 2015. "Advanced building energy management based on a two-stage receding horizon optimization," Applied Energy, Elsevier, vol. 160(C), pages 194-205.
    15. Zhao, Bo & Zhang, Xuesong & Li, Peng & Wang, Ke & Xue, Meidong & Wang, Caisheng, 2014. "Optimal sizing, operating strategy and operational experience of a stand-alone microgrid on Dongfushan Island," Applied Energy, Elsevier, vol. 113(C), pages 1656-1666.
    16. de la Hoz, Jordi & Martín, Helena & Alonso, Alex & Carolina Luna, Adriana & Matas, José & Vasquez, Juan C. & Guerrero, Josep M., 2019. "Regulatory-framework-embedded energy management system for microgrids: The case study of the Spanish self-consumption scheme," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    17. Pavić, Ivan & Capuder, Tomislav & Kuzle, Igor, 2016. "Low carbon technologies as providers of operational flexibility in future power systems," Applied Energy, Elsevier, vol. 168(C), pages 724-738.
    18. Kanevce, Aleksandra & Mishkovski, Igor & Kocarev, Ljupco, 2013. "Modeling long-term dynamical evolution of Southeast European power transmission system," Energy, Elsevier, vol. 57(C), pages 116-124.
    19. Wouters, Carmen & Fraga, Eric S. & James, Adrian M., 2015. "An energy integrated, multi-microgrid, MILP (mixed-integer linear programming) approach for residential distributed energy system planning – A South Australian case-study," Energy, Elsevier, vol. 85(C), pages 30-44.
    20. Wu, Qiong & Ren, Hongbo & Gao, Weijun & Ren, Jianxing & Lao, Changshi, 2017. "Profit allocation analysis among the distributed energy network participants based on Game-theory," Energy, Elsevier, vol. 118(C), pages 783-794.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:appene:v:162:y:2016:i:c:p:1074-1088. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.