IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v238y2019icp627-642.html
   My bibliography  Save this article

Smart energy management algorithm for load smoothing and peak shaving based on load forecasting of an island’s power system

Author

Listed:
  • Chapaloglou, Spyridon
  • Nesiadis, Athanasios
  • Iliadis, Petros
  • Atsonios, Konstantinos
  • Nikolopoulos, Nikos
  • Grammelis, Panagiotis
  • Yiakopoulos, Christos
  • Antoniadis, Ioannis
  • Kakaras, Emmanuel

Abstract

In this study, a novel algorithm for the management of the power flows of an islanded power system was developed, capable of simultaneously achieving steadier conventional unit operation and shaving the demand peak values, for the days of the year that present a night peak in their load curve. The under investigation system is composed of Diesel Generators, a PV farm and a Battery Energy Storage System (BESS) with the power system’s consumption to be relatively higher than its RES production. The proposed algorithm combines the use of a load forecasting methodology, a pattern recognition procedure and a custom optimal power flow scheduling algorithm. The prediction module was based on a feedforward artificial neural network, capable of short-term day ahead load forecasting. The forecasted day ahead load profile was then used as an input to the developed pattern recognition algorithm, in order to be classified based on its load curve shape (pattern). Subsequently, in case that the classification resulted in a clear night peak pattern, it was possible to estimate an hourly based trajectory for the diesel generators operation and derive the BESS charging setpoints, which result in the desired peak shaving and smoothing level simultaneously. In this way, it is possible to replace or substitute the highest power demand with stored renewable energy and to operate the diesel engines as steady as possible, diminishing the ramp up and the steep gradients before the night hours’ peak. The algorithm was integrated in the overall system model in APROS software, where dynamic simulations were performed. The simulation results proved that by applying the proposed algorithm, a combined effect of smoother diesel generator operation and peak shaving with renewable energy is achievable even with the absence of PV overproduction, diminishing the variability of the load to be covered from the conventional units. Such an operation aims at enabling diesel engines to be rated at a lower, than currently, maximum capacity while increasing the share of the renewable energy penetration into the grid.

Suggested Citation

  • Chapaloglou, Spyridon & Nesiadis, Athanasios & Iliadis, Petros & Atsonios, Konstantinos & Nikolopoulos, Nikos & Grammelis, Panagiotis & Yiakopoulos, Christos & Antoniadis, Ioannis & Kakaras, Emmanuel, 2019. "Smart energy management algorithm for load smoothing and peak shaving based on load forecasting of an island’s power system," Applied Energy, Elsevier, vol. 238(C), pages 627-642.
    • Handle: RePEc:eee:appene:v:238:y:2019:i:c:p:627-642
    DOI: 10.1016/j.apenergy.2019.01.102
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261919301035
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2019.01.102?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. Das, Utpal Kumar & Tey, Kok Soon & Seyedmahmoudian, Mehdi & Mekhilef, Saad & Idris, Moh Yamani Idna & Van Deventer, Willem & Horan, Bend & Stojcevski, Alex, 2018. "Forecasting of photovoltaic power generation and model optimization: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 912-928.
    2. Hahn, Heiko & Meyer-Nieberg, Silja & Pickl, Stefan, 2009. "Electric load forecasting methods: Tools for decision making," European Journal of Operational Research, Elsevier, vol. 199(3), pages 902-907, December.
    3. Hu, Jiefeng & Xu, Yinliang & Cheng, Ka Wai & Guerrero, Josep M., 2018. "A model predictive control strategy of PV-Battery microgrid under variable power generations and load conditions," Applied Energy, Elsevier, vol. 221(C), pages 195-203.
    4. Sepasi, Saeed & Reihani, Ehsan & Howlader, Abdul M. & Roose, Leon R. & Matsuura, Marc M., 2017. "Very short term load forecasting of a distribution system with high PV penetration," Renewable Energy, Elsevier, vol. 106(C), pages 142-148.
    5. Arcos-Aviles, Diego & Pascual, Julio & Guinjoan, Francesc & Marroyo, Luis & Sanchis, Pablo & Marietta, Martin P., 2017. "Low complexity energy management strategy for grid profile smoothing of a residential grid-connected microgrid using generation and demand forecasting," Applied Energy, Elsevier, vol. 205(C), pages 69-84.
    6. Reihani, Ehsan & Motalleb, Mahdi & Ghorbani, Reza & Saad Saoud, Lyes, 2016. "Load peak shaving and power smoothing of a distribution grid with high renewable energy penetration," Renewable Energy, Elsevier, vol. 86(C), pages 1372-1379.
    7. Moral-Carcedo, Julián & Pérez-García, Julián, 2017. "Integrating long-term economic scenarios into peak load forecasting: An application to Spain," Energy, Elsevier, vol. 140(P1), pages 682-695.
    8. Mazzola, Simone & Vergara, Claudio & Astolfi, Marco & Li, Vivian & Perez-Arriaga, Ignacio & Macchi, Ennio, 2017. "Assessing the value of forecast-based dispatch in the operation of off-grid rural microgrids," Renewable Energy, Elsevier, vol. 108(C), pages 116-125.
    9. Chua, Kein Huat & Lim, Yun Seng & Morris, Stella, 2017. "A novel fuzzy control algorithm for reducing the peak demands using energy storage system," Energy, Elsevier, vol. 122(C), pages 265-273.
    10. Jaeyeong Yoo & Byungsung Park & Kyungsung An & Essam A. Al-Ammar & Yasin Khan & Kyeon Hur & Jong Hyun Kim, 2012. "Look-Ahead Energy Management of a Grid-Connected Residential PV System with Energy Storage under Time-Based Rate Programs," Energies, MDPI, vol. 5(4), pages 1-19, April.
    11. Zhao, Bo & Chen, Jian & Zhang, Leiqi & Zhang, Xuesong & Qin, Ruwen & Lin, Xiangning, 2018. "Three representative island microgrids in the East China Sea: Key technologies and experiences," Renewable and Sustainable Energy Reviews, Elsevier, vol. 96(C), pages 262-274.
    12. Pfenninger, Stefan & Staffell, Iain, 2016. "Long-term patterns of European PV output using 30 years of validated hourly reanalysis and satellite data," Energy, Elsevier, vol. 114(C), pages 1251-1265.
    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. Cho, Yongjun & Lee, Eunjung & Baek, Keon & Kim, Jinho, 2023. "Stochastic Optimization-Based hosting capacity estimation with volatile net load deviation in distribution grids," Applied Energy, Elsevier, vol. 341(C).
    2. Yunbo Yang & Rongling Li & Tao Huang, 2020. "Smart Meter Data Analysis of a Building Cluster for Heating Load Profile Quantification and Peak Load Shifting," Energies, MDPI, vol. 13(17), pages 1-20, August.
    3. Sooyoung Jung & Yong Tae Yoon & Jun-Ho Huh, 2020. "An Efficient Micro Grid Optimization Theory," Mathematics, MDPI, vol. 8(4), pages 1-21, April.
    4. Uddin, Moslem & Romlie, M.F. & Abdullah, M.F. & Tan, ChiaKwang & Shafiullah, GM & Bakar, A.H.A., 2020. "A novel peak shaving algorithm for islanded microgrid using battery energy storage system," Energy, Elsevier, vol. 196(C).
    5. Sachajdak, Andrzej & Lappalainen, Jari & Mikkonen, Hannu, 2019. "Dynamic simulation in development of contemporary energy systems – oxy combustion case study," Energy, Elsevier, vol. 181(C), pages 964-973.
    6. Mawson, Victoria Jayne & Hughes, Ben Richard, 2021. "Optimisation of HVAC control and manufacturing schedules for the reduction of peak energy demand in the manufacturing sector," Energy, Elsevier, vol. 227(C).
    7. Yan, Zhe & Zhang, Yongming & Liang, Runqi & Jin, Wenrui, 2020. "An allocative method of hybrid electrical and thermal energy storage capacity for load shifting based on seasonal difference in district energy planning," Energy, Elsevier, vol. 207(C).
    8. Talaat, M. & Hatata, A.Y. & Alsayyari, Abdulaziz S. & Alblawi, Adel, 2020. "A smart load management system based on the grasshopper optimization algorithm using the under-frequency load shedding approach," Energy, Elsevier, vol. 190(C).
    9. Benalcazar, Pablo & Kalka, Maciej & Kamiński, Jacek, 2024. "From consumer to prosumer: A model-based analysis of costs and benefits of grid-connected residential PV-battery systems," Energy Policy, Elsevier, vol. 191(C).
    10. Ibrahim Alotaibi & Mohammed A. Abido & Muhammad Khalid & Andrey V. Savkin, 2020. "A Comprehensive Review of Recent Advances in Smart Grids: A Sustainable Future with Renewable Energy Resources," Energies, MDPI, vol. 13(23), pages 1-41, November.
    11. Wang, Bangyan & Wang, Xifan & Wang, Zhiwei & Wei, Chengxiao & Zhang, Xiao-Ping & Zhou, Mo & Gao, Jiawen & Han, Zhentao, 2024. "A four-stage fast reliability assessment framework for renewables-dominated strong power systems with large-scale energy storage by temporal decoupling and contingencies filtering," Applied Energy, Elsevier, vol. 362(C).
    12. Daiva Stanelyte & Virginijus Radziukynas, 2019. "Review of Voltage and Reactive Power Control Algorithms in Electrical Distribution Networks," Energies, MDPI, vol. 13(1), pages 1-26, December.
    13. Lange, Christopher & Rueß, Alexandra & Nuß, Andreas & Öchsner, Richard & März, Martin, 2020. "Dimensioning battery energy storage systems for peak shaving based on a real-time control algorithm," Applied Energy, Elsevier, vol. 280(C).
    14. Velaz-Acera, Néstor & Álvarez-García, Javier & Borge-Diez, David, 2023. "Economic and emission reduction benefits of the implementation of eVTOL aircraft with bi-directional flow as storage systems in islands and case study for Canary Islands," Applied Energy, Elsevier, vol. 331(C).
    15. Xianfei Yang & Xiang Yu & Hui Lu, 2020. "Dual possibilistic regression models of support vector machines and application in power load forecasting," International Journal of Distributed Sensor Networks, , vol. 16(5), pages 15501477209, May.
    16. Hossein Shokouhinejad & Eduardo Castillo Guerra, 2024. "Self-Scheduling Virtual Power Plant for Peak Management," Energies, MDPI, vol. 17(11), pages 1-20, June.
    17. Rubasinghe, Osaka & Zhang, Tingze & Zhang, Xinan & Choi, San Shing & Chau, Tat Kei & Chow, Yau & Fernando, Tyrone & Iu, Herbert Ho-Ching, 2023. "Highly accurate peak and valley prediction short-term net load forecasting approach based on decomposition for power systems with high PV penetration," Applied Energy, Elsevier, vol. 333(C).
    18. Ebrahimi, Armin & Ziabasharhagh, Masoud, 2022. "Introducing a novel control algorithm and scheduling procedure for optimal operation of energy storage systems," Energy, Elsevier, vol. 252(C).
    19. Kucevic, Daniel & Englberger, Stefan & Sharma, Anurag & Trivedi, Anupam & Tepe, Benedikt & Schachler, Birgit & Hesse, Holger & Srinivasan, Dipti & Jossen, Andreas, 2021. "Reducing grid peak load through the coordinated control of battery energy storage systems located at electric vehicle charging parks," Applied Energy, Elsevier, vol. 295(C).
    20. Erick Alves & Santiago Sanchez & Danilo Brandao & Elisabetta Tedeschi, 2019. "Smart Load Management with Energy Storage for Power Quality Enhancement in Wind-Powered Oil and Gas Applications," Energies, MDPI, vol. 12(15), pages 1-15, August.
    21. Nieta, Agustín A. Sánchez de la & Ilieva, Iliana & Gibescu, Madeleine & Bremdal, Bernt & Simonsen, Stig & Gramme, Eivind, 2021. "Optimal midterm peak shaving cost in an electricity management system using behind customers’ smart meter configuration," Applied Energy, Elsevier, vol. 283(C).
    22. Golmohamadi, Hessam, 2022. "Demand-side management in industrial sector: A review of heavy industries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 156(C).
    23. Qin, Peijia & Tan, Xianlin & Huang, Youbin & Pan, Mingming & Ouyang, Tiancheng, 2023. "Two-stage robust optimal scheduling framework applied for microgrids: Combined energy recovery and forecast," Renewable Energy, Elsevier, vol. 214(C), pages 290-306.

    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. Gui, Yonghao & Wei, Baoze & Li, Mingshen & Guerrero, Josep M. & Vasquez, Juan C., 2018. "Passivity-based coordinated control for islanded AC microgrid," Applied Energy, Elsevier, vol. 229(C), pages 551-561.
    2. Hau, Lee Cheun & Lim, Yun Seng & Liew, Serena Miao San, 2020. "A novel spontaneous self-adjusting controller of energy storage system for maximum demand reductions under penetration of photovoltaic system," Applied Energy, Elsevier, vol. 260(C).
    3. Lange, Christopher & Rueß, Alexandra & Nuß, Andreas & Öchsner, Richard & März, Martin, 2020. "Dimensioning battery energy storage systems for peak shaving based on a real-time control algorithm," Applied Energy, Elsevier, vol. 280(C).
    4. Huxley, O.T. & Taylor, J. & Everard, A. & Briggs, J. & Tilley, K. & Harwood, J. & Buckley, A., 2022. "The uncertainties involved in measuring national solar photovoltaic electricity generation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 156(C).
    5. Md Masud Rana & Mohamed Atef & Md Rasel Sarkar & Moslem Uddin & GM Shafiullah, 2022. "A Review on Peak Load Shaving in Microgrid—Potential Benefits, Challenges, and Future Trend," Energies, MDPI, vol. 15(6), pages 1-17, March.
    6. Semmelmann, Leo & Hertel, Matthias & Kircher, Kevin J. & Mikut, Ralf & Hagenmeyer, Veit & Weinhardt, Christof, 2024. "The impact of heat pumps on day-ahead energy community load forecasting," Applied Energy, Elsevier, vol. 368(C).
    7. Shen, Xiaojun & Wei, Hongyang & Wei, Li, 2020. "Study of trackside photovoltaic power integration into the traction power system of suburban elevated urban rail transit line," Applied Energy, Elsevier, vol. 260(C).
    8. Ahn, Hyeunguk, 2024. "A framework for developing data-driven correction factors for solar PV systems," Energy, Elsevier, vol. 290(C).
    9. Ng, Rong Wang & Begam, K.M. & Rajkumar, Rajprasad Kumar & Wong, Yee Wan & Chong, Lee Wai, 2022. "A novel dynamic two-stage controller of battery energy storage system for maximum demand reductions," Energy, Elsevier, vol. 248(C).
    10. Rafal Dzikowski, 2020. "DSO–TSO Coordination of Day-Ahead Operation Planning with the Use of Distributed Energy Resources," Energies, MDPI, vol. 13(14), pages 1-25, July.
    11. Luca Massidda & Marino Marrocu, 2017. "Decoupling Weather Influence from User Habits for an Optimal Electric Load Forecast System," Energies, MDPI, vol. 10(12), pages 1-16, December.
    12. Langenmayr, Uwe & Wang, Weimin & Jochem, Patrick, 2020. "Unit commitment of photovoltaic-battery systems: An advanced approach considering uncertainties from load, electric vehicles, and photovoltaic," Applied Energy, Elsevier, vol. 280(C).
    13. Bhagya Nathali Silva & Murad Khan & Kijun Han, 2020. "Futuristic Sustainable Energy Management in Smart Environments: A Review of Peak Load Shaving and Demand Response Strategies, Challenges, and Opportunities," Sustainability, MDPI, vol. 12(14), pages 1-23, July.
    14. Robert Bauer & Dominik Schopf & Grégoire Klaus & Raimund Brotsack & Javier Valdes, 2022. "Energy Cell Simulation for Sector Coupling with Power-to-Methane: A Case Study in Lower Bavaria," Energies, MDPI, vol. 15(7), pages 1-22, April.
    15. Yamashita, Daniela Yassuda & Vechiu, Ionel & Gaubert, Jean-Paul, 2020. "A review of hierarchical control for building microgrids," Renewable and Sustainable Energy Reviews, Elsevier, vol. 118(C).
    16. Li, Yanxue & Gao, Weijun & Ruan, Yingjun, 2018. "Performance investigation of grid-connected residential PV-battery system focusing on enhancing self-consumption and peak shaving in Kyushu, Japan," Renewable Energy, Elsevier, vol. 127(C), pages 514-523.
    17. Uddin, Moslem & Romlie, Mohd Fakhizan & Abdullah, Mohd Faris & Abd Halim, Syahirah & Abu Bakar, Ab Halim & Chia Kwang, Tan, 2018. "A review on peak load shaving strategies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 3323-3332.
    18. Agüera-Pérez, Agustín & Palomares-Salas, José Carlos & González de la Rosa, Juan José & Florencias-Oliveros, Olivia, 2018. "Weather forecasts for microgrid energy management: Review, discussion and recommendations," Applied Energy, Elsevier, vol. 228(C), pages 265-278.
    19. de Guibert, Paul & Shirizadeh, Behrang & Quirion, Philippe, 2020. "Variable time-step: A method for improving computational tractability for energy system models with long-term storage," Energy, Elsevier, vol. 213(C).
    20. Plain, N. & Hingray, B. & Mathy, S., 2019. "Accounting for low solar resource days to size 100% solar microgrids power systems in Africa," Renewable Energy, Elsevier, vol. 131(C), pages 448-458.

    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:238:y:2019:i:c:p:627-642. 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.