IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v203y2017icp422-441.html
   My bibliography  Save this article

Optimal battery storage operation for PV systems with tariff incentives

Author

Listed:
  • Sani Hassan, Abubakar
  • Cipcigan, Liana
  • Jenkins, Nick

Abstract

Many efforts are recently being dedicated to developing models that seek to provide insights into the techno-economic benefits of battery storage coupled to photovoltaic (PV) generation system. However, not all models consider the operation of the PV – battery storage system with a feed-in tariff (FiT) incentive, different electricity rates and battery storage unit cost. An electricity customer whose electricity demand is supplied by a grid connected PV generation system benefiting from a FiT incentive is simulated in this paper. The system is simulated with the PV modelled as an existing system and the PV modelled as a new system. For a better understanding of the existing PV system with battery storage operation, an optimisation problem was formulated which resulted in a mixed integer linear programming (MILP) problem. The optimisation model was developed to solve the MILP problem and to analyse the benefits considering different electricity tariffs and battery storage in maximising FiT revenue streams for the existing PV generating system. Real data from a typical residential solar PV owner is used to study the benefit of the battery storage system using half-hourly dataset for a complete year. A sensitivity analysis of the MILP optimisation model was simulated to evaluate the impact of battery storage capacity (kWh) on the objective function. In the second case study, the electricity demand data, solar irradiance, tariff and battery unit cost were used to analyse the effect of battery storage unit cost on the adoption of electricity storage in maximising FiT revenue. In this case, the PV is simulated as a new system using Distributed Energy Resources Customer Adoption Model (DER-CAM) software tool while modifying the optimisation formulation to include the PV onsite generation and export tariff incentive. The results provide insights on the benefit of battery storage for existing and new PV system benefiting from FiT incentives and under time-varying electricity tariffs.

Suggested Citation

  • Sani Hassan, Abubakar & Cipcigan, Liana & Jenkins, Nick, 2017. "Optimal battery storage operation for PV systems with tariff incentives," Applied Energy, Elsevier, vol. 203(C), pages 422-441.
  • Handle: RePEc:eee:appene:v:203:y:2017:i:c:p:422-441
    DOI: 10.1016/j.apenergy.2017.06.043
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S030626191730778X
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.apenergy.2017.06.043?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. Beck, T. & Kondziella, H. & Huard, G. & Bruckner, T., 2017. "Optimal operation, configuration and sizing of generation and storage technologies for residential heat pump systems in the spotlight of self-consumption of photovoltaic electricity," Applied Energy, Elsevier, vol. 188(C), pages 604-619.
    2. Stadler, Michael & Cardoso, Gonçalo & Mashayekh, Salman & Forget, Thibault & DeForest, Nicholas & Agarwal, Ankit & Schönbein, Anna, 2016. "Value streams in microgrids: A literature review," Applied Energy, Elsevier, vol. 162(C), pages 980-989.
    3. Khalilpour, Rajab & Vassallo, Anthony, 2016. "Planning and operation scheduling of PV-battery systems: A novel methodology," Renewable and Sustainable Energy Reviews, Elsevier, vol. 53(C), pages 194-208.
    4. Bertsch, Valentin & Geldermann, Jutta & Lühn, Tobias, 2017. "What drives the profitability of household PV investments, self-consumption and self-sufficiency?," Applied Energy, Elsevier, vol. 204(C), pages 1-15.
    5. Xydas, Erotokritos & Qadrdan, Meysam & Marmaras, Charalampos & Cipcigan, Liana & Jenkins, Nick & Ameli, Hossein, 2017. "Probabilistic wind power forecasting and its application in the scheduling of gas-fired generators," Applied Energy, Elsevier, vol. 192(C), pages 382-394.
    6. Wang, Y.F. & Li, K.P. & Xu, X.M. & Zhang, Y.R., 2014. "Transport energy consumption and saving in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 29(C), pages 641-655.
    7. Pyrgou, Andri & Kylili, Angeliki & Fokaides, Paris A., 2016. "The future of the Feed-in Tariff (FiT) scheme in Europe: The case of photovoltaics," Energy Policy, Elsevier, vol. 95(C), pages 94-102.
    8. Ayón, X. & Gruber, J.K. & Hayes, B.P. & Usaola, J. & Prodanović, M., 2017. "An optimal day-ahead load scheduling approach based on the flexibility of aggregate demands," Applied Energy, Elsevier, vol. 198(C), pages 1-11.
    9. Ratnam, Elizabeth L. & Weller, Steven R. & Kellett, Christopher M., 2015. "An optimization-based approach to scheduling residential battery storage with solar PV: Assessing customer benefit," Renewable Energy, Elsevier, vol. 75(C), pages 123-134.
    10. Wu, Zhou & Tazvinga, Henerica & Xia, Xiaohua, 2015. "Demand side management of photovoltaic-battery hybrid system," Applied Energy, Elsevier, vol. 148(C), pages 294-304.
    11. Hoppmann, Joern & Volland, Jonas & Schmidt, Tobias S. & Hoffmann, Volker H., 2014. "The economic viability of battery storage for residential solar photovoltaic systems – A review and a simulation model," Renewable and Sustainable Energy Reviews, Elsevier, vol. 39(C), pages 1101-1118.
    12. Holladay, J. Scott & Price, Michael K. & Wanamaker, Marianne, 2015. "The perverse impact of calling for energy conservation," Journal of Economic Behavior & Organization, Elsevier, vol. 110(C), pages 1-18.
    13. Matthew Rowe & Timur Yunusov & Stephen Haben & William Holderbaum & Ben Potter, 2014. "The Real-Time Optimisation of DNO Owned Storage Devices on the LV Network for Peak Reduction," Energies, MDPI, vol. 7(6), pages 1-24, May.
    14. Xue, Yu & Kang, San-Jun & Lu, Wei-Zhen & He, Hong-Di, 2014. "Energy dissipation of traffic flow at an on-ramp," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 398(C), pages 172-178.
    15. Brusco, Giovanni & Burgio, Alessandro & Menniti, Daniele & Pinnarelli, Anna & Sorrentino, Nicola, 2016. "The economic viability of a feed-in tariff scheme that solely rewards self-consumption to promote the use of integrated photovoltaic battery systems," Applied Energy, Elsevier, vol. 183(C), pages 1075-1085.
    16. Li, J.S. & Chen, G.Q. & Wu, X.F. & Hayat, T. & Alsaedi, A. & Ahmad, B., 2014. "Embodied energy assessment for Macao׳s external trade," Renewable and Sustainable Energy Reviews, Elsevier, vol. 34(C), pages 642-653.
    17. Stadler, M. & Groissböck, M. & Cardoso, G. & Marnay, C., 2014. "Optimizing Distributed Energy Resources and building retrofits with the strategic DER-CAModel," Applied Energy, Elsevier, vol. 132(C), pages 557-567.
    18. Li, Ran & Wang, Zhimin & Gu, Chenghong & Li, Furong & Wu, Hao, 2016. "A novel time-of-use tariff design based on Gaussian Mixture Model," Applied Energy, Elsevier, vol. 162(C), pages 1530-1536.
    19. repec:ten:wpaper:20141 is not listed on IDEAS
    20. Nistor, Silviu & Wu, Jianzhong & Sooriyabandara, Mahesh & Ekanayake, Janaka, 2015. "Capability of smart appliances to provide reserve services," Applied Energy, Elsevier, vol. 138(C), pages 590-597.
    21. 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.
    22. Berrada, Asmae & Loudiyi, Khalid, 2016. "Operation, sizing, and economic evaluation of storage for solar and wind power plants," Renewable and Sustainable Energy Reviews, Elsevier, vol. 59(C), pages 1117-1129.
    23. Linssen, Jochen & Stenzel, Peter & Fleer, Johannes, 2017. "Techno-economic analysis of photovoltaic battery systems and the influence of different consumer load profiles," Applied Energy, Elsevier, vol. 185(P2), pages 2019-2025.
    24. Balcombe, Paul & Rigby, Dan & Azapagic, Adisa, 2015. "Environmental impacts of microgeneration: Integrating solar PV, Stirling engine CHP and battery storage," Applied Energy, Elsevier, vol. 139(C), pages 245-259.
    25. Quoilin, Sylvain & Kavvadias, Konstantinos & Mercier, Arnaud & Pappone, Irene & Zucker, Andreas, 2016. "Quantifying self-consumption linked to solar home battery systems: Statistical analysis and economic assessment," Applied Energy, Elsevier, vol. 182(C), pages 58-67.
    26. Morvaj, Boran & Evins, Ralph & Carmeliet, Jan, 2016. "Optimization framework for distributed energy systems with integrated electrical grid constraints," Applied Energy, Elsevier, vol. 171(C), pages 296-313.
    27. Cherrington, R. & Goodship, V. & Longfield, A. & Kirwan, K., 2013. "The feed-in tariff in the UK: A case study focus on domestic photovoltaic systems," Renewable Energy, Elsevier, vol. 50(C), pages 421-426.
    28. Olaszi, Balint D. & Ladanyi, Jozsef, 2017. "Comparison of different discharge strategies of grid-connected residential PV systems with energy storage in perspective of optimal battery energy storage system sizing," Renewable and Sustainable Energy Reviews, Elsevier, vol. 75(C), pages 710-718.
    29. Karakaya, Emrah & Hidalgo, Antonio & Nuur, Cali, 2015. "Motivators for adoption of photovoltaic systems at grid parity: A case study from Southern Germany," Renewable and Sustainable Energy Reviews, Elsevier, vol. 43(C), pages 1090-1098.
    Full references (including those not matched with items on IDEAS)

    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. Andreolli, Francesca & D’Alpaos, Chiara & Moretto, Michele, 2022. "Valuing investments in domestic PV-Battery Systems under uncertainty," Energy Economics, Elsevier, vol. 106(C).
    2. O'Shaughnessy, Eric & Cutler, Dylan & Ardani, Kristen & Margolis, Robert, 2018. "Solar plus: A review of the end-user economics of solar PV integration with storage and load control in residential buildings," Applied Energy, Elsevier, vol. 228(C), pages 2165-2175.
    3. von Appen, J. & Braun, M., 2018. "Interdependencies between self-sufficiency preferences, techno-economic drivers for investment decisions and grid integration of residential PV storage systems," Applied Energy, Elsevier, vol. 229(C), pages 1140-1151.
    4. Schopfer, S. & Tiefenbeck, V. & Staake, T., 2018. "Economic assessment of photovoltaic battery systems based on household load profiles," Applied Energy, Elsevier, vol. 223(C), pages 229-248.
    5. Bruno Domenech & Gema Calleja & Jordi Olivella, 2021. "Residential Photovoltaic Profitability with Storage under the New Spanish Regulation: A Multi-Scenario Analysis," Energies, MDPI, vol. 14(7), pages 1-17, April.
    6. Azuatalam, Donald & Paridari, Kaveh & Ma, Yiju & Förstl, Markus & Chapman, Archie C. & Verbič, Gregor, 2019. "Energy management of small-scale PV-battery systems: A systematic review considering practical implementation, computational requirements, quality of input data and battery degradation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 112(C), pages 555-570.
    7. Olivella, Jordi & Domenech, Bruno & Calleja, Gema, 2021. "Potential of implementation of residential photovoltaics at city level: The case of London," Renewable Energy, Elsevier, vol. 180(C), pages 577-585.
    8. Hirschburger, Rafael & Weidlich, Anke, 2020. "Profitability of photovoltaic and battery systems on municipal buildings," Renewable Energy, Elsevier, vol. 153(C), pages 1163-1173.
    9. Ma, Tao & Zhang, Yijie & Gu, Wenbo & Xiao, Gang & Yang, Hongxing & Wang, Shuxiao, 2022. "Strategy comparison and techno-economic evaluation of a grid-connected photovoltaic-battery system," Renewable Energy, Elsevier, vol. 197(C), pages 1049-1060.
    10. Bertsch, Valentin & Geldermann, Jutta & Lühn, Tobias, 2017. "What drives the profitability of household PV investments, self-consumption and self-sufficiency?," Applied Energy, Elsevier, vol. 204(C), pages 1-15.
    11. Federica Cucchiella & Idiano D’Adamo & Massimo Gastaldi, 2017. "The Economic Feasibility of Residential Energy Storage Combined with PV Panels: The Role of Subsidies in Italy," Energies, MDPI, vol. 10(9), pages 1-18, September.
    12. Petrollese, Mario & Cau, Giorgio & Cocco, Daniele, 2018. "Use of weather forecast for increasing the self-consumption rate of home solar systems: An Italian case study," Applied Energy, Elsevier, vol. 212(C), pages 746-758.
    13. Aniello, Gianmarco & Shamon, Hawal & Kuckshinrichs, Wilhelm, 2021. "Micro-economic assessment of residential PV and battery systems: The underrated role of financial and fiscal aspects," Applied Energy, Elsevier, vol. 281(C).
    14. Han, Xuejiao & Garrison, Jared & Hug, Gabriela, 2022. "Techno-economic analysis of PV-battery systems in Switzerland," Renewable and Sustainable Energy Reviews, Elsevier, vol. 158(C).
    15. Barbour, Edward & González, Marta C., 2018. "Projecting battery adoption in the prosumer era," Applied Energy, Elsevier, vol. 215(C), pages 356-370.
    16. Aniello, Gianmarco & Bertsch, Valentin, 2023. "Shaping the energy transition in the residential sector: Regulatory incentives for aligning household and system perspectives," Applied Energy, Elsevier, vol. 333(C).
    17. Liu, Xuezhi & Yan, Zheng & Wu, Jianzhong, 2019. "Optimal coordinated operation of a multi-energy community considering interactions between energy storage and conversion devices," Applied Energy, Elsevier, vol. 248(C), pages 256-273.
    18. Oliva H., Sebastian & Passey, Rob & Abdullah, Md Abu, 2019. "A semi-empirical financial assessment of combining residential photovoltaics, energy efficiency and battery storage systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 105(C), pages 206-214.
    19. von Appen, J. & Braun, M., 2018. "Strategic decision making of distribution network operators and investors in residential photovoltaic battery storage systems," Applied Energy, Elsevier, vol. 230(C), pages 540-550.
    20. Rômulo de Oliveira Azevêdo & Paulo Rotela Junior & Luiz Célio Souza Rocha & Gianfranco Chicco & Giancarlo Aquila & Rogério Santana Peruchi, 2020. "Identification and Analysis of Impact Factors on the Economic Feasibility of Photovoltaic Energy Investments," Sustainability, MDPI, vol. 12(17), pages 1-40, September.

    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:203:y:2017:i:c:p:422-441. 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.