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Optimal battery storage operation for PV systems with tariff incentives

Author

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  • 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
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    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. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. 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.
    16. 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.
    17. 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.
    18. 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.
    19. 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.
    20. 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.
    21. 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.
    22. Wu, Zhou & Tazvinga, Henerica & Xia, Xiaohua, 2015. "Demand side management of photovoltaic-battery hybrid system," Applied Energy, Elsevier, vol. 148(C), pages 294-304.
    23. 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.
    24. 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.
    25. 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.
    26. repec:ten:wpaper:20141 is not listed on IDEAS
    27. 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.
    28. 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.
    29. 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.
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