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Feasibility assessment for high penetration of distributed photovoltaics based on net demand planning

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  • Azzopardi, Brian
  • Gabriel-Buenaventura, Alejandro

Abstract

Well integrated distributed photovoltaics (PVs) will help tomorrow's energy system become more sustainable. This paper highlights the net demand planning feasibility assessment to understand these dynamics. These dynamics underpins the technical feasibility when setting up high penetration of PVs within a new development area. Real measurements of disaggregated domestic electricity demand from three low-carbon homes and simulated PV output are used. A case study is based on a new building development in North West Bicester Eco Town, Oxfordshire, consisting of 393 homes, community and commercial units. Using simulation models and real domestic load measurements, the results show potential for demand management and energy storage. With a sensitivity analysis, the paper discusses also related energy policy aspects such as options for PV orientation aspects, the use of Electric Vehicles (EVs), the potential of Direct Current electrical installations and schemes that encourage load shifting. The paper concludes, within the context of the case study, assumptions and scenarios that, contrary to what is commonly believed, high penetration of PVs in a development area is feasible and may even reduce grid infrastructure costs.

Suggested Citation

  • Azzopardi, Brian & Gabriel-Buenaventura, Alejandro, 2014. "Feasibility assessment for high penetration of distributed photovoltaics based on net demand planning," Energy, Elsevier, vol. 76(C), pages 233-240.
    • Handle: RePEc:eee:energy:v:76:y:2014:i:c:p:233-240
    DOI: 10.1016/j.energy.2014.06.052
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    1. 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.
    2. Doostizadeh, Meysam & Ghasemi, Hassan, 2012. "A day-ahead electricity pricing model based on smart metering and demand-side management," Energy, Elsevier, vol. 46(1), pages 221-230.
    3. Atikol, Uğur, 2013. "A simple peak shifting DSM (demand-side management) strategy for residential water heaters," Energy, Elsevier, vol. 62(C), pages 435-440.
    4. Pina, André & Silva, Carlos & Ferrão, Paulo, 2012. "The impact of demand side management strategies in the penetration of renewable electricity," Energy, Elsevier, vol. 41(1), pages 128-137.
    5. Breukers, S.C. & Heiskanen, E. & Brohmann, B. & Mourik, R.M. & Feenstra, C.F.J., 2011. "Connecting research to practice to improve energy demand-side management (DSM)," Energy, Elsevier, vol. 36(4), pages 2176-2185.
    6. Ji, L. & Niu, D.X. & Huang, G.H., 2014. "An inexact two-stage stochastic robust programming for residential micro-grid management-based on random demand," Energy, Elsevier, vol. 67(C), pages 186-199.
    7. Finn, P. & Fitzpatrick, C. & Connolly, D., 2012. "Demand side management of electric car charging: Benefits for consumer and grid," Energy, Elsevier, vol. 42(1), pages 358-363.
    8. Torriti, Jacopo, 2012. "Price-based demand side management: Assessing the impacts of time-of-use tariffs on residential electricity demand and peak shifting in Northern Italy," Energy, Elsevier, vol. 44(1), pages 576-583.
    9. Prüggler, Natalie & Prüggler, Wolfgang & Wirl, Franz, 2011. "Storage and Demand Side Management as power generator’s strategic instruments to influence demand and prices," Energy, Elsevier, vol. 36(11), pages 6308-6317.
    Full references (including those not matched with items on IDEAS)

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    7. Mohammad Rozali, Nor Erniza & Wan Alwi, Sharifah Rafidah & Manan, Zainuddin Abdul & Klemeš, Jiří Jaromír, 2015. "Peak-off-peak load shifting for hybrid power systems based on Power Pinch Analysis," Energy, Elsevier, vol. 90(P1), pages 128-136.
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    9. Markovska, Natasa & Duić, Neven & Mathiesen, Brian Vad & Guzović, Zvonimir & Piacentino, Antonio & Schlör, Holger & Lund, Henrik, 2016. "Addressing the main challenges of energy security in the twenty-first century – Contributions of the conferences on Sustainable Development of Energy, Water and Environment Systems," Energy, Elsevier, vol. 115(P3), pages 1504-1512.
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