IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v162y2016icp713-722.html
   My bibliography  Save this article

Net metering and market feedback loops: Exploring the impact of retail rate design on distributed PV deployment

Author

Listed:
  • Darghouth, Naïm R.
  • Wiser, Ryan H.
  • Barbose, Galen
  • Mills, Andrew D.

Abstract

The substantial increase in deployment of customer-sited solar photovoltaics (PV) in the United States has been driven by a combination of steeply declining costs, financing innovations, and supportive policies. Among those supportive policies is net metering, which in most states effectively allows customers to receive compensation for distributed PV generation at the full retail electricity price. The current design of retail electricity rates and the presence of net metering have elicited concerns that the possible under-recovery of fixed utility costs from PV system owners may lead to a feedback loop of increasing retail prices that accelerate PV adoption and further rate increases. However, a separate and opposing feedback loop could offset this effect: increased PV deployment may lead to a shift in the timing of peak-period electricity prices that could reduce the bill savings received under net metering where time-varying retail electricity rates are used, thereby dampening further PV adoption. In this paper, we examine the impacts of these two competing feedback dynamics on U.S. distributed PV deployment through 2050 for both residential and commercial customers, across states. Our results indicate that, at the aggregate national level, the two feedback effects nearly offset one another and therefore produce a modest net effect, although their magnitude and direction vary by customer segment and by state. We also model aggregate PV deployment trends under various rate designs and net-metering rules, accounting for feedback dynamics. Our results demonstrate that future adoption of distributed PV is highly sensitive to retail rate structures. Whereas flat, time-invariant rates with net metering lead to higher aggregate national deployment levels than the current mix of rate structures (+5% in 2050), rate structures with higher monthly fixed customer charges or PV compensation at levels lower than the full retail rate can dramatically erode aggregate customer adoption of PV (from −14% to −61%, depending on the design). Moving towards time-varying rates, on the other hand, accelerates near- and medium-term deployment (through 2030) but slows adoption in the longer term (−22% in 2050).

Suggested Citation

  • Darghouth, Naïm R. & Wiser, Ryan H. & Barbose, Galen & Mills, Andrew D., 2016. "Net metering and market feedback loops: Exploring the impact of retail rate design on distributed PV deployment," Applied Energy, Elsevier, vol. 162(C), pages 713-722.
  • Handle: RePEc:eee:appene:v:162:y:2016:i:c:p:713-722
    DOI: 10.1016/j.apenergy.2015.10.120
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261915013562
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.apenergy.2015.10.120?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. Lion Hirth, 2013. "The Market Value of Variable Renewables. The Effect of Solar and Wind Power Variability on their Relative Price," RSCAS Working Papers 2013/36, European University Institute.
    2. Darghouth, Naïm R. & Barbose, Galen & Wiser, Ryan, 2011. "The impact of rate design and net metering on the bill savings from distributed PV for residential customers in California," Energy Policy, Elsevier, vol. 39(9), pages 5243-5253, September.
    3. 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.
    4. Eid, Cherrelle & Reneses Guillén, Javier & Frías Marín, Pablo & Hakvoort, Rudi, 2014. "The economic effect of electricity net-metering with solar PV: Consequences for network cost recovery, cross subsidies and policy objectives," Energy Policy, Elsevier, vol. 75(C), pages 244-254.
    5. Hirth, Lion, 2013. "The market value of variable renewables," Energy Economics, Elsevier, vol. 38(C), pages 218-236.
    6. Mills, Andrew & Wiser, Ryan & Barbose, Galen & Golove, William, 2008. "The impact of retail rate structures on the economics of commercial photovoltaic systems in California," Energy Policy, Elsevier, vol. 36(9), pages 3266-3277, September.
    7. Darghouth, Naïm R. & Barbose, Galen & Wiser, Ryan H., 2014. "Customer-economics of residential photovoltaic systems (Part 1): The impact of high renewable energy penetrations on electricity bill savings with net metering," Energy Policy, Elsevier, vol. 67(C), pages 290-300.
    8. Sensfuß, Frank & Ragwitz, Mario & Genoese, Massimo, 2008. "The merit-order effect: A detailed analysis of the price effect of renewable electricity generation on spot market prices in Germany," Energy Policy, Elsevier, vol. 36(8), pages 3076-3084, August.
    9. Nottrott, A. & Kleissl, J. & Washom, B., 2013. "Energy dispatch schedule optimization and cost benefit analysis for grid-connected, photovoltaic-battery storage systems," Renewable Energy, Elsevier, vol. 55(C), pages 230-240.
    10. Mills, Andrew D. & Wiser, Ryan H., 2015. "Strategies to mitigate declines in the economic value of wind and solar at high penetration in California," Applied Energy, Elsevier, vol. 147(C), pages 269-278.
    11. Cai, Desmond W.H. & Adlakha, Sachin & Low, Steven H. & De Martini, Paul & Mani Chandy, K., 2013. "Impact of residential PV adoption on Retail Electricity Rates," Energy Policy, Elsevier, vol. 62(C), pages 830-843.
    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. Castaneda, Monica & Jimenez, Maritza & Zapata, Sebastian & Franco, Carlos J. & Dyner, Isaac, 2017. "Myths and facts of the utility death spiral," Energy Policy, Elsevier, vol. 110(C), pages 105-116.
    2. L. (Lisa B.) Ryan & Sarah La Monaca & Linda Mastrandrea & Petr Spodniak, 2018. "Harnessing Electricity Retail Tariffs to Support Climate Change Policy," Working Papers 201822, School of Economics, University College Dublin.
    3. Georgios C. Christoforidis & Ioannis P. Panapakidis & Theofilos A. Papadopoulos & Grigoris K. Papagiannis & Ioannis Koumparou & Maria Hadjipanayi & George E. Georghiou, 2016. "A Model for the Assessment of Different Net-Metering Policies," Energies, MDPI, vol. 9(4), pages 1-24, April.
    4. Heleno, Miguel & Sehloff, David & Coelho, Antonio & Valenzuela, Alan, 2020. "Probabilistic impact of electricity tariffs on distribution grids considering adoption of solar and storage technologies," Applied Energy, Elsevier, vol. 279(C).
    5. Brown, Patrick R. & O'Sullivan, Francis M., 2020. "Spatial and temporal variation in the value of solar power across United States electricity markets," Renewable and Sustainable Energy Reviews, Elsevier, vol. 121(C).
    6. Hartner, Michael & Ortner, André & Hiesl, Albert & Haas, Reinhard, 2015. "East to west – The optimal tilt angle and orientation of photovoltaic panels from an electricity system perspective," Applied Energy, Elsevier, vol. 160(C), pages 94-107.
    7. Brown, T. & Reichenberg, L., 2021. "Decreasing market value of variable renewables can be avoided by policy action," Energy Economics, Elsevier, vol. 100(C).
    8. Eising, Manuel & Hobbie, Hannes & Möst, Dominik, 2020. "Future wind and solar power market values in Germany — Evidence of spatial and technological dependencies?," Energy Economics, Elsevier, vol. 86(C).
    9. Darghouth, Naïm R. & Wiser, Ryan H. & Barbose, Galen, 2016. "Customer economics of residential photovoltaic systems: Sensitivities to changes in wholesale market design and rate structures," Renewable and Sustainable Energy Reviews, Elsevier, vol. 54(C), pages 1459-1469.
    10. Dufo-López, Rodolfo & Bernal-Agustín, José L., 2015. "A comparative assessment of net metering and net billing policies. Study cases for Spain," Energy, Elsevier, vol. 84(C), pages 684-694.
    11. Kubli, Merla, 2018. "Squaring the sunny circle? On balancing distributive justice of power grid costs and incentives for solar prosumers," Energy Policy, Elsevier, vol. 114(C), pages 173-188.
    12. Csereklyei, Zsuzsanna & Qu, Songze & Ancev, Tihomir, 2019. "The effect of wind and solar power generation on wholesale electricity prices in Australia," Energy Policy, Elsevier, vol. 131(C), pages 358-369.
    13. Simshauser, P., 2019. "On the impact of government-initiated CfD’s in Australia’s National Electricity Market," Cambridge Working Papers in Economics 1901, Faculty of Economics, University of Cambridge.
    14. Gugler, Klaus & Haxhimusa, Adhurim, 2019. "Market integration and technology mix: Evidence from the German and French electricity markets," Energy Policy, Elsevier, vol. 126(C), pages 30-46.
    15. Mills, Andrew & Wiser, Ryan & Millstein, Dev & Carvallo, Juan Pablo & Gorman, Will & Seel, Joachim & Jeong, Seongeun, 2021. "The impact of wind, solar, and other factors on the decline in wholesale power prices in the United States," Applied Energy, Elsevier, vol. 283(C).
    16. Pape, Christian, 2018. "The impact of intraday markets on the market value of flexibility — Decomposing effects on profile and the imbalance costs," Energy Economics, Elsevier, vol. 76(C), pages 186-201.
    17. Marie Petitet, Dominique Finon, and Tanguy Janssen, 2016. "Carbon Price instead of Support Schemes: Wind Power Investments by the Electricity Market," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4).
    18. Brian Rivard and Adonis Yatchew, 2016. "Integration of Renewables into the Ontario Electricity System," The Energy Journal, International Association for Energy Economics, vol. 0(Bollino-M).
    19. Axel Gautier & Julien Jacqmin & Jean-Christophe Poudou, 2018. "The prosumers and the grid," Journal of Regulatory Economics, Springer, vol. 53(1), pages 100-126, February.
    20. Klaus Gugler & Mario Liebensteiner & Adhurim Haxhimusa & Nora Schindler, 2016. "Investment under Uncertainty in Electricity Generation," Department of Economics Working Papers wuwp234, Vienna University of Economics and Business, Department of Economics.

    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:713-722. 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.