SELECTION OF ELECTRICITY TARIFF DESIGNS FOR DISTRIBUTION NETWORKS USING ANALYTIC NETWORK PROCESS

##plugins.themes.bootstrap3.article.main##

##plugins.themes.bootstrap3.article.sidebar##

Published Oct 4, 2023
Vinod Nair Usha Nair

Abstract

In electricity distribution networks, tariff designs set the interface between the users and network operators or service providers. Tariff designs provide the reference base for tariff schedules covering multiple categories of network users. It is widely accepted that electric utility rate designs have subjective and objective multi-criteria dependencies. Based on utility rate making literature, subcriteria for selection of tariff designs can be listed under the economic, technological, and social criteria. In this study, two widely used electricity tariff designs, volumetric or energy charges and capacity or demand charges are considered. In addition, real-time pricing and a hybrid tariff design that combines energy and capacity charges with critical peak pricing are also included in the comparison. Performance evaluation of these tariff designs on quantifiable parameters relating to economic aspects is carried out using the Tariff Design and Analysis Tool. Literature on electricity tariff designs and pricing provides the metadata on performance relating to qualitative criteria covering mainly the technological and social aspects. A synthesis of the quantitative and qualitative criteria evaluations was done by developing a Benefits-Opportunities-Costs-Risks (BOCR) model in the Analytic Network Process (ANP), a Multi-Criteria Decision Making methodology. A quantitative assessment of inconsistencies in evaluation and synthesis of the model using a consistency index shows that the developed ANP framework for tariff design selection is a valid approach. The developed BOCR model in ANP shows that the hybrid tariff design of Energy and Capacity charges with Coincident Peak Pricing is the best alternative. A sensitivity analysis shows that the ranking is variable when the BOCR priorities change.

 

How to Cite

Nair, V., & Nair, U. (2023). SELECTION OF ELECTRICITY TARIFF DESIGNS FOR DISTRIBUTION NETWORKS USING ANALYTIC NETWORK PROCESS. International Journal of the Analytic Hierarchy Process, 15(2). https://doi.org/10.13033/ijahp.v15i2.1052

Downloads

Download data is not yet available.
Abstract 244 | PDF Downloads 327

##plugins.themes.bootstrap3.article.details##

Keywords

Capacity charges, Coincident Peak Pricing, Electricity tariff, Real Time Pricing, Volumetric charges, Analytic Network Process

References
AEC (2018).Solar report.Australian Energy Council.

AEMO (2017). Distribution loss factors for the 2017/2018 financial year, Version 6.

AEMO(2019).National electricity market data,2017. [Online].Available: www.aemo.com.au/ Electricity/ National-Electricity-Market-NEM/Data- dashboard #aggregated-data

AusGrid(2020).Solar home electricity data.[Online]. Available :www.ausgrid.com.au/Industry/Our-Research/Data-to-share/Solar-home-electricity-data

Anderson, J. A. (2009). Electricity restructuring: a review of efforts around the world and the consumer response. The Electricity Journal, 22(3), 70-86.

Ansarin, M., Ghiassi-Farrokhfal, Y., Ketter, W., Collins, J. (2020). The economic consequences of electricity tariff design in a renewable energy era. Applied Energy, 275(1), 115317.Doi: https://doi.org/10.1016/j.apenergy.2020.115317

Apponen, R., Heine, P., Lehtinen, J., Lehtonen, M., Lummi, K., Järventausta, P. (2017).Development of power-based tariff structure for small customers and pathway for this change. CIRED-Open Access Proceedings Journal, 2017(1), 2692-2695.Doi: https://doi.org/10.1049/oap-cired.2017.0701

Ayo-Vaughan, J. (2022).Empowering tomorrow, controlling today: a multi-criteria assessment of electricity grid tariff designs. Document No: 1020997_Ayo, [Master’s Thesis, Eindhoven University of Technology].

Bai, C., Yang, F., Zhang, Y. (2016). Transforming the electricity value chain: A view from consumer demand. Journal of Clean Energy Technologies, 4(6), 408-413.Doi: https://doi.org/10.18178/jocet.2016.4.6.322

Bogdanov, D., Ram, M., Aghahosseini, A., Gulagi, A., Oyewo, A. S., Child, M., Sadovskaia C.K., Barbosa, L.D.N.S., Fasihi, M., Khalili,S., ThureTraber, T., Breyer, C. (2021). Low-cost renewable electricity as the key driver of the global energy transition towards sustainability. Energy, 227, 120467. Doi: https://doi.org/10.1016/j.energy.2021.120467

Bohra, S. S., Anvari Moghaddam, A. (2022). A comprehensive review on applications of multicriteria decision making methods in power and energy systems. International Journal of Energy Research, 46(4), 4088-4118.Doi: https://doi.org/10.1002/er.7517

Bonbright, J. C., Danielsen, A. L., Kamerschen, D. R. (1961). Principles of public utility rates . New York: Columbia University Press.

Brown, T., Faruqui, A. (2014). Structure of electricity distribution network tariffs: recovery of residual costs. Sydney: Australian Energy Market Commission.

Burger, S. P., Luke, M. (2017). Business models for distributed energy resources: A review and empirical analysis. Energy Policy, 109, 230-248.Doi: https://doi.org/10.1016/j.enpol.2017.07.007

Cantarero, M. M. V. (2020). Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries. Energy Research & Social Science, 70, 101716.Doi:https://doi.org/10.1016/j.erss.2020.101716

Cagnano, A., De Tuglie, E., Mancarella, P. (2020). Microgrids: Overview and guidelines for practical implementations and operation. Applied Energy, 258, 114039.Doi: https://doi.org/10.1016/j.apenergy.2019.114039

Darghouth, N. R., Barbose, G., Wiser, R. (2011). The impact of rate design and net metering on the bill savings from distributed PV for residential customers in California. Energy Policy, 39(9), 5243-5253. Doi: https://doi.org/10.1016/j.enpol.2011.05.040

De Martini, P. (2019). Operational coordination architecture: New models and approaches. IEEE Power and Energy Magazine, 17(5), 29-39.Doi: https://doi.org/10.1109/mpe.2019.2921740

Faruqui, A., Sergici, S. (2010). Household response to dynamic pricing of electricity: a survey of 15 experiments. Journal of Regulatory Economics, 38(2), 193-225.Doi: https://doi.org/10.1007/s11149-010-9127-y

Faruqui, A., Bourbonnais, C. (2020). The tariffs of tomorrow: Innovations in rate designs. IEEE Power and Energy Magazine, 18(3), 18-25.

Foster, V., Witte, S. H. (2020).Falling short: A global survey of electricity tariff design. Working Paper No. 9174. World Bank Policy Research.

Gencer, B., Larsen, E. R., van Ackere, A. (2020). Understanding the coevolution of electricity markets and regulation. Energy Policy, 143, 111585. Doi: https://doi.org/10.1016/j.enpol.2020.111585

Ghorbanian, M., Dolatabadi, S. H., Masjedi, M., Siano, P. (2019). Communication in smart grids: A comprehensive review on the existing and future communication and information infrastructures. IEEE Systems Journal, 13(4), 4001-4014.Doi: https://doi.org/10.1109/jsyst.2019.2928090

Glachant, J. M. (2021). New business models in the electricity sector. In J.M. Glachant, P.L. Joskow and M.G. Pollitt (Eds).Handbook on Electricity Markets (pp. 443-462). Edward Elgar Publishing. Doi: https://doi.org/10.4337/9781788979955.00024

Grünewald, P., McKenna, E., Thomson, M. (2015). Keep it simple: time-of-use tariffs in high-wind scenarios. IET Renewable Power Generation, 9(2), 176-183.Doi: https://doi.org/10.1049/iet-rpg.2014.0031

Günther, C., Schill, W. P., Zerrahn, A. (2021). Prosumage of solar electricity: Tariff design, capacity investments, and power sector effects. Energy Policy, 152, 112168.Doi: https://doi.org/10.1016/j.enpol.2021.112168

Hamwi, M., Lizarralde, I., Legardeur, J. (2021). Demand response business model canvas: A tool for flexibility creation in the electricity markets. Journal of Cleaner Production, 282, 124539.Doi: https://doi.org/10.1016/j.jclepro.2020.124539

Hobman, E.V., Frederiks, E.R., Stenner, K. and Meikle, S. (2016). Uptake and usage of cost-reflective electricity pricing: Insights from psychology and behavioural economics. Renewable and Sustainable Energy Reviews, 57, 455-467.Doi: https://doi.org/10.1016/j.rser.2015.12.144

Jang, D., Eom, J., Park, M. J., Rho, J. J. (2016). Variability of electricity load patterns and its effect on demand response: A critical peak pricing experiment on Korean commercial and industrial customers. Energy Policy, 88, 11-26.Doi: https://doi.org/10.1016/j.enpol.2015.09.029

Jargstorf, J., Belmans, R. (2015). Multi-objective low voltage grid tariff setting. IET Generation, Transmission & Distribution, 9(15), 2328-2336.Doi: https://doi.org/10.1049/iet-gtd.2014.1165

Kaye, R. J., Outhred, H. R. (1989). A theory of electricity tariff design for optimal operation and investment. IEEE Transactions on Power Systems, 4(2), 606-613.Doi: https://doi.org/10.1109/59.193835

Kirschen, D. S., Strbac, G. (2018). Fundamentals of power system economics. John Wiley & Sons.

Kumar, A., Sah, B., Singh, A.R.,. Deng, Y., He, X., Kumar, P., Bansal, R.C. (2017).A review of multi-criteria decision making towards sustainable renewable energy development. Renewable and Sustainable Energy Reviews, 69, 596–609.Doi: https://doi.org/10.1016/j.rser.2016.11.191

Lenhart, S., Araújo, K. (2021). Microgrid decision-making by public power utilities in the United States: A critical assessment of adoption and technological profiles. Renewable and Sustainable Energy Reviews, 139, 110692.Doi: https://doi.org/10.1016/j.rser.2020.110692

Masera, M., Bompard, E. F., Profumo, F., Hadjsaid, N. (2018). Smart (electricity) grids for smart cities: Assessing roles and societal impacts. Proceedings of the IEEE, 106(4), 613-625.Doi: https://doi.org/10.1109/jproc.2018.2812212

Mastropietro, P. (2019). Who should pay to support renewable electricity? Exploring regressive impacts, energy poverty and tariff equity. Energy Research & Social Science, 56, 101222.Doi: https://doi.org/10.1016/j.erss.2019.101222

Passey, R., Haghdadi, N., Bruce, A., MacGill, I. (2017). Designing more cost reflective
electricity network tariffs with demand charges. Energy Policy, 109, 642-649.Doi: https://doi.org/10.1016/j.enpol.2017.07.045

Picciariello, A., Reneses, J., Frias, P., Söder, L. (2015). Distributed generation and distribution pricing: why do we need new tariff design methodologies?’ Electric Power Systems Research, 119, 370-376. Doi: https://doi.org/10.1016/j.epsr.2014.10.021

Pollitt, M. G. (2018). Electricity network charging in the presence of distributed energy resources. Economics of Energy & Environmental Policy, 7(1), 89-104.Doi: https://doi.org/10.5547/2160-5890.7.1.mpol

Rábago, K. R., Valova, R. (2018). Revisiting Bonbright’s principles of public utility rates in a DER world. Electricity Journal, 31(8), 9-13.Doi: https://doi.org/10.1016/j.tej.2018.09.004

Ratnam, K. S., Palanisamy, K., Yang, G. (2020). Future low-inertia power systems: Requirements, issues, and solutions-A review. Renewable and Sustainable Energy Reviews, 124, 109773.Doi: https://doi.org/10.1016/j.rser.2020.109773

Reneses, J., Ortega, M. P. R. (2014). Distribution pricing: theoretical principles and practical approaches. IET Generation, Transmission & Distribution, 8(10), 1645-1655.Doi: https://doi.org/10.1049/iet-gtd.2013.0817

Revesz, R. L., Unel, B. (2020). Managing the future of the electricity grid: Modernizing rate design. Harvard Environmental Law Review, 44, 43-115.

Saaty, T. L.,Vargas, L. G. (2006). Decision making with the analytic network process (Vol. 282). Berlin, Germany: Springer Science+ Business Media, LLC.

Satchwell, A., Cappers, P. (2018). Evolving grid services, products, and market opportunities for regulated electric utilities. Berkley, CA: Lawrence Berkley National Lab. Doi: https://doi.org/10.2172/1506307

Schittekatte, T., Momber, I., Meeus, L. (2018). Future-proof tariff design: Recovering sunk grid costs in a world where consumers are pushing back. Energy Economics, 70, 484-498.Doi: https://doi.org/10.1016/j.eneco.2018.01.028

Schittekatte, T., Deschamps, V., Meeus, L. (2021).The regulatory framework for independent aggregators. Electricity Journal, 34(6), 106971.Doi: https://doi.org/10.1016/j.tej.2021.106971

Stadler, M., Cardoso, G., Mashayekh, S., Forget, T., DeForest, N., Agarwal, A.,Schönbein, A. (2016). Value streams in microgrids: A literature review. Applied Energy, 162, 980-989.Doi: https://doi.org/10.1016/j.apenergy.2015.10.081

SuperDecisions Version 2.10.[ Online ]. Available: http://www.superdecisions.com

Tariff Design and Analysis Tool, CEEM-UNSW,2017.[Online].
Available: https://www.ceem.unsw.edu.au

Vijay, A., Fouquet, N., Staffell, I., Hawkes, A. (2017). The value of electricity and reserve services in low carbon electricity systems. Applied Energy, 201, 111-123.Doi: https://doi.org/10.1016/j.apenergy.2017.05.094

Wang, C., Zhou, H., Dınçer, H., Yüksel, S., Ubay, G. G., Uluer, G. S. (2020). Analysis of electricity pricing in emerging economies with hybrid multi-criteria decision-making technique based on interval-valued intuitionistic hesitant fuzzy sets. IEEE Access, 8, 190882-190896.Doi: https://doi.org/10.1109/access.2020.3031761

Widergren, S., Melton, R., Khandekar, A., Nordman, B., Knight, M. (2019). The plug-and-play electricity era: Interoperability to integrate anything, anywhere, anytime. IEEE Power and Energy Magazine, 17(5), 47-58.Doi: https://doi.org/10.1109/mpe.2019.2921742

Woo, C. K., Sreedharan, P., Hargreaves, J., Kahrl, F., Wang, J., Horowitz, I. (2014). A review of electricity product differentiation. Applied Energy, 114, 262-272.Doi: https://doi.org/10.1016/j.apenergy.2013.09.070

Young, S., Bruce, A., &MacGill, I. (2019).Potential impacts of residential PV and battery storage on Australia's electricity networks under different tariffs. Energy Policy, 128, 616-627.Doi: https://doi.org/10.1016/j.enpol.2019.01.005

Section
Articles