Decision making in the electricity sector using performance indicators

Abstract

The studies on the electricity sector are usually focused on the supply side, considering consumers as price-takers, i.e. assuming no demand elasticity. The present paper highlights the role of consumers on the electricity sector, assuming that consumers react to electricity prices and make decisions. Many studies focused on the demand side disaggregate consumers by activities, leading to a highly complex analyse. In the present paper, consumers are divided by three main types. In the present paper, the Government makes decisions on the measures to implement to influence the production and the consumption. To study the impact of the Government decisions, the present paper studies and implements a tool: a decision support system. This tool is based on a conceptual model and assists the task of test and analyse the electricity sector using scenarios to obtain a set of performance indicators that would allow to make quantitative balance and to eliminate unfeasible measures. The performance indicators quantify the technical, environmental, social and economical aspects of the electricity sector and help to understand the effect of consumer practices, production technology and Government measures on the electricity sector. Based on the scenarios produced, it is possible to conclude that the price signal is important for consumers and it is a way to guide their behaviour. It is also possible to conclude that is preferable to apply incentives on supporting energy-efficiency measures implementation than on reduce the price of electricity sold to consumers.

Keywords

Decision support systems / Demand elasticity / Energy efficiency and savings / Market-based instruments

References

[1] Abreu C (2007) Custos financeiros e sociais da geração de electricidade em parques eólicos. Universidade do Minho

[2] Bosquet Benoit. Environmental tax reform: does it work? A survey of the empirical evidence. Ecol Econ, 2000, 34(1): 19-32

[3] Barros T (2014) Previsão de carga—Comparação de técnicas. (Master), Faculdade de Engenharia da Universidade do Porto.

[4] Blarke M (2015) COMPOSE: compare options for sustainable energy. http://homes.et.aau.dk/mbb/compose.htm

[5] Boucinha J (1991) Electricty demand trends in Portugal. In: Paper presented at the ELAB—Encontro Luso Afro-Brasileiro de Redes de Energia

[6] Branquinho P (2014) Modelos de Previsão do Consumo Energético no Sector Residencial. (Master), IST

[7] Cabral A (2012) Tributação da electricidade num contexto ambiental. (Master), Universidade Católica Portuguesa do Porto

[8] Capros P (1995) Integrated economy-energy-environment models. In: Paper presented at the international symposium on electricity, health and the environment: comparative assessment in support of decision making, IAEA, Vienna, Austria

[9] Carmona N (2006) Modelação Econométrica da Procura de Electricidade em Portugal Continental: Uma Aplicação Empírica. ISEG

[10] COM (2009) Factsheets by Country. http://ec.europa.eu/energy/energypolicy/factsen.htm

[11] COM (2010) Taxation trends in the European Union: European Commission

[12] Connolly D, Lundb H, Mathiesenb BV, Leahya M. A review of computer tools for analysing the integration of renewable energy into various energy systems. Appl Energy, 2010, 87(4): 1059-1082

[13] Dorf RC. The electrical engineering handbook, 1997 Boca Raton CRC Press

[14] ECN (2012) On the design of an EU climate and energy policy framework for 2030—with special reference to renewable energy Policy Studies: Energy research Centre of the Netherlands

[15] EDP (2014) Origens da Eletricidade. http://www.edpsu.pt/pt/origemdaenergia/Pages/OrigensdaEnergia.aspx

[16] EEA (2012) Environmental tax reform in Europe: opportunities for eco-innovation (09 Jan 2012 ed.): European Environmental Agency

[17] EEA (2013) Achieving energy efficiency through behaviour change: what does it take?: European Environmental Agency

[18] EEA (2014) Resource-efficient green economy and EU policies: European Environmental Agency

[19] Endesa (2014) Como é produzida a electricidade que consome? http://www.endesa.pt/PT/iframe.asp

[20] ERSE, Entidade Reguladora do Sector Energético (2014) Relatório Mercado Liberalizado de Eletricidade - Maio 2014

[21] Eurostat. (2012a) Electricity prices for household consumers

[22] Eurostat. (2012b) Gas prices for household consumers

[23] EuroStat (2014) Statistics by theme. http://epp.eurostat.ec.europa.eu/portal/page/portal/statistics/themes

[24] Fortes P (2014) Clearing the cloudy crystall balls: hybrid modelling for energy and climate change mitigation scenarios—a case study for Portugal (Doutoramento), FCT

[25] GALP (2014) Eletricidade: origens e impacte ambiental. http://www.galpenergia.com/PT/ProdutosServicos/Produtos/Eletricidade/Centro-de-informacao/A-nossa-Energia/Paginas/A-nossa-Energia.aspx

[26] GEOTA (2013) Reforma Fiscal Ambiental: fiscalidade e incentivos no sector energético

[27] GBE, Green Budget Europe (2009) Economic Instruments for Energy Efficiency and the Environment In Policy Research Report (Ed.)

[28] Grubb M, Kohler J, Anderson D. Induced technical change in energy and environmental modeling: analytic approaches and policy implications. Annu Rev Energy Environ, 2002, 27: 271-308

[29] Horne M, Jaccard M, Tiedemann K. Improving behavioral realism in hybrid energyeconomy models using discrete choice studies of personal transportation decisions. Energy Econ, 2005, 27(1): 59-77

[30] Hourcade J-C, Jaccard M, Bataille C, Ghersi F. Hybrid modeling: new answers to old challenges introduction to the Special Issue of The Energy Journal. Energy J Hybrid Model, 2006

[31] IPCC (2006) Guidelines for National Greenhouse Gas. Energy Policy, 2

[32] IPCC (2014a) Climate change 2014: impacts, adaptation, and vulnerability

[33] IPCC (2014b) Climate change 2014: mitigation of climate change (Working Group III Technical Support Unit Ed.) Cambridge Publisher

[34] Jaccard M, Nyboer J, Bataille C, Sadownik B. Modeling the cost of climate policy: distinguishing between alternative cost definitions and long-run cost dynamics. Energy J, 2003, 24(1): 49-73

[35] Jaccard M, Murphy R, Rivers N. Energy–environment policy modeling of endogenous technological change with personal vehicles: combining top-down and bottom-up methods. Ecol Econ, 2004, 51(1–2): 31-46

[36] Metz B (2001) Climate change 2001: mitigation: contribution of Working Group III to the third assessment report of the Intergovernmental Panel on Climate Change (vol 3). Cambridge University Press

[37] OECD (2015a) Aligning policies for a low-carbon economy. OECD Publishing

[38] OECD (2015b) Policy challenges for the next 50 years. OECD Publishing

[39] Pina A (2012) Supply and demand dynamics in energy systems modeling (PhD), IST

[40] Pordata (2014) Base de dados de Portugal Contemporâneo. www.pordata.pt

[41] REN, Redes Energéticas Nacionais (2014). www.ren.pt

[42] Rivers N, Jaccard M. Combining top-down and bottom-up approaches to energy-economy modeling using discrete choice methods. Energy J, 2005, 26: 183-106

[43] Rivers Nic, Jaccard Mark. Useful models for simulating policies to induce technological change. Energy Policy, 2006, 34(15): 2038-2047

[44] Rutherford TF, Böhringer C (2006) Combining top-down and bottom-up in energy policy analysis: a decomposition approach, Discussion Paper No. 06-007, ftp://ftp.zew.de/pub/zewdocs/dp/dp06007.pdf

[45] Silva P (2014) Clearing the cloudy crystal balls: hybrid modelling for energy and climate change mitigation scenarios—a case study for Portugal (PhD), FCT-UNL

[46] Silva S, Soares I, Afonso Ó (2010) E3 Models Revisited. Universidade do Porto, Faculdade de Economia do Porto

[47] Sutherland RJ (1991) Market barriers to energy-efficiency investments. Energy J 15–34

Funding

Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa