|Title:||Social and Economic Implications for the Smart Grids of the Future|
Vol. 10, No 1, 2017
Published date: 03-2017 (print) / 03-2017 (online)
Economics & Sociology
ISSN: 2071-789X, eISSN: 2306-3459
University of Cambridge
|Keywords:||smart grids, autonomic power system, energy policy, electricity markets, singularity, energy economics|
|JEL classification:||D40, Q41, Q47, O30|
This paper discusses the implications of autonomous self* (self-configuring, self-healing, self-optimizing and self-protecting) systems for the development of the electrical smart grids of the future. It assesses several scenarios of the future development without prioritizing any of them. The paper employs the data from the Smart Metering Electricity Customer Behaviour Trials conducted by the Commission for Energy Regulation and kindly provided by the Irish Social Science Data Archive (ISSDA) to test the consumers’ attitude toward smart meters and adaptive energy tariffs. The findings suggest that when it comes to the implementation of the new approaches to generating, supplying, and monitoring of electrical energy, most of the consumers retain the old-fashioned approach and are driven by the economic incentives. Thence, the developments of the smart grids of the future (or the system will exist beyond these smart grids) is very likely to be shaped by the economic behaviour of the optimizing rational agents on the market.
1. Abrhám, J., Bilan, Y., Krauchenia, A., & Strielkowski, W. (2015), Planning horizon in labour supply of Belarusian small entrepreneurs, Economic Research-Ekonomska Istraživanja, Vol. 28, No. 1, pp. 773-787.
2. Aksamitauskaitė, R., Sutkutė, N., Štreimikienė, D. (2014), The impact of sustainable development knowledge on competitiveness of organizations, Czech Journal of Social Sciences Business and Economics, (4), pp. 6-17.
3. Alimisis, V., Taylor, P. C. (2015), Zoning evaluation for improved coordinated automatic voltage control, IEEE Transactions on Power Systems, 30(5), pp. 2736-2746.
4. Čábelková, I., Strielkowski, W., Mirvald, M. (2015), Business influence on the mass media: a case study of 21 countries, Transformation in Business & Economics, Vol. 14, No, 1, pp. 65-75.
5. Chawla, M. and Pollitt, M. (2013), Global Trends in Electricity Transmission System Operation: Where Does the Future Lie? Electricity Journal, Vol. 26, Issue 5, pp. 65-71.
6. Janda, K., Rausser, G., & Strielkowski, W. (2013), Determinants of Profitability of Polish Rural Micro-Enterprises at the Time of EU Accession, Eastern European Countryside, Vol. 19, pp. 177-217
7. King, J. E., Jupe, S. C., Taylor, P. C. (2015), Network State-Based Algorithm Selection for Power Flow Management Using Machine Learning, IEEE Transactions on Power Systems, 30(5), pp. 2657-2664.
8. Kitapbayev, Y., Moriarty, J., Mancarella, P. (2015), Stochastic control and real options valuation of thermal storage-enabled demand response from flexible district energy systems, Applied Energy, 137, pp. 823-831.
9. Kozinets, R. V. (2002), Can consumers escape the market? Emancipatory illuminations from burning man, Journal of Consumer research, 29(1), pp. 20-38.
10. Levi, P. G., Pollitt, M. G. (2015), Cost trajectories of low carbon electricity generation technologies in the UK: A study of cost uncertainty, Energy Policy, 87, pp. 48-59.
11. Lisin, E., Strielkowski, W. (2012), It’s the end of the world (as we know it): An Economist’s perspective, International Economics Letters, 1(1), pp. 5-13.
12. Loukarakis, E., Bialek, J. W., Dent, C. J. (2015), Investigation of maximum possible OPF problem decomposition degree for decentralized energy markets, IEEE Transactions on Power Systems, 30(5), pp. 2566-2578.
13. McArthur, S. D., Taylor, P. C., Ault, G. W., King, J. E., Athanasiadis, D., Alimisis, V. D., Czaplewski, M. (2012), The autonomic power system-network operation and control beyond smart grids, In: Innovative Smart Grid Technologies (ISGT Europe), 2012, 3r
14. Milanovic, J. V., Xu, Y. (2015), Methodology for estimation of dynamic response of demand using limited data, IEEE Transactions on Power Systems, 30(3), pp. 1288-1297.
15. Moreno, R., Moreira, R., Strbac, G. (2015), A MILP model for optimising multi-service portfolios of distributed energy storage, Applied Energy, 137, pp. 554-566.
16. Nillesen, P., Pollitt, M., Witteler, E. (2014), "New utility business model: a global view", In: Sioshani, F. P. (ed.), Distributed generation and its implications for the utility industry, Oxford: Academic Press, pp. 33-47.
17. Oseni, M. O., Pollitt, M. G. (2016), The promotion of regional integration of electricity markets: Lessons for developing countries, Energy Policy, 88, pp. 628-638.
18. Papadaskalopoulos, D., Strbac, G. (2013), Decentralized participation of flexible demand in electricity markets – Part I: Market mechanism, IEEE Transactions on Power Systems, 28 (4), pp. 3658-3666.
19. Papadaskalopoulos, D., Strbac, G., Mancarella, P., Aunedi, M., Stanojevic, V. (2013), Decentralized participation of flexible demand in electricity markets – Part II: Application with electric vehicles and heat pump systems, Power Systems, IEEE Transactio
20. Piacentini, C., Alimisis, V., Fox, M., Long, D. (2015), An extension of metric temporal planning with application to AC voltage control, Artificial Intelligence, 229, pp. 210-245.
21. Pitt, J., Bourazeri, A., Nowak A., Roszczynska-Kurasinska, M., Rychwalska, A., Rodriguez Santiago, I., Lopez-Sanchez, M., Florea, M., Sanduleac, M. (2013), Transforming big data into collective awareness, IEEE Computer, 46(6), pp. 40-45.
22. Pollitt, M. G. (2012), Lessons from the history of independent system operators in the energy sector, Energy Policy, 47, pp. 32-48.
23. Revolution (2012), Revolution TV series opening introduction. NBC, retrieved from: http://www.nbc.com/revolution (accessed 28.02.2016).
24. Strbac, G., Pollitt, M., Konstantinidis, C. V., Konstantelos, I., Moreno, R., Newbery, D. and Green, R. (2014), Electricity transmission arrangements in Great Britain: time for change? Energy Policy, 73, pp. 298-311.
25. Strielkowski, W., Čábelková, I. (2015), Religion, Culture, and Tax Evasion: Evidence from the Czech Republic, Religions, Vol. 6(2), pp. 657-669.
26. Xu, Y., Milanovic, J. V. (2015), Artificial-intelligence-based methodology for load disaggregation at bulk supply point, IEEE Transactions on Power Systems, 30(2), pp. 795-803.
27. Zhou, Y., Mancarella, P., Mutale, J. (2015), Modelling and assessment of the contribution of demand response and electrical energy storage to adequacy of supply, Sustainable Energy, Grids and Networks, 3, pp. 12-23.