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Learning Bayesian Network to Predict Group Emotion in Kindergarten by Evolutionary Computation Read chapter Read first chapter

2018 | OriginalPaper | Chapter

Optimization of Wind Power Producer Participation in Electricity Markets with Energy Storage in a Way of Energy 4.0

Authors : Isaias L. R. Gomes, Hugo M. I. Pousinho, Rui Melício, Victor M. F. Mendes

Published in: International Joint Conference SOCO’17-CISIS’17-ICEUTE’17 León, Spain, September 6–8, 2017, Proceeding

Publisher: Springer International Publishing

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Abstract

This paper proposes a problem formulation to aid as a support information management system of a wind power producer having energy storage devices and participating in electricity markets. Energy storage can play an important role in the reduction of uncertainties faced by a wind power producer. Excess of conversion of wind energy into electric energy can be stored and then released at favorable hours. Energy storage provides capability for arbitrage and increases the revenue of the wind power producers participating in electricity markets. The formulation models the wind power and the market prices as stochastic processes represented by a set of convenient scenarios. The problem is solved by a powerful stochastic mixed integer linear programming problem. A case study using data from the Iberian Electricity Market is presented to show the aid of the formulation.

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Literature
1.
Graaf, T.V.: Is OPEC dead? Oil exporters, the Paris agreement and the transition to post-carbon world. Energy Res. Soc. Sci. 23, 182–188 (2017)CrossRef
2.
Vandyck, T., Keramidas, K., Kitous, B., Vrontisi, Z.: A global stocktake of the Paris pledges: implications for energy systems and economy. Global Environ. Change 41, 46–63 (2016)CrossRef
3.
Rajgor, G.: Greater acceleration of renewables required to meet COP21 goal. Renew. Energy 17(5), 175–177 (2016)
4.
Denholm, P., Ela, E., Kirby, B., Milligan, M.: The role of energy storage with renewable electricity generation. National Renewable Energy Laboratory, Colorado, USA (2010)
5.
Beaudin, M., Zareipour, H., Schellenberglabe, A., Rosehart, W.: Energy storage for mitigating the variability of renewable electricity sources: an updated review. Energy. Sustain. Dev. 14(4), 302–314 (2010)CrossRef
6.
Divya, K.C., Østergaard, J.: Battery energy storage technology for power systems–an overview. Electr. Power Syst. Res. 79(4), 511–520 (2009)CrossRef
7.
Lang, M.: From industry 4.0 to energy 4.0. future business, models and legal relations. Digitalisierung in der Energiewirtschaft XX, Jahrestagung Institut für Berg- und Energierecht (2016)
8.
Batista, N.C., Melicio, R., Mendes, V.M.F.: Services enabler architecture for smart grid and smart living services providers under industry 4.0. Energy Build. 141, 16–27 (2017)CrossRef
9.
Batista, N.C., Melício, R., Mendes, V.M.F.: Layered smart grid architecture approach and field tests by ZigBee technology. Energy Convers. Manag. 88, 49–59 (2014)CrossRef
10.
Arsan, T.: Smart systems: from design to implementation of embedded smart systems. In: 13th International Symposium on Smart MicroGrids for Sustainable Energy Sources enabled by Photonics and IoT Sensors, Nicosia, Cyprus, pp. 59–64 (2016)
11.
Gomes, I.L.R., Pousinho, H.M.I., Melício, R., Mendes, V.M.F.: Bidding and optimization strategies for wind-PV systems in electricity markets assisted by CPS. Energy Procedia 106, 111–121 (2016)CrossRef
12.
Glesner, M., Philip, F.: Embedded systems design for smart system integration. In: IEEE Computer Society Annual Symposium on VLSI, Natal, Brazil, pp. 32–33 (2013)
13.
Martínez-Álvarez, F., Troncoso, A., Asensio-Cortés, G., Riquelme, J.C.: A survey on data mining techniques applied to electricity-related time series forecasting. Energies 8(11), 13162–13193 (2015)CrossRef
14.
Matevosyan, J., Söder, L.: Minimization of imbalance cost trading wind power on the short-term power market. IEEE Trans. Power Syst. 21(3), 1396–1404 (2006)CrossRef
15.
González-Garcia, J., Muela, R.M.R., Santos, L.M., González, A.M.: Stochastic joint optimization of wind generation and pumped-storage units in an electricity market. IEEE Trans. Power Syst. 23(2), 460–468 (2008)CrossRef
16.
Angarita, J.L., Usaola, J., Martínez-Crespo, J.: Combined hydro-wind generation bids in a pool-based electricity market. Electr. Power Syst. Res. 79(7), 1038–1046 (2009)CrossRef
17.
Sundararagavan, S., Baker, E.: Evaluating energy storage technologies for wind power integration. Sol. Energy 86(9), 2707–2717 (2012)CrossRef
18.
Hedman, K.W., Sheble, G.B.: Comparing hedging methods for wind power: using pumped storage hydro units vs. options purchasing. In: Proceedings of the International Conference on Probabilistic Methods Applied to Power Systems – PMAPS, Stockholm, Sweden, pp. 1–6 (2006)
19.
Laia, R., Pousinho, H.M.I., Melicio, R., Mendes, V.M.F.: Self-scheduling and bidding strategies of thermal units with stochastic emission constraints. Energy Convers. Manag. 89, 975–984 (2015)CrossRef
20.
Laia, R., Pousinho, H.M.I., Melicio, R., Mendes, V.M.F.: Bidding strategy of wind-thermal energy producers. Renew. Energy 99, 673–681 (2016)CrossRef
21.
Arribas, B.N., Melício, R., Teixeira, J.G., Mendes, V.M.F.: Vanadium redox flow battery storage system linked to the electric grid. Proc. ICREPQ Renew. Energy Power Qual. J. 1(14), 1025–1030 (2016)CrossRef
22.
Gomes, I.L.R., Pousinho, H.M.I., Melício, R., Mendes, V.M.F.: Stochastic coordination of joint wind and photovoltaic systems with energy storage in day-ahead market. Energy 124, 310–320 (2017)CrossRef
23.
Metadata
Title
Optimization of Wind Power Producer Participation in Electricity Markets with Energy Storage in a Way of Energy 4.0
Authors
Isaias L. R. Gomes
Hugo M. I. Pousinho
Rui Melício
Victor M. F. Mendes
Copyright Year
2018
Book
International Joint Conference SOCO’17-CISIS’17-ICEUTE’17 León, Spain, September 6–8, 2017, Proceeding

Print ISBN: 978-3-319-67179-6

Electronic ISBN: 978-3-319-67180-2

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-3-319-67180-2_9

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