A novel method for electricity price determination in deregulated markets

• Autorzy: Nwulu Nnamdi

Identyfikatory

DOI

10.15199/48.2020.11.29

Warianty tytułu

PL

Nowa metoda określania cen energii na zderegulowanym rynku

• Języki publikacji: EN

Abstrakty

EN

The aim of the Dynamic Economic Emissions Dispatch (DEED) is to determine the optimal output of committed generating units whilst minimizing the units’ fuel costs and emissions without violating practical power system operational constraints. In a deregulated market environment, the objective changes from solely minimizing fuel costs and emissions to include the maximization of the Independent System Operator’s (ISO) profit. This formulation is known as the Profit Based Dynamic Economic Emissions Dispatch (PBDEED). In this paper, the PBDEED problem is investigated for the Nigerian electricity market which is a recently liberalised market. The model is solved in the Advanced Interactive Multidimensional Modelling System (AIMMS) environment using the price penalty factor approach and a comparison is made with the weighted sum approach. Obtained results indicate the suitability of our developed model.

PL

Celem artykułu jest określenie optymalnego wyjścia powiązanych jednostek generatorów przy minimalizacji kosztów paliwa i emisji zanieczyszczeń bez wymuszania zmian w system,ie energetycznym. Przedstawiono problem PBDEED (Bazujący na zysku dynamiczny rozsył energii uwzględniający emisję zanieczyszczeń).

Słowa kluczowe

EN

dynamic economic emissions dispatch; independent system operator

PL

ekonomiczny rozsył energii; emisja zanieczyszczeń; cena energii; zderegulowany rynek

• Wydawca: Wydawnictwo SIGMA-NOT
• Czasopismo: Przegląd Elektrotechniczny
• Rocznik: 2020
• Tom: R. 96, nr 11
• Strony: 142--146
• Opis fizyczny: Bibliogr. 30 poz., rys., tab.

Twórcy

autor

Nwulu Nnamdi

• Department of Electrical & Electronic Engineering Science, University of Johannesburg, South Africa

Bibliografia

• 1. J. Jasper , Albert Aruldoss : Differential evolution with random scale factor for economic dispatch considering prohibited operating zones, PRZEGLĄD ELEKTROTECHNICZNY, ISSN 0033-2097, R. 89 NR 5/2013
• 2. N.I. Nwulu, X. Xia. A Combined Dynamic Economic Emission Dispatch and Time of Use Demand Response Mathematical Modelling Framework. Journal of Renewable and Sustainable Energy. 7: 043134, (2015)
• 3. N.I. Nwulu, X. Xia. Implementing a Model Predictive Control Strategy on the Dynamic Economic Emission Dispatch Problem with Game Theory Based Demand Response Programs, Energy. 91, 404-419, (2015)
• 4. N.I. Nwulu, Emission Constrained Bid based Dynamic Economic Dispatch using Quadratic Programming, IEEE International Conference on Energy, Communication, Data Analytics and Soft Computing (ICECDS), Chennai, India, 2017
• 5. Aurasopon, C. Takeang, Hybrid Algorithm combining Lambda Iteration and Bee Colony Optimization to Solve an Economic Dispatch Problem with Prohibited Operating Zones, PRZEGLĄD ELEKTROTECHNICZNY, ISSN 0033-2097, R. 95 NR 10/2019
• 6. N.I. Nwulu, Dynamic Economic Dispatch of Electric Power Incorporating Transmission Line Costs, IEEEInternational Conference on Energy, Communication, Data Analytics and Soft Computing (ICECDS), Chennai, India, 2017.
• 7. N.I. Nwulu, X. Xia. Multi-Objective Dynamic Economic Emission Dispatch of Electric Power Generation Integrated with Game Theory Based Demand Response Programs, Energy Conversion and Management.89, pp.963-974 (2015)
• 8. N.I. Nwulu, X. Xia, Optimal dispatch for a microgrid incorporating renewables and demand response, Renewable Energy. 101, 16-28 (2017).
• 9. N.I. Nwulu, Optimal operational dispatch of an islanded microgrid, IEEE International Conference on Domestic Use of Energy (DUE), Cape Town, South Africa. 199-203, 2017
• 10. Rajan , K. Dhayalini , S. Sathiyamoorthy, Genetic Algorithm for the coordination of wind thermal dispatch, PRZEGLĄD ELEKTROTECHNICZNY, ISSN 0033-2097, R. 90 NR 4/2014
• 11. H. Bouzeboudja, M. Maamri , M. Tandjaoui, The Use of Grey Wolf Optimizer (GWO) for Solving the Economic Dispatch Problems based on Renewable Energy in Algeria A case study of “Naama Site”, PRZEGLĄD ELEKTROTECHNICZNY, ISSN 0033-2097, R. 95 NR 6/2019
• 12. M. Gajer, Z. Handzel, Implementation of group-based genetic algorithms for economic dispatch problem in an electrical energetic system, PRZEGLĄD ELEKTROTECHNICZNY, ISSN 0033-2097, R. 90 NR 11/2014
• 13. S. Sekharan, K. Balasubramanian, Estimation of Recovery Cost with TCSC in Dynamic Economic Dispatch, PRZEGLĄD ELEKTROTECHNICZNY, ISSN 0033-2097, R. 93 NR 5/2017
• 14. K. Medles, A. Bendaoud, F. Benhamida, A. Tilmatine : Dynamic Economic Dispatch Solution with Practical Constraints Using a Recurrent neural network, PRZEGLĄD ELEKTROTECHNICZNY, ISSN 0033-2097, R. 87 NR 8/2011
• 15. H. Bouzeboudja, A. Si-Tayeb, Application of a New Metaheuristic Algorithm using Egyptian Vulture Optimization for Economic, PRZEGLĄD ELEKTROTECHNICZNY, ISSN 0033-2097, R. 95 NR 6/2019
• 16. W. Khamsen, C. Takeang, Hybrid of Lamda and Bee Colony Optimization for Solving Economic Dispatch, PRZEGLĄD ELEKTROTECHNICZNY, ISSN 0033-2097, R. 92 NR 9/2016
• 17. Aurasopon , W. Khamsen, An improved local search involving bee colony optimization using lambda iteration combined with a golden section search method to solve an economic dispatch problem, PRZEGLĄD ELEKTROTECHNICZNY, ISSN 0033-2097, R. 95 NR 1/2019.
• 18. S. Orike, D.W. Corne, Constrained Elitist Genetic Algorithm for Economic Load Dispatch: Case Study on Nigerian Power System, International Journal of Computer Applications, 76, 5, pp. 27-33 (2013).
• 19. Nercng.Org., MYTO, http://www.nercng.org/index.php/home/myto.(2018)(Accessed September 26, 2019).
• 20. O. Akintayo, Discos, MAN, NECAN, Others Disagree On MYTO Review -Sweetcrudereports". Sweetcrudereports. http://sweetcrudereports.com/2017/09/26/discos-man-necanothers-disagree-on-myto-review/. (2017) (Accessed September 26, 2019).
• 21. U. Güvença, Y. Sönmez, S. Duman, N. Yörükeren, Combined economic and emission dispatch solution using gravitational search algorithm, Scientia Iranica, 19, 6, pp. 1754-1762 (2012).
• 22. Y. Sonmez, Multi-objective environmental/economic dispatch solution with penalty factor using artificial bee colony algorithm. Scientific Research and Essays. 6, 13, pp.2824-2831 (2011).
• 23. J. Bisschop, M. Roelofs, AIMMS Language Reference, Version 3.12, Paragon Decision Technology, Haarlem, 2011.
• 24. U. Damisa, N.I. Nwulu, Y. Sun, Microgrid energy and reserve management incorporating prosumer behind-the-meter resources, IET Renewable Power Generation, Volume 12, Issue 8, 11 June 2018.
• 25. K. Musasa, N.I. Nwulu, M.N. Gitau, R.C. Bansal, Review on DC collection grids for offshore wind farms with high-voltage DC transmission system, IET Power Electronics, Volume 10, Issue 15, 15 December 2017.
• 26. N.I. Nwulu, Y. Sun, A neural network model for optimal demand management contract design, 10th International Conference on Environment and Electrical Engineering, Rome, Italy; 8-11 May 2011
• 27. S.L. Gbadamosi, N.I. Nwulu, Y. Sun, Multi-objective optimisation for composite generation and transmission expansion planning considering offshore wind power and feedin prices, IET Renewable Power Generation, Volume 12, Issue 14, 2018.
• 28. N.I. Nwulu, O.P. Agboola, Modelling and predicting electricity consumption using artificial neural networks, 11th International Conference on Environment and Electrical Engineering, EEEIC 2012; Venice; Italy; 18 -25 May 2012.
• 29. N.I. Nwulu, M. Fahrioglu, Przeglad Elektrotechniczny, Investigating a ranking of loads in avoiding potential power system outages, Volume 88, Issue 11 A, 2012.
• 30. W.T. Huang, K.C. Yao, M.K. Chen, F.Y. Wang, C.H. Zhu and Y.R. Chang, Derivation and application of a new transmission loss formula for power system economic dispatch, Energies, Volume 11, Issue 2, 2018.

Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).