SavedAdd your journal

Journals / Uluslararası Mühendislik Araştırma ve Geliştirme Dergisi / 2020 / Cilt: 12 - Sayı: 3

Bidding and Operating Planning of a Virtual Power Plant in a Day-Ahead Market

Gün Öncesi Piyasasında Yer Alan Sanal Güç Santrali için Teklif ve İşletme Planlaması

Özge Pinar AKKAŞ
Ertugrul CAM
Pages
1–10
Publication Date
2020-12-31
DOI
—
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The obtained results show that the model is applicable and the method is valid.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:In this study, it is aimed to determine the optimum bidding and operating planning of a Virtual Power Plant (VPP) in the energy market to obtain maximum profit.
📊
Key Findings & Data:For this purpose, the VPP containing a Wind Power Plant (WPP), a Photovoltaic Power Plant (PVPP), and an Energy Storage System (ESS) is composed on the IEEE 6-bus test system with Distributed Generators (DGs).
💡
Conclusion & Impact:The obtained results show that the model is applicable and the method is valid.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Sanal güç santrali · gün öncesi piyasası · optimizasyon

Abstract

In this study, it is aimed to determine the optimum bidding and operating planning of a Virtual Power Plant (VPP) in the energy market to obtain maximum profit. For this purpose, the VPP containing a Wind Power Plant (WPP), a Photovoltaic Power Plant (PVPP), and an Energy Storage System (ESS) is composed on the IEEE 6-bus test system with Distributed Generators (DGs). The bidding planning and operating scheduling of the components of the VPP participating in the Day-ahead Market (DAM) are decided hourly for a day. Thus, SGS is aimed to gain maximum profit. The proposed problem has been modeled as Mixed Integer Linear Programming (MILP) in GAMS software and solved with CPLEX solver to obtain optimum results. The obtained results show that the model is applicable and the method is valid.

Özet

Bu çalışmada, enerji piyasasında yer alan bir Sanal Güç Santralinin (SGS) maksimum kâr elde etmesi amacıyla optimum teklif ve işletme planlamasının belirlenmesi amaçlanmıştır. Bunun için, Dağıtık Üretim Sistemlerine (DÜS) sahip IEEE 6-baralı test sistemi üzerinde Rüzgâr Enerji Santrali (RES), Fotovoltaik Enerji Santrali (FVES) ve Enerji Depolama Sistemi (ESS) içeren bir SGS oluşturulmuştur. Gün Öncesi Piyasasına (GÖP) katılan bu SGS’nin piyasada vereceği tekliflerin ve bileşenlerinin işletim planlaması bir gün için saatlik olarak yapılmıştır. Böylece SGS’nin maksimum kâr elde etmesi amaçlanmıştır. Önerilen problem Karışık Tamsayı Doğrusal Programlama (KTDP) olarak GAMS yazılımında modellenmiş ve CPLEX çözücüsü ile çözülerek optimum sonuç elde edilmeye çalışılmıştır. Elde edilen sonuçlar modelin uygulanabilir olduğunu ve metotun geçerli olduğunu göstermektedir.

🔖

Cite This Article

AKKAŞ, Ö. P., CAM, E. (2020). Bidding and Operating Planning of a Virtual Power Plant in a Day-Ahead Market. Uluslararası Mühendislik Araştırma ve Geliştirme Dergisi, Cilt: 12 - Sayı: 3, 1–10. https://ajindex.com/articles/889274

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (2)

  1. Abdolrasol, M. G. M., Hannan, M. A., Mohamed, A., Amiruldin, U. A. U., Abidin, I. B. Z. & Uddin, M. N. (2018). An Optimal Scheduling Controller for Virtual Power Plant and Microgrid Integration Using the Binary Backtracking Search Algorithm. IEEE Transactions on Industry Applications, 54(3), 2834-2844. doi: 10.1109/TIA.2018.2797121 Behi, B., Baniasadi, A., Arefi, A., Gorjy, A., Jennings, P. & Pivrikas, A. (2020). Cost–Benefit Analysis of a Virtual Power Plant Including Solar PV, Flow Battery, Heat Pump, and Demand Management: AWestern Australian Case Study. Energies, 13, 2614. doi: 10.3390/en13102614 Guo, W., Liu, P. & Shu, X. (2021). Optimal dispatching of electric-thermal interconnected virtual power plant considering market trading mechanism. Journal of Cleaner Production, 279, 123446. doi: 10.1016/j.jclepro.2020.123446 Hadayeghparast, S., Farsangi, A. S. & Shayanfar H. (2019). Day-ahead stochastic multi-objective economic/emission operational scheduling of a large scale virtual power plant. Energy, 172(2019), 630-646. doi: 10.1016/j.energy.2019.01.143 Hannan, M. A., Abdolrasol, M. G. M., Faisal, M., Ker, P. J., Begum, R. A. & Hussain, A. (2019). Binary Particle Swarm Optimization for Scheduling MG Integrated Virtual Power Plant Toward Energy Saving. IEEE Access, 7, 107937-107951. doi: 10.1109/ACCESS.2019.2933010 Karimyan, P., Abedi, M., Hosseinian, S. H. & Khatami, R. (2016). Stochastic approach to represent distributed energy resources in the form of a virtual power plant in energy and reserve markets. IET Generation, Transmission & Distribution, 10(8), 1792-1804. doi: 10.1049/iet-gtd.2015.0715 Lazaroiu, G. C., Dumbrava, V., Roscia, M. & Zaninelli, D. (2015). Energy trading optimization of a Virtual Power Plant on electricity market. The 9th International Symposium on Advanced Topics in Electrical Engineering, May 7-9, 2015,
  2. Bucharest, Romania. Naval, N. & Yusta, J. M. (2020). Water-Energy Management for Demand Charges and Energy Cost Optimization of a Pumping Stations System under a Renewable Virtual Power Plant Model. Energies, 13, 2900. doi: 10.3390/en13112900 Othman, M. M., Hegazy, Y. G. & Abdelaziz, A. Y. (2017). Electrical energy management in unbalanced distribution networks using virtual power plant concept. Electric Power Systems Research, 145, 157-165. doi: 10.1016/j.epsr.2017.01.004 Ozerdem, B., Ozer, S. & Tosun, M. (2006). Feasibility study of wind farms: A case study for Izmir, Turkey. Journal of Wind Engineering and Industrial Aerodynami