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

Yıl 2020, Cilt: 12 Sayı: 3, 1 - 10, 31.12.2020

Özge Pinar Akkaş Ertugrul Cam

https://doi.org/10.29137/umagd.842476

Öz

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.

Anahtar Kelimeler

Sanal güç santrali, gün öncesi piyasası, optimizasyon, yenilenebilir enerji sistemleri, dağıtık üretim sistemleri, enerji depolama sistemi

Destekleyen Kurum

Kırıkkale Üniversitesi Bilimsel Araştırma Projeleri Koordinasyon Birimi

Proje Numarası

2018/009

Teşekkür

Bu çalışma Kırıkkale Üniversitesi Bilimsel Araştırma Projeleri Koordinasyon Birimi tarafından (2018/009) nolu BAP projesi ile desteklenmiştir.

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

Öz

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.

Anahtar Kelimeler

Virtual power plant, day-ahead market, optimization, renewable energy systems, distributed generators, energy storage system

Proje Numarası

2018/009

Kaynakça

• 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, 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 Aerodynamics, 94 (2006), 725–743. doi: 10.1016/j.jweia.2006.02.004
• Rahimi, M., Ardakani, F. J. & Ardakani, A. J. (2021). Optimal stochastic scheduling of electrical and thermal renewable and non-renewable resources in virtual power plant. International Journal of Electrical Power & Energy Systems, 127, 106658. doi: 10.1016/j.ijepes.2020.106658
• Sadeghi, S., Jahangir, H., Vatandoust, B., Golkar, M. A., Ahmadian, A. & Elkamel, A. (2021). Optimal bidding strategy of a virtual power plant in day-ahead energy and frequency regulation markets: A deep learning-based approach. International Journal of Electrical Power & Energy Systems, 127, 106646. doi: 10.1016/j.ijepes.2020.106646
• Sadeghian, O., Shotorbani A. M. & Mohammadi-Ivatloo, B. (2019). Generation maintenance scheduling in virtual power plants. IET Generation, Transmission & Distribution, 13(12), 2584-2596. doi: 10.1049/iet-gtd.2018.6751
• Vahedipour-Dahraie, M., Rashidizadeh-Kermani, H., Anvari-Moghaddam, A., & Siano, P. (2020). Risk-averse probabilistic framework for scheduling of virtual power plants considering demand response and uncertainties. Electrical Power and Energy Systems, 121 (2020), 106126.
• Vahedipour-Dahraie, M., Rashidizade-Kermani, H, Shafie-khah, M. & Catalão, J. P. S. (2020). Risk-Averse Optimal Energy and Reserve Scheduling for Virtual Power Plants Incorporating Demand Response Programs. IEEE Transactions on Smart Grid, doi: 10.1109/TSG.2020.3026971
• Wei, C., Xu, J., Liao, S., Sun, Y., Jiang, Y., Ke, D., Zhang, Z. & Wang, J. (2018). A bi-level scheduling model for virtual power plants with aggregated thermostatically controlled loads and renewable energy. Applied Energy, 224, 659-670. doi: 10.1016/j.apenergy.2018.05.032
• Wozabal, D. & Rameseder, G. (2020). Optimal bidding of a virtual power plant on the Spanish day-ahead and intraday market for electricity. European Journal of Operational Research, 280(2), 639-655.