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Dynamic Price Control Using Pole Placement Method in Smart Grids

Year 2021, Volume: IDAP-2021 : 5th International Artificial Intelligence and Data Processing symposium Issue: Special, 411 - 421, 20.10.2021
https://doi.org/10.53070/bbd.982884

Abstract

Energy has been one of the most important concepts that we cannot remove from our lives with its many uses, from transportation, warming, and enlightenment to the tourism sector, being at the beginning of the most basic requirements for humanity for centuries. Renewable energy is a resource that does not decrease according to the increase of the population, can be obtained naturally on earth, can create an alternative solution to energy shortages and several problems. The concept of a smart grid, which provides an advantage for the use of renewable energy sources, ensures that the energy network can be controlled in the future under conditions of intermittent energy production and instantaneous demand. With the increase in distributed production in smart grids, production and consumption conditions have paved the way for energy pricing to be dynamic. In this study, price balancing was achieved by dynamic electricity pricing, which is one of the methods of achieving autonomous control in smart grids and obtaining energy safely. For this purpose, the coefficients of the Proportional-Integral-Derivative (PID) controller obtained using the pole placement method are modeled in the MATLAB/SIMULINK program with the energy supply-demand scenario. In order to examine the effect of change in energy demand on price, a temporary peak and fall are given to energy demand. According to changing demand conditions, the PID controller has been shown to provide price balance, regulate energy price online and maintain energy balance.

References

  • [1] EkoYapı (2014, Ocak 28). Akıllı Şebeke Nedir. Grapido Yayıncılık. https://www.ekoyapidergisi.org/354-akilli-sebeke-nedir.html. Accessed 10.08.2021
  • [2] Alagöz, B., Kaygusuz, A. (2014). Kapalı çevrim kesir dereceli PI kontrolör ile dinamik enerji fiyatı kontrolü ve akıllı şebekelerde otomatik enerji arz-talep dengelemesi uygulaması, Kocaeli, 535-539.
  • [3] Alagoz BB, Kaygusuz A. (2016) Dynamic energy pricing by closed-loop fractional order PI control system and energy balancing in smart grid energy markets. Transactions of the Institute of Measurement and Control; Vol 38(5): 565-578.
  • [4] S.S.S.R. Depuru, L. Wang, V. Devabhaktuni, (2011) Smart meters for power grid: Challenges, issues, advantages and status, Renewable and Sustainable Energy Reviews, Cilt 15, s:2736–2742
  • [5] Amin SM, Wollenberg BF, (2005) Toward a smart grid: power delivery for the 21st century. IEEE Power and Energy Magazine Vol (3): 34-41.
  • [6] Albert M, Vincent B, Maurice GCB, Johann LH, Gerard JMS (2009) Domestic energy management methodology for optimizing efficiency in smart grids. IEEE Bucharest PowerTech:1-7.
  • [7] Ayompe, L., Duffy, A., McCormack, S., & Conlon, M. (2010) Validated real-time energy models for smallscale grid-connected PV-systems. Energy, vol.36, no.10, pp.4086-4091.
  • [8] Prasad, A. Rajendra & Natarajan, E., (2006) "Optimization of integrated photovoltaic–wind power generation systems with battery storage," Energy, Elsevier, vol. 31(12), pages 1943-1954.
  • [9] Lund, Henrik, 2005. "Large-scale integration of wind power into different energy systems," Energy, Elsevier, vol. 30(13), pages 2402-2412.
  • [10] B.B. Alagoz, A. Kaygusuz, M. Akcin, S. Alagoz, (2013) “A closed-loop energy price controlling method for real-time energy balancing in a smart grid energy market,” Energy, Cilt:59, s:95-104.
  • [11] A.P. Sanghvi (1989) “Flexible strategies for load/demand management using dynamic pricing,” Power Systems, IEEE Transactions on, Cilt:4, No:1, s:83-93.
  • [12] K. Spees, L.B. Lave (2008) “Impacts of responsive load in PJM: load shifting and real time pricing,” Energy Journal Cilt:29, s:101-122.
  • [13] P. Andre, S. Carlos, F. Paulo (2011) “The impact of demand side management strategies in the penetration of renewable electricity,” Energy, Cilt:41, s:128-137.
  • [14] Yüce A., Tan N. (2014) Zaman Gecikmeli Kontrol Sistemleri için LabVIEW ile PI Kontrolör Tasarımı. ISITES, Karabük, 237-246.
  • [15] Elektrik port (2014, Mart 27). PID Denetleyiciler. https://www.elektrikport.com/makale-detay/pid-denetleyiciler/11787#ad-image-0 Accessed 9.08.2021
  • [16] Zehir, M. A., Bağrıyanık, M. (2010). Akıllı Şebekelerde Gelişmiş Yerel Talep Yönetimi. V.Enerji Verimliliği Ve Kalitesi Sempozyumu, Kocaeli, 14-18.

Akıllı Şebekelerde Kutup Yerleştirme Metodu Kullanarak Dinamik Fiyat Kontrolü

Year 2021, Volume: IDAP-2021 : 5th International Artificial Intelligence and Data Processing symposium Issue: Special, 411 - 421, 20.10.2021
https://doi.org/10.53070/bbd.982884

Abstract

Enerji, çağlar boyunca insanoğlu için en temel gereksinimlerinin başında gelip; ulaşım, ısınma ve aydınlanmadan turizm sektörüne kadar birçok kullanım alanıyla hayatımızdan çıkaramayacağımız en önemli kavramlardan biri olmuştur. Yenilenebilir enerji ise nüfusun artmasına göre azalmayan, yeryüzünde doğal olarak elde edilebilen, enerji yetersizliği ve birtakım problemlere alternatif çözüm oluşturabilecek kaynaklardır. Yenilenebilir enerji kaynaklarının kullanımı için avantaj sağlayan akıllı şebeke kavramı gelecekte enerjinin aralıklı üretim ve anlık olarak değişen talep koşulları altında enerji ağının kontrol edilebilir olmasını sağlamaktadır. Akıllı şebekelerde dağıtık üretimin de artmasıyla birlikte üretim ve tüketim koşulları enerji fiyatlandırmasının dinamik bir yapıda olmasının önünü açmıştır. Bu çalışmada akıllı şebekelerde otonom kontrolü sağlanabilen ve güvenli bir şekilde enerji elde etme yöntemlerinden biri olan, dinamik elektrik fiyatlandırması yapılarak fiyat dengelenmesi sağlanmıştır. Bu amaçla kutup yerleştirme metodu kullanılarak elde edilen Oransal-İntegral-Türev (PID) kontrolörün katsayıları enerji arz-talep senaryosu ile MATLAB/SIMULINK ortamında modellenmiştir. Enerji talebinin değişiminin fiyat üzerindeki etkisinin incelenmesi için enerji talebine anlık olarak zirve ve düşüş verilmiştir. Değişen talep koşullarına göre PID kontrolörün fiyat dengesini sağladığı, enerji fiyatını çevrimiçi olarak düzenlediği ve enerji dengesini koruduğu görülmüştür.

References

  • [1] EkoYapı (2014, Ocak 28). Akıllı Şebeke Nedir. Grapido Yayıncılık. https://www.ekoyapidergisi.org/354-akilli-sebeke-nedir.html. Accessed 10.08.2021
  • [2] Alagöz, B., Kaygusuz, A. (2014). Kapalı çevrim kesir dereceli PI kontrolör ile dinamik enerji fiyatı kontrolü ve akıllı şebekelerde otomatik enerji arz-talep dengelemesi uygulaması, Kocaeli, 535-539.
  • [3] Alagoz BB, Kaygusuz A. (2016) Dynamic energy pricing by closed-loop fractional order PI control system and energy balancing in smart grid energy markets. Transactions of the Institute of Measurement and Control; Vol 38(5): 565-578.
  • [4] S.S.S.R. Depuru, L. Wang, V. Devabhaktuni, (2011) Smart meters for power grid: Challenges, issues, advantages and status, Renewable and Sustainable Energy Reviews, Cilt 15, s:2736–2742
  • [5] Amin SM, Wollenberg BF, (2005) Toward a smart grid: power delivery for the 21st century. IEEE Power and Energy Magazine Vol (3): 34-41.
  • [6] Albert M, Vincent B, Maurice GCB, Johann LH, Gerard JMS (2009) Domestic energy management methodology for optimizing efficiency in smart grids. IEEE Bucharest PowerTech:1-7.
  • [7] Ayompe, L., Duffy, A., McCormack, S., & Conlon, M. (2010) Validated real-time energy models for smallscale grid-connected PV-systems. Energy, vol.36, no.10, pp.4086-4091.
  • [8] Prasad, A. Rajendra & Natarajan, E., (2006) "Optimization of integrated photovoltaic–wind power generation systems with battery storage," Energy, Elsevier, vol. 31(12), pages 1943-1954.
  • [9] Lund, Henrik, 2005. "Large-scale integration of wind power into different energy systems," Energy, Elsevier, vol. 30(13), pages 2402-2412.
  • [10] B.B. Alagoz, A. Kaygusuz, M. Akcin, S. Alagoz, (2013) “A closed-loop energy price controlling method for real-time energy balancing in a smart grid energy market,” Energy, Cilt:59, s:95-104.
  • [11] A.P. Sanghvi (1989) “Flexible strategies for load/demand management using dynamic pricing,” Power Systems, IEEE Transactions on, Cilt:4, No:1, s:83-93.
  • [12] K. Spees, L.B. Lave (2008) “Impacts of responsive load in PJM: load shifting and real time pricing,” Energy Journal Cilt:29, s:101-122.
  • [13] P. Andre, S. Carlos, F. Paulo (2011) “The impact of demand side management strategies in the penetration of renewable electricity,” Energy, Cilt:41, s:128-137.
  • [14] Yüce A., Tan N. (2014) Zaman Gecikmeli Kontrol Sistemleri için LabVIEW ile PI Kontrolör Tasarımı. ISITES, Karabük, 237-246.
  • [15] Elektrik port (2014, Mart 27). PID Denetleyiciler. https://www.elektrikport.com/makale-detay/pid-denetleyiciler/11787#ad-image-0 Accessed 9.08.2021
  • [16] Zehir, M. A., Bağrıyanık, M. (2010). Akıllı Şebekelerde Gelişmiş Yerel Talep Yönetimi. V.Enerji Verimliliği Ve Kalitesi Sempozyumu, Kocaeli, 14-18.
There are 16 citations in total.

Details

Primary Language English
Subjects Software Testing, Verification and Validation
Journal Section PAPERS
Authors

Zehva Yalçınöz 0000-0003-1574-7556

Asım Kaygusuz 0000-0003-2905-1816

Publication Date October 20, 2021
Submission Date August 14, 2021
Acceptance Date October 10, 2021
Published in Issue Year 2021 Volume: IDAP-2021 : 5th International Artificial Intelligence and Data Processing symposium Issue: Special

Cite

APA Yalçınöz, Z., & Kaygusuz, A. (2021). Dynamic Price Control Using Pole Placement Method in Smart Grids. Computer Science, IDAP-2021 : 5th International Artificial Intelligence and Data Processing symposium(Special), 411-421. https://doi.org/10.53070/bbd.982884

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