Retraction: Dinamik Tüketici Talep Yönetimi Yapabilen Blokzincir/Kripto Para Tabanlı Elektrik Piyasası İşletme Modeli

Year 2022, Issue: 36, 322 - 322, 31.05.2022

Alper Özpınar

This is a retraction to: Dinamik Tüketici Talep Yönetimi Yapabilen Blokzincir/Kripto Para Tabanlı Elektrik Piyasası İşletme Modeli https://dergipark.org.tr/en/pub/ejosat/issue/56356/780683

Retraction Note

Yayının farklı bir sayıda yayınlanma tercihinden kaynaklı olarak geri çekilmiştir.

Abstract

Günümüzde elektrik enerjisi piyasası, en genel ve ideal tanımlaması ile tüketiciler ve üreticiler arasındaki arz-talep dengesinin oluşturulması, en uygun fiyatlamanın yapılarak piyasaya sunulması ve tüketilmesi ve enerji kaynaklarının hem üretimde hem de tüketimde farklı kontrol ve denetim araçları ile kontrol edilmesiyle oluşmaktadır. Bu piyasalara ülkelere göre serbest piyasa koşullarının oluşması için gerekli hukuki düzenlemeler yapılmaktadır. Bu düzenlemlerde temel amaç, elektrik enerjisi gibi insan yaşamındaki toplumsal yaşam zamanlarına bağlı tüketim ve sanayii elektrik kullanımı ile ilgili genel bir denge kurulmasının sağlanarak enerjinin en verimli şekilde tüketilmesini sağlamaktır. Özellikle fosil yakıtlara dayalı enerji üretimi yerine yenilenebilir enerji kaynaklarına dayalı temiz enerji üretimi için tüketici tarafındaki enerji talebini kontrol edebilmek ve bu talebe yönelik olarak en uygun üretim senaryolarını ve fiyatlandırma optimizasyonunu yapmak çok önemli bir konu haline gelmiştir. Özellikle 2020 yılı içerisinde tüm dünyayı etkileyen pandemi süreci ile birlikte geleneksel tüketici davranışları ev tipi ve sanayii tipi tüketimin trendlerinin değişmesine neden olmuştur. Bu makalede tüketicilerin taleplerini bireysel ve tüketim senaryolarına göre segmente ederek dinamik fiyatlandırma yapan ama bunu toplu olarak merkezi sistemde düzenleyerek talep tarafındaki dalgalanmaları en aza indirerek Gün İçi, Gün Öncesi ve Dengeleme Güç Piyasalarına yönelik yeni nesil piyasa işletme modeli ve bu modelin işletilmesinde kullanılacak olan blokzincir tabanlı teklif güvenliği ve tüketicilerin çif taraflı enerji kullanımlarına yönelik önerilen kripto para kWhCoin anlatılmaktadır.

Keywords

Talep Tarafı Yönetimi, Talep Katılımı, Blokzincir, Elektrik Piyasası, Grup Tarifesi, kWhCoin

Retraction: Blockchain / Crypto Money Based Electricity Market Business Model with Dynamic Consumer Demand Side Management

This is a retraction to: Dinamik Tüketici Talep Yönetimi Yapabilen Blokzincir/Kripto Para Tabanlı Elektrik Piyasası İşletme Modeli https://dergipark.org.tr/en/pub/ejosat/issue/56356/780683

Retraction Note

Abstract

The electricity market is formed by establishing the supply-demand balance between consumers and producers, by making the most appropriate pricing and controlling the energy sources with different control and supervision tools in both production and consumption. Nowadays, necessary legal arrangements are made in different countries to create free market conditions. In these arrangements, the main purpose is to provide a general balance regarding consumption and industrial electricity usage related to community life time zones in order to consume energy in the most efficient way. It has become a very important issue to control the energy demand on the consumer side and to optimize the most suitable production scenarios and pricing for this demand, especially for clean energy production based on renewable energy sources in order to replace energy production based on fossil fuels. Especially with the pandemic process affecting the whole world in 2020, traditional consumer behavior caused changes in domestic and industrial consumption trends. In this article, a new generation market operating model for the Intraday, Day-Ahead and Balancing Power Markets and blockchain-based to be used in the operation of this model by making dynamic pricing by segmenting the demands of the consumers according to individual and consumption scenarios, but by organizing this collectively in the central system, minimizing the fluctuations on the demand side. The recommended cryptocurrency kWhCoin for bid security and consumer two-way energy usage is described. 

Keywords

Demand Side Management, Demand Response, Blockchain, Cryptomoney, Electricity Market, Group Tariff, kWhCoin

References

• Acar, B., Selcuk, O., & Dastan, S. A. (2019). The merit order effect of wind and river type hydroelectricity generation on Turkish electricity prices. Energy Policy, 132, 1298–1319. https://doi.org/https://doi.org/10.1016/j.enpol.2019.07.006
• Aghajani, G. R., Shayanfar, H. A., & Shayeghi, H. (2017). Demand side management in a smart micro-grid in the presence of renewable generation and demand response. Energy, 126, 622–637.
• Albadi, M. H., & El-Saadany, E. F. (2007). Demand response in electricity markets: An overview. 2007 IEEE Power Engineering Society General Meeting, 1–5. IEEE.
• Albadi, M. H., & El-Saadany, E. F. (2008). A summary of demand response in electricity markets. Electric Power Systems Research, 78(11), 1989–1996.
• Androulaki, E., Barger, A., Bortnikov, V., Cachin, C., Christidis, K., De Caro, A., … Manevich, Y. (2018). Hyperledger fabric: a distributed operating system for permissioned blockchains. Proceedings of the Thirteenth EuroSys Conference, 1–15.
• Atzeni, I., Ordóñez, L. G., Scutari, G., Palomar, D. P., & Fonollosa, J. R. (2012). Demand-side management via distributed energy generation and storage optimization. IEEE Transactions on Smart Grid, 4(2), 866–876.
• Aydar, M., & Çetin, S. (2020). Blokzincir Teknolojisinin Sağlık Bilgi Sistemlerinde Kullanımı. European Journal of Science and Technology, (19), 533–538. https://doi.org/10.31590/ejosat.735052
• Badr, B., Horrocks, R., & Wu, X. B. (2018). Blockchain By Example: A developer’s guide to creating decentralized applications using Bitcoin, Ethereum, and Hyperledger. Packt Publishing Ltd.
• Berges, M., Goldman, E., Matthews, H. S., & Soibelman, L. (2009). Learning systems for electric consumption of buildings. In Computing in Civil Engineering (2009) (pp. 1–10).
• Bianco, V., Manca, O., & Nardini, S. (2009). Electricity consumption forecasting in Italy using linear regression models. Energy, 34(9), 1413–1421.
• Cachin, C. (2016). Architecture of the hyperledger blockchain fabric. Workshop on Distributed Cryptocurrencies and Consensus Ledgers, 310(4).
• Çetinkaya, M., Başaran, A. A., & Bağdadioğlu, N. (2015). Electricity reform, tariff and household elasticity in Turkey. Utilities Policy, 37, 79–85. https://doi.org/https://doi.org/10.1016/j.jup.2015.06.003
• Crosby, M., Pattanayak, P., Verma, S., & Kalyanaraman, V. (2016). Blockchain technology: Beyond bitcoin. Applied Innovation, 2(6–10), 71.
• del Río González, P. (2008). Ten years of renewable electricity policies in Spain: An analysis of successive feed-in tariff reforms. Energy Policy, 36(8), 2917–2929.
• Dong, B., Li, Z., Rahman, S. M. M., & Vega, R. (2016). A hybrid model approach for forecasting future residential electricity consumption. Energy and Buildings, 117, 341–351.
• Ediger, V. Ş., Kirkil, G., Çelebi, E., Ucal, M., & Kentmen-Çin, Ç. (2018). Turkish public preferences for energy. Energy Policy, 120, 492–502. https://doi.org/https://doi.org/10.1016/j.enpol.2018.05.043
• Elektrik Piyasası Tarifeler Yönetmeliği. (2020). Resmi Gazete, 31160, 28. Retrieved from https://www.resmigazete.gov.tr/eskiler/2020/06/20200619-4.htm
• EPIAS Web Sitesi. (2020). Retrieved June 6, 2020, from https://www.epias.com.tr/
• Hamzaçebi, C. (2007). Forecasting of Turkey’s net electricity energy consumption on sectoral bases. Energy Policy, 35(3), 2009–2016.
• Kaytez, F., Taplamacioglu, M. C., Cam, E., & Hardalac, F. (2015). Forecasting electricity consumption: A comparison of regression analysis, neural networks and least squares support vector machines. International Journal of Electrical Power & Energy Systems, 67, 431–438.
• Köksal, E., & Ardıyok, Ş. (2018). Regulatory and market disharmony in the Turkish electricity industry. Utilities Policy, 55, 90–98. https://doi.org/https://doi.org/10.1016/j.jup.2018.10.001
• Kumar, U., & Jain, V. K. (2010). Time series models (Grey-Markov, Grey Model with rolling mechanism and singular spectrum analysis) to forecast energy consumption in India. Energy, 35(4), 1709–1716.
• Lin, B., & Liu, X. (2013). Electricity tariff reform and rebound effect of residential electricity consumption in China. Energy, 59, 240–247.
• MacPherson, R., & Lange, I. (2013). Determinants of green electricity tariff uptake in the UK. Energy Policy, 62, 920–933.
• McLoughlin, F., Duffy, A., & Conlon, M. (2013). Evaluation of time series techniques to characterise domestic electricity demand. Energy, 50, 120–130.
• Mustaçoğlu, A. F. (2018). Blockchain-Based Data Sharing and Decentralizing Privacy. European Journal of Science and Technology, (14), 235–240. https://doi.org/10.31590/ejosat.440049
• Nakamoto, S. (2019). Bitcoin: A peer-to-peer electronic cash system. Manubot.
• Nguyen, K. Q. (2008). Impacts of a rise in electricity tariff on prices of other products in Vietnam. Energy Policy, 36(8), 3145–3149.
• Ozil, E., Ugursal, V. I., Akbulut, U., & Ozpinar, A. (2008). Renewable Energy and Environmental Awareness and Opinions: A Survey of University Students in Canada, Romania, and Turkey. International Journal of Green Energy, 5(3), 174–188. https://doi.org/10.1080/15435070802107025
• Palensky, P., & Dietrich, D. (2011). Demand side management: Demand response, intelligent energy systems, and smart loads. IEEE Transactions on Industrial Informatics, 7(3), 381–388.
• Pilkington, M. (2016). Blockchain technology: principles and applications. In Research handbook on digital transformations. Edward Elgar Publishing.
• Rahman, A., Srikumar, V., & Smith, A. D. (2018). Predicting electricity consumption for commercial and residential buildings using deep recurrent neural networks. Applied Energy, 212, 372–385.
• Sajana, P., Sindhu, M., & Sethumadhavan, M. (2018). On blockchain applications: hyperledger fabric and ethereum. International Journal of Pure and Applied Mathematics, 118(18), 2965–2970.
• Sanquist, T. F., Orr, H., Shui, B., & Bittner, A. C. (2012). Lifestyle factors in US residential electricity consumption. Energy Policy, 42, 354–364.
• Siano, P. (2014). Demand response and smart grids—A survey. Renewable and Sustainable Energy Reviews, 30, 461–478.
• Swan, M. (2015). Blockchain: Blueprint for a new economy. “ O’Reilly Media, Inc.”
• Toros, H., & Aydın, D. (2018). Kısa Vadeli Elektrik Tüketiminin Sıcaklığa Bağlı Yapay Sinir Ağları ile Tahmini. European Journal of Science and Technology, (14), 393–398. https://doi.org/10.31590/ejosat.407229
• Ünsal, E., & Kocaoğlu, Ö. (2018). Blokzinciri Teknolojisi: Kullanım Alanları, Açık Noktaları ve Gelecek Beklentileri. European Journal of Science and Technology, (13), 54–64. https://doi.org/10.31590/ejosat.423676
• Valenta, M., & Sandner, P. (2017). Comparison of ethereum, hyperledger fabric and corda. No. June, 1–8.
• Weron, R. (2007). Modeling and forecasting electricity loads and prices: A statistical approach (Vol. 403). John Wiley & Sons.
• Wolde-Rufael, Y. (2006). Electricity consumption and economic growth: a time series experience for 17 African countries. Energy Policy, 34(10), 1106–1114.
• Wood, G. (2014). Ethereum: A secure decentralised generalised transaction ledger. Ethereum Project Yellow Paper, 151(2014), 1–32.
• Zeifman, M., & Roth, K. (2012). Disaggregation of home energy display data using probabilistic approach. 2012 IEEE International Conference on Consumer Electronics (ICCE), 630–631. IEEE.
• Zheng, Z., Xie, S., Dai, H.-N., Chen, X., & Wang, H. (2018). Blockchain challenges and opportunities: A survey. International Journal of Web and Grid Services, 14(4), 352–375.