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Demand Response in Generation Capacity Planning Technology Roadmap: Turkey’s Quest

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Next Generation Roadmapping

Abstract

The objective of the study is to propose a roadmap for the application of demand response (DR) technologies in capacity planning. Capacity planning is aimed as part of the general DR roadmap. In this context, it is of great importance to bring the flexibility of grid-connected hydrogen production to the system, open the markets to the demand side, encourage new business models, reduce greenhouse gas emissions, build an aggregator system and create a hydrogen economy. Generation capacity planning has been studied and solved in 3 different parts: mitigation of constraints in the generation, system balancing and flexibility and optimal aggregation and dispatch DR in generation capacity planning (BPA 2014)

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References

  • Abdalla AN, Nazir MS, Tao H, Cao S, Ji R, Jiang M, Yao L (2021) Integration of energy storage system and renewable energy sources based on artificial intelligence: an overview. Journal of Energy Storage 40:102811

    Article  Google Scholar 

  • Amer M, Daim TU, Jetter A (2013) A review of scenario planning. Futures 46:23–40

    Article  Google Scholar 

  • BPA (2014) Bonneville Power Administration Demand Response Technology Roadmap, Portland Oregon USA

    Google Scholar 

  • Buhan S, Scientific T, Cinar MS (2020) Ak ı m Tahmin ve Havza Optimizasyon Modeli (ATHOM) Projesi: Güncel Geli ş meler. September

    Google Scholar 

  • Daim TU, Rueda G, Martin H, Gerdsri P (2006) Forecasting emerging technologies: Use of bibliometrics and patent analysis. Technol Forecast Soc Change 73(8):981–1012

    Article  Google Scholar 

  • Daim TU, Gerdsri N, Kockan I, Kocaoglu D (2011) Technology development envelope approach for the adoption of future powertrain technologies: A case study on ford otosan roadmapping model. J Transp Syst Eng Inf Technol 11(2):58–69

    Google Scholar 

  • Daim TU, Li X, Kim J, Simms S (2012) Evaluation of energy storage technologies for integration with renewable electricity: quantifying expert opinions. Environ Innov Soc Transit 3:29–49

    Article  Google Scholar 

  • Daim TU, Lavoie J, de Oliveira MG, Fleury AL, Oliver T, Phaal R (2018) Technology roadmapping improvement through an add-on process: Presentation and initial application. In: Technology roadmapping, vol 2. World Scientific, pp 383–424

    Chapter  Google Scholar 

  • EPIAS (2020) EPIAS-2020-Yili-Yonetim-Kurulu-Faaliyet-Raporu.pdf

    Google Scholar 

  • EUAS (2022). https://argesis.euas.gov.tr/Default.aspx?ReturnUrl=%2f

  • Farsangi AS, Hadayeghparast S, Mehdinejad M, Shayanfar H (2018) A novel stochastic energy management of a microgrid with various types of distributed energy resources in presence of demand response programs. Energy 160:257–274

    Article  Google Scholar 

  • Gao J, Xiao Y, Liu J, Liang W, Chen CP (2012) A survey of communication/networking in smart grids. Fut Gen Comput Syst 28(2):391–404

    Article  Google Scholar 

  • Gilani MA, Kazemi A, Ghasemi M (2020) Distribution system resilience enhancement by microgrid formation considering distributed energy resources. Energy 191:116442

    Article  Google Scholar 

  • Golembiewski B, Sick N, Bröring S (2015) Patterns of convergence within the emerging bioeconomy—The case of the agricultural and energy sector. Int J Innov Technol Manag 12(03):1550012

    Article  Google Scholar 

  • Harmancioglu N, Altinbilek D (2020) Water Resources of Turkey. In: Water Resources of Turkey, vol. 2

    Google Scholar 

  • Hassan MAS, Assad U, Farooq U, Kabir A, Khan MZ, Bukhari SSH et al (2022) Dynamic price-based demand response through linear regression for microgrids with renewable energy resources. Energies 15(4):1385

    Article  Google Scholar 

  • Jayachandran M, Rao KP, Gatla RK, Kalaivani C, Kalaiarasy C, Logasabarirajan C (2022) Operational concerns and solutions in smart electricity distribution systems. Util Policy 74:101329

    Article  Google Scholar 

  • Mahani K, Farzan F, Jafari MA (2017) Network-aware approach for energy storage planning and control in the network with high penetration of renewables. Appl Energy 195:974–990

    Article  Google Scholar 

  • McPherson M, Stoll B (2020) Demand response for variable renewable energy integration: a proposed approach and its impacts. Energy 197:117205

    Article  Google Scholar 

  • No P, Ih E, Tr SER (2018) Düşük Karbonlu Kalkınma i çin Çözümsel Tabanlı Strateji ve Eylem Geliştirilmesi Teknik Destek Projesi yasal ve kurumsal boşluk analizi (Boşluk Analizi Raporu)

    Google Scholar 

  • Poyrazoglu G (2021) Determination of price zones during transition from uniform to zonal electricity market: a case Study for Turkey. Energies 14(4):1014

    Article  Google Scholar 

  • Siano P (2014) Demand response and smart grids—A survey. Renew Sustain Energy Rev 30:461–478

    Article  Google Scholar 

  • TEIAS (2022) Aylık Elektrik Üretim-Tüketim Raporları. Retrieved 2 June 2022, from https://www.teias.gov.tr/aylik-elektrik-uretim-tuketim-raporlari

  • TEİAŞ (n.d.-b) Aylık Elektrik Üretim-Tüketim Raporları. https://www.teias.gov.tr/aylik-elektrik-uretim-tuketim-raporlari

  • Tran TA, Daim T (2008) A taxonomic review of methods and tools applied in technology assessment. Technol Forecast Soc Change 75(9):1396–1405

    Article  Google Scholar 

  • Tubitak MAM (2020a). https://mam.tubitak.gov.tr/en/teknoloji-transfer-ofisi/estimation-natural-energy-resources

  • Tubitak MAM (2020b). https://mam.tubitak.gov.tr/en/teknoloji-transfer-ofisi/wind-power-monitoring-and-estimation-system

  • Türkiye Sınai Kalkınma Bankası (2021) Enerji Görünümü 2021

    Google Scholar 

  • U. I. Nations (2018) Energy Transition UN Report - Towards the achievement of SDG 7 Net-zero emissions, pp 157–166

    Google Scholar 

  • Wang Y, Huang Y, Wang Y, Zeng M, Li F, Wang Y, Zhang Y (2018) Energy management of smart micro-grid with response loads and distributed generation considering demand response. J Clean Prod 197:1069–1083

    Article  Google Scholar 

  • Zakariazadeh A, Jadid S, Siano P (2014) Smart microgrid energy and reserve scheduling with demand response using stochastic optimization. Int J Electr Power Ener Syst 63:523–533

    Article  Google Scholar 

  • Zhang Q, Martín M, Grossmann IE (2019) Integrated design and operation of renewables-based fuels and power production networks. Comput Chem Eng 122:80–92

    Article  Google Scholar 

  • Zhang S, Cheng H, Li K, Tai N, Wang D, Li F (2018) Multi-objective distributed generation planning in distribution network considering correlations among uncertainties. Appl Energy 226:743–755

    Article  Google Scholar 

  • Zunnurain I, Maruf M, Islam N, Rahman M, Shafiullah GM (2018) Implementation of advanced demand side management for microgrid incorporating demand response and home energy management system. Infrastructures 3(4):50

    Article  Google Scholar 

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Correspondence to Tugrul Daim .

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Kayakutlu, G. et al. (2023). Demand Response in Generation Capacity Planning Technology Roadmap: Turkey’s Quest. In: Daim, T.U., Phaal, R., Meissner, D., Kerr, C. (eds) Next Generation Roadmapping. Science, Technology and Innovation Studies. Springer, Cham. https://doi.org/10.1007/978-3-031-38575-9_10

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