Integrating Renewable Energy and Demand Response Strategies for Cost-Effective Industrial Energy Management
Subject Areas : journal of Artificial Intelligence in Electrical Engineering
1 - Department of Electrical Engineering, Shabestar Branch, Islamic Azad University, Shabestar, Iran
Keywords: Energy Procurement, Large Industrial Consumers, Real-time Pricing, Time-Of-Use Pricing,
Abstract :
In this paper, the energy procurement of large industrial consumers with the minimum cost of alternative energy sources including the micro-turbines, bilateral contracts, power market and renewable energy sources, namely wind turbines and photovoltaic systems, is investigated. Also, the battery storage is used to increase energy efficiency. Additionally, the effects of real-time pricing demand response program (RTP-DRP) and the time-of-use demand response program (TOU-DRP) on the load curve of the large industrial consumer have been studied, which leads to the smoothing of the load curve and, as a result, reduces the cost of energy procurement of the consumer. To model the uncertainties of electricity price, consumer's load, wind speed, irradiation of sun, temperature, scenario-based probabilistic programming is proposed. The proposed scheme is modeled as mixed-integer linear programming and the global optimal is extracted using GAMS software. Comparison of the results shows that the cost of purchasing industrial consumer's energy is reduced by 12.33% and 6.23% due to the use of RTP-DRP and TOU-DRP, respectively; and also indicates the efficiency of the proposed RTP-DRP in comparison to the traditional TOU-DRP.
[1] Kirschen DS, Strbac G. Fundamentals of power system economics. John Wiley & Sons; 2004 Oct 22.
[2] Su CL, Kirschen D. Quantifying the effect of demand response on electricity markets. IEEE Transactions on Power Systems. 2009 Aug;24(3):1199-207.
[3] Arroyo JM, Conejo AJ. Multiperiod auction for a pool-based electricity market. IEEE Transactions on Power Systems. 2002 Nov;17(4):1225-31.
[4] S. Nojavan, H.A. Aalami, 2015, "Stochastic energy procurement of large electricity consumer considering photovoltaic, wind-turbine, micro-turbines, energy storage system in the presence of demand response program", Energy Conversion and Management, vol. 103, 1008-1018.
[5] S. Nojavan, K. Zare, B. Mohammadi-Ivatloo, 2017, "Optimal stochastic energy management of retailer based on selling price determination under smart grid environment in the presence of demand response program", Applied Energy, vol. 187, 449-464.
[6] Zare K, Moghaddam MP, Sheikh-El-Eslami MK. Risk-based electricity procurement for large consumers. IEEE Transactions on Power Systems. 2011 Nov;26(4):1826-35.
[7] H.A. Aalami, S. Nojavan, 2016, "Energy storage system and demand response program effects on stochastic energy procurement of large consumers considering renewable generation", IET Generation Transmission & Distribution, vol. 10, 107-114
[8] Aalami HA, Moghaddam MP, Yousefi GR. Demand response modeling considering interruptible/curtailable loads and capacity market programs. Applied Energy. 2010 Jan 1;87(1):243-50.
[9] Conejo AJ, Morales JM, Baringo L. Real-time demand response model. IEEE Transactions on Smart Grid. 2010 Dec;1(3):236-42.
[10] Nguyen DT, Negnevitsky M, De Groot M. Pool-based demand response exchange—concept and modeling. IEEE Transactions on Power Systems. 2011 Aug;26(3):1677-85.
[11] Nojavan S, allah Aalami H. Stochastic energy procurement of large electricity consumer considering photovoltaic, wind-turbine, micro-turbines, energy storage system in the presence of demand response program. Energy Conversion and Management. 2015 Oct 1;103:1008-18.
[12] Aalami HA, Nojavan S. Energy storage system and demand response program effects on stochastic energy procurement of large consumers considering renewable generation. IET Generation, Transmission & Distribution. 2016 Jan 7;10(1):107-14.
[13] Nojavan S, Zare K. Optimal energy pricing for consumers by electricity retailer. International Journal of Electrical Power & Energy Systems. 2018 Nov 30;102:401-12.
[14] Nojavan S, Zare K, Mohammadi-Ivatloo B. Application of fuel cell and electrolyzer as hydrogen energy storage system in energy management of electricity energy retailer in the presence of the renewable energy sources and plug-in electric vehicles. Energy conversion and management. 2017 Mar 15;136:404-17.
[15] Nojavan S, Zare K, Mohammadi-Ivatloo B. Selling price determination by electricity retailer in the smart grid under demand side management in the presence of the electrolyser and fuel cell as hydrogen storage system. International Journal of Hydrogen Energy. 2017 Feb 2;42(5):3294-308.
[16] Nojavan S, Zare K, Mohammadi-Ivatloo B. Risk-based framework for supplying electricity from renewable generation-owning retailers to price-sensitive customers using information gap decision theory. International Journal of Electrical Power & Energy Systems. 2017 Dec 1;93:156-70.
[17] Nojavan S, Zare K, Mohammadi-Ivatloo B. Robust bidding and offering strategies of electricity retailer under multi-tariff pricing. Energy Economics. 2017 Oct 1;68:359-72.
[18] Habib Farham, Leila Mohammadian, Hasan Alipour, Jaber Pouladi, Robust performance of photovoltaic/wind/grid based large electricity consumer, Solar Energy, Volume 174, 2018, Pages 923-932.
[19] Nojavan S, Qesmati H, Zare K, Seyyedi H. Large consumer electricity acquisition considering time-of-use rates demand response programs. Arabian Journal for Science and Engineering. 2014 Dec 1;39(12):8913-23.
[20] Ghalelou AN, Fakhri AP, Nojavan S, Majidi M, Hatami H. A stochastic self-scheduling program for compressed air energy storage (CAES) of renewable energy sources (RESs) based on a demand response mechanism. Energy conversion and management. 2016 Jul 15;120:388-96.
[21] Nojavan S, Mohammadi-Ivatloo B, Zare K. Optimal bidding strategy of electricity retailers using robust optimisation approach considering time-of-use rate demand response programs under market price uncertainties. IET Generation, Transmission & Distribution. 2015 Jan 13;9(4):328-38.
[22] Nojavan S, Ghesmati H, Zare K. Robust optimal offering strategy of large consumer using IGDT considering demand response programs. Electric Power Systems Research. 2016 Jan 1;130:46-58.
[23] Habib Farham, Leila Mohammadian, Hasan Alipour, Jaber Pouladi, Energy procurement of large industrial consumer via interval optimization approach considering peak demand management, Sustainable Cities and Society, Volume 46, 2019, 101421.
[24] The GAMS Software Website, 2018. [Online]. Available:http://www.gams.com
/dd/docs/solvers/cplex.pdf.
[25] Brooke A, Kendrick D, Meeraus A, Raman R. GAMS: A User’s Guide. Washington, DC: GAMS Development Corporation, 1998.