Abstract
In this chapter, the power procurement problem of a large consumer under power price uncertainty is solved using information gap decision theory (IGDT). In contrast to other uncertainty modeling methods, the IGDT method makes it possible to model the positive and negative impacts of uncertainty through different strategies. To do so, the risk of the power procurement process of a large consumer is assessed considering the opportunity and robustness functions of the IGDT method, and three different strategies, risk-averse, risk-neutral, and risk-taker, are derived. It should be noted that the problem is formulated as mixed integer nonlinear programming and solved using GAMS programming software.
Based on the obtained results, in the risk-averse strategy, the large consumer is 12.16% robust against the power price uncertainty without implementing demand response program (DRP) by paying $42,000 to meet electricity demand. In addition, considering $40,000 as the procurement cost, 11.4% robustness is obtained against the power price increase in the pool market due to implement TOU-DRP. Also, in the risk-taker strategy, for a 15% power price reduction in the market, the large consumer’s costs will be $37,250 and $35,700 in cases without and with DRP, respectively, which means DRP will reduce procurement costs by about 4.2%.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Y. Ben-Haim, Y. Ben-Haim, Info-Gap Decision Theory: Decisions Under Severe Uncertainty (Academic Press, New York, 2006)
A.J. Conejo, M. Carrión, J.M. Morales, Decision Making Under Uncertainty in Electricity Markets, vol 153 (Springer, Boston, 2010)
I. Ahmadian, O. Abedinia, N. Ghadimi, Fuzzy stochastic long-term model with consideration of uncertainties for deployment of distributed energy resources using interactive honey bee mating optimization. Front. Energy 8(4), 412–425 (2014)
Z. Chen, L. Wu, Y. Fu, Real-time price-based demand response management for residential appliances via stochastic optimization and robust optimization. IEEE Trans. Smart Grid 3(4), 1822–1831 (2012)
S. Nojavan, H. Ghesmati, K. Zare, Robust optimal offering strategy of large consumer using IGDT considering demand response programs. Electr. Power Syst. Res. 130, 46–58 (2016)
A. Najafi-Ghalelou, S. Nojavan, K. Zare, Heating and power hub models for robust performance of smart building using information gap decision theory. Int. J. Electr. Power Energy Syst. 98, 23–35 (2018)
S. Nojavan, K. Zare, M.A. Ashpazi, A hybrid approach based on IGDT–MPSO method for optimal bidding strategy of price-taker generation station in day-ahead electricity market. Int. J. Electr. Power Energy Syst. 69, 335–343 (2015)
S. Nojavan, K. Zare, M.R. Feyzi, Optimal bidding strategy of generation station in power market using information gap decision theory (IGDT). Electr. Power Syst. Res. 96, 56–63 (2013)
S. Nojavan, K. Zare, Risk-based optimal bidding strategy of generation company in day-ahead electricity market using information gap decision theory. Int. J. Electr. Power Energy Syst. 48, 83–92 (2013)
K. Zare, M.P. Moghaddam, M.K. Sheikh El Eslami, Electricity procurement for large consumers based on information gap decision theory. Energy Policy 38(1), 234–242 (2010)
K. Zare, M.P. Moghaddam, M.K. Sheikh El Eslami, Demand bidding construction for a large consumer through a hybrid IGDT-probability methodology. Energy 35(7), 2999–3007 (2010)
M. Alipour, K. Zare, B. Mohammadi-Ivatloo, Optimal risk-constrained participation of industrial cogeneration systems in the day-ahead energy markets. Renew. Sust. Energ. Rev. 60, 421–432 (2016)
S. Shafiee, H. Zareipour, A.M. Knight, N. Amjady, B. Mohammadi-Ivatloo, Risk-constrained bidding and offering strategy for a merchant compressed air energy storage plant. IEEE Trans. Power Syst. 32, 1–1 (2016)
A. Najafi-Ghalelou, S. Nojavan, K. Zare, Information gap decision theory-based risk-constrained scheduling of smart home energy consumption in the presence of solar thermal storage system. Sol. Energy 163, 271–287 (2018)
J. Zhao, C. Wan, Z. Xu, J. Wang, Risk-based day-ahead scheduling of electric vehicle aggregator using information gap decision theory. IEEE Trans. Smart Grid 8(4), 1609–1618 (2017)
A. Rabiee, S. Nikkhah, A. Soroudi, E. Hooshmand, Information gap decision theory for voltage stability constrained OPF considering the uncertainty of multiple wind farms. IET Renew. Power Gen. 11(5), 585–592 (2017)
A. Kazemi, S. Dehghan, N. Amjady, Multi-objective robust transmission expansion planning using information-gap decision theory and augmented ɛ-constraint method. IET Gener. Transm. Distrib. 8(5), 828–840 (2014)
X. Cao, J. Wang, B. Zeng, A chance constrained information-gap decision model for multi-period microgrid planning. IEEE Trans. Power Syst. 33(3), 2684–2695 (2018)
D. Ke, F. Shen, C.Y. Chung, C. Zhang, J. Xu, Y. Sun, Application of information gap decision theory to the design of robust wide-area power system stabilizers considering uncertainties of wind power. IEEE Trans. Sustain. Energy 9(2), 805–817 (2018)
M. Eslami, H.A. Moghadam, H. Zayandehroodi, N. Ghadimi, A new formulation to reduce the number of variables and constraints to expedite scuc in bulky power systems. Proc. Natl. Acad. Sci. India Sect. A: Phys. Sci., 1–11 (2018). https://doi.org/10.1007/s40010-017-0475-1
O. Abedinia, M. Bekravi, N. Ghadimi, Intelligent controller based wide-area control in power system. Int. J. Uncertainty Fuzziness Knowl. Based Syst. 25(01), 1–30 (2017)
A. Jalili, N. Ghadimi, Hybrid harmony search algorithm and fuzzy mechanism for solving congestion management problem in an electricity market. Complexity 21(S1), 90–98 (2016)
F. Jabari, S. Nojavan, B. Mohammadi-ivatloo, H. Ghaebi, H. Mehrjerdi, Risk-constrained scheduling of solar Stirling engine based industrial continuous heat treatment furnace. Appl. Therm. Eng. 128, 940–955 (2018)
M. Charwand, Z. Moshavash, Midterm decision-making framework for an electricity retailer based on information gap decision theory. Int. J. Electr. Power Energy Syst. 63, 185–195 (2014)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this chapter
Cite this chapter
Farashah, M.D. (2019). Risk-Based Energy Procurement via IGDT. In: Nojavan, S., Shafieezadeh, M., Ghadimi, N. (eds) Robust Energy Procurement of Large Electricity Consumers . Springer, Cham. https://doi.org/10.1007/978-3-030-03229-6_5
Download citation
DOI: https://doi.org/10.1007/978-3-030-03229-6_5
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-03228-9
Online ISBN: 978-3-030-03229-6
eBook Packages: EnergyEnergy (R0)