A bilevel approach to optimize electricity prices
DOI:
https://doi.org/10.2298/YJOR171115002AKeywords:
demand-side management, electricity market, bilevel optimization, complementary slackness conditionsAbstract
To meet unbalanced demand, an energy provider has to include costly generation technologies, which in turn results in high residential electricity prices. Our work is devoted to the application of a bilevel optimisation, a challenging class of optimisation problems, in electricity market. We propose an original demand-side management model, adapt a solution approach based on complementary slackness conditions, and provide the computational results on illustrative and real data. The goal is to optimise hourly electricity prices, taking into account consumers' behaviour and minimizing energy generation costs. By choosing new pricing policy and shifting electricity consumption from peak to off-peaks hours, the consumers might decrease their electricity payments and eventually, decrease the energy generation costs.References
Alekseeva, E., and Kochetov Y., Matheuristics and exact methods for the discrete (rp) centroid problem, in: E-G. Talbi, (ed.), Metaheuristics for bi-level optimization, Springer, 482 (2013) 189-219.
Bard, J., Practical bilevel optimization. Algorithms and applications, Dordrecht, Boston, London: Kluwer Academic Publishers, 1998.
Ben-Ayed, O., Bilevel linear programming, Comput. Oper. Res., 20 (5) (1993) 485-501.
Billups, S.C. and Murty, K., Complementarity problems, Journal of Computational and Applied Mathematics, 124 (2000) 303-318.
Bracken, J., and McGill, J., Production and marketing decisions with multiple objectives in a competitive environment, Journal of Optimization Theory and Applications, 24 (1978) 449-458.
Bracken, J., and McGill, J., Mathematical programs with optimization problems in the constraints, J. Oper. Res., 21 (1973) 37-44.
Cervilla, C., Villar, J., and Campos, F. A., Bi-level optimization of electricity tariffs and PV distributed generation investments, European Energy Market (EEM), 12th International Conference on the, IEEE, Lisbon, Portugal, 2015, 1-5.
Colson, B., Marcotte, P. and Savard, G., An overview of bilevel optimization, Ann. Oper. Res., 153 (2007) 235-256.
Dempe, S., Foundations of bilevel programming, Springer Science & Business Media, 2002.
Fortuny-Amat, J. and McCarl, B., A representation and economic interpretation of a two-level programming problem, The Journal of the Operational Research Society, 32 (9) (1981) 783-792.
Gabriel, S. A., Conejo, A. J., Fuller, J. D., Hobbs B. F., and Ruiz C., Complementarity Modeling in Energy Markets, Springer-Verlag New, York, 2013.
General Algebraic Modeling System (GAMS), http://gams.com (accessed date 01/10/2017).
Fernandez-Blanco, R., Arroyo, J.M., Alguacil, N., and Guan, X., Incorporating Price Responsive Demand in Energy Scheduling Based on Consumer Payment Minimization, IEEE Transactions on Smart Grid, 7 (2) (2016) 817-826.
Masters, G. M., Renewable and Efficient Electric Power Systems, Hoboken, NJ: Wiley, 2004.
Mohsenian-Rad, A.-H., Wong, V. W., Jatskevich, J., Schober, R., and Leon-Garcia, A., Autonomous demand-side management based on game-theoretic energy consumption scheduling for the future smart grid, IEEE Transactions on Smart Grid, 1 (3) (2010) 320-331.
Nguyen, D. T., Nguyen, H. T., and Le, L. B., Dynamic pricing design for demand response integration in power distribution networks, IEEE Transactions on Power Systems, 31 (5) (2016) 3457-3472.
Ventosa, M., Balllo, A., Ramos, A., and Rivier, M., Electricity market modeling trends, Energy Policy, 33 (2005) 897-913.
Zugno, M., Morales, J. M., Pinson, P., and Madsen, H., A bilevel model for electricity retailers participation in a demand response market environment, Energy Economics, 36 (2013) 182-197.
Downloads
Published
Issue
Section
License
Copyright (c) 2019 YUJOR
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
