106142 20220208112848.0 doi 10.1016/j.energy.2019.07.137 sideral 114817 ART-2019-114817 eng Lujano-Rojas, J.M. Contract design of direct-load control programs and their optimal management by genetic algorithm 2019 Access copy available to the general public Unrestricted A computational model for designing direct-load control (DLC) demand response (DR) contracts is presented in this paper. The critical and controllable loads are identified in each node of the distribution system (DS). Critical loads have to be supplied as demanded by users, while the controllable loads can be connected during a determined time interval. The time interval at which each controllable load can be supplied is determined by means of a contract or compromise established between the utility operator and the corresponding consumers of each node of the DS. This approach allows us to reduce the negative impact of the DLC program on consumers’ lifestyles. Using daily forecasting of wind speed and power, solar radiation and temperature, the optimal allocation of DR resources is determined by solving an optimization problem through a genetic algorithm where the energy content of conventional power generation and battery discharging energy are minimized. The proposed approach was illustrated by analyzing a system located in the Virgin Islands. Capabilities and characteristics of the proposed method in daily and annual terms are fully discussed, as well as the influence of forecasting errors. info:eu-repo/grantAgreement/ES/FEDER/POCI-01-0145-029803 info:eu-repo/semantics/openAccess by-nc-nd http://creativecommons.org/licenses/by-nc-nd/3.0/es/ 6.082 2019 THERMODYNAMICS 3 / 61 = 0.049 2019 Q1 T1 ENERGY & FUELS 20 / 112 = 0.179 2019 Q1 T1 2.166 2019 Building and Construction 2019 Q1 Civil and Structural Engineering 2019 Q1 Electrical and Electronic Engineering 2019 Q1 Management, Monitoring, Policy and Law 2019 Q1 Energy Engineering and Power Technology 2019 Q1 Fuel Technology 2019 Q1 Industrial and Manufacturing Engineering 2019 Q1 Energy (miscellaneous) 2019 Q1 info:eu-repo/semantics/article info:eu-repo/semantics/acceptedVersion Zubi, G. Dufo-López, R. Universidad de Zaragoza (orcid)0000-0002-1490-6423 Bernal-Agustín, J.L. Universidad de Zaragoza (orcid)0000-0003-2813-1240 García-Paricio, E. Universidad de Zaragoza (orcid)0000-0003-2457-0422 Catalão, J.P.S. 5009 535 Universidad de Zaragoza Dpto. Ingeniería Eléctrica Área Ingeniería Eléctrica 186 (2019), 115807 [16 pp.] Energy Energy 0360-5442 935640 http://zaguan.unizar.es/record/106142/files/texto_completo.pdf Postprint 2039139 http://zaguan.unizar.es/record/106142/files/texto_completo.jpg?subformat=icon icon Postprint oai:zaguan.unizar.es:106142 articulos driver 2022-02-08-11:24:43 ARTICLE