000106142 001__ 106142
000106142 005__ 20220208112848.0
000106142 0247_ $$2doi$$a10.1016/j.energy.2019.07.137
000106142 0248_ $$2sideral$$a114817
000106142 037__ $$aART-2019-114817
000106142 041__ $$aeng
000106142 100__ $$aLujano-Rojas, J.M.
000106142 245__ $$aContract design of direct-load control programs and their optimal management by genetic algorithm
000106142 260__ $$c2019
000106142 5060_ $$aAccess copy available to the general public$$fUnrestricted
000106142 5203_ $$aA 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.
000106142 536__ $$9info:eu-repo/grantAgreement/ES/FEDER/POCI-01-0145-029803
000106142 540__ $$9info:eu-repo/semantics/openAccess$$aby-nc-nd$$uhttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
000106142 590__ $$a6.082$$b2019
000106142 591__ $$aTHERMODYNAMICS$$b3 / 61 = 0.049$$c2019$$dQ1$$eT1
000106142 591__ $$aENERGY & FUELS$$b20 / 112 = 0.179$$c2019$$dQ1$$eT1
000106142 592__ $$a2.166$$b2019
000106142 593__ $$aBuilding and Construction$$c2019$$dQ1
000106142 593__ $$aCivil and Structural Engineering$$c2019$$dQ1
000106142 593__ $$aElectrical and Electronic Engineering$$c2019$$dQ1
000106142 593__ $$aManagement, Monitoring, Policy and Law$$c2019$$dQ1
000106142 593__ $$aEnergy Engineering and Power Technology$$c2019$$dQ1
000106142 593__ $$aFuel Technology$$c2019$$dQ1
000106142 593__ $$aIndustrial and Manufacturing Engineering$$c2019$$dQ1
000106142 593__ $$aEnergy (miscellaneous)$$c2019$$dQ1
000106142 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/acceptedVersion
000106142 700__ $$aZubi, G.
000106142 700__ $$0(orcid)0000-0002-1490-6423$$aDufo-López, R.$$uUniversidad de Zaragoza
000106142 700__ $$0(orcid)0000-0003-2813-1240$$aBernal-Agustín, J.L.$$uUniversidad de Zaragoza
000106142 700__ $$0(orcid)0000-0003-2457-0422$$aGarcía-Paricio, E.$$uUniversidad de Zaragoza
000106142 700__ $$aCatalão, J.P.S.
000106142 7102_ $$15009$$2535$$aUniversidad de Zaragoza$$bDpto. Ingeniería Eléctrica$$cÁrea Ingeniería Eléctrica
000106142 773__ $$g186 (2019), 115807 [16 pp.]$$pEnergy$$tEnergy$$x0360-5442
000106142 8564_ $$s935640$$uhttps://zaguan.unizar.es/record/106142/files/texto_completo.pdf$$yPostprint
000106142 8564_ $$s2039139$$uhttps://zaguan.unizar.es/record/106142/files/texto_completo.jpg?subformat=icon$$xicon$$yPostprint
000106142 909CO $$ooai:zaguan.unizar.es:106142$$particulos$$pdriver
000106142 951__ $$a2022-02-08-11:24:43
000106142 980__ $$aARTICLE