000206848 001__ 206848
000206848 005__ 20190317000133.0
000206848 020__ $$a978-1-4799-5238-0
000206848 0247_ $$2doi$$a10.1109/SusTech.2014.7046225
000206848 037__ $$aCONF
000206848 245__ $$aStochastic Day-ahead Optimal Scheduling of Active Distribution Networks with Dispersed Energy Storage and Renewable Resources
000206848 269__ $$a2014
000206848 260__ $$bIEEE$$c2014$$aPortnald, USA
000206848 336__ $$aConference Papers
000206848 520__ $$aThis paper focuses on the problem of the probabilistic optimal day-ahead scheduling of energy resources in Active Distribution Networks (ADNs). These resources include both dispersed energy storage systems (DESSs) and volatile renewable embedded generators. Technical constraints related to both energy resources and electrical network are modeled and taken into account in the proposed optimization problem. The paper first proposes a convex formulation of a specific optimal power flow (OPF) used to compute the resources schedule. Its objective function aims at achieving the minimum of the following quantities: network and DESSs losses, energy cost imported from the external grid, and deviations from the day-ahead scheduled power flow with the same external grid. In addition, the ability of using the substation transformer tap-changer is incorporated into the problem with a suitable cost function. The initial OPF formulation is then enhanced thanks to the use of the Mixed Integer Second Order Cone Programming approach in order to formulate a stochastic AC-OPF. The uncertainties of the problem are due to the forecast errors of the PV generation, load consumption and energy prices. The applicability and the effectiveness of the proposed scheduling approach are tested by using a modified version of the IEEE 34 buses test feeder.
000206848 6531_ $$aDispersed energy storage systems
000206848 6531_ $$aActive distribution networks
000206848 6531_ $$aStochastic programming
000206848 6531_ $$aConvex optimization
000206848 6531_ $$aOptimal power flow
000206848 6531_ $$aepfl-smartgrids
000206848 700__ $$0246332$$g218988$$aNick, Mostafa
000206848 700__ $$0242729$$g104759$$aCherkaoui, Rachid
000206848 700__ $$g156731$$aPaolone, Mario$$0245463
000206848 7112_ $$dJuly 24-26, 2014$$cPortland, USA$$a2014 IEEE Conference on Technologies for Sustainability (SusTech)
000206848 720_1 $$aPerkins, Ed$$eed.
000206848 773__ $$j1$$tProc. of the 2014 IEEE Conference on Technologies for Sustainability (SusTech)$$k1$$q91-96
000206848 8564_ $$uhttps://infoscience.epfl.ch/record/206848/files/2014%20-%20Nick%20et%20al%20-%20Day-ahead%20optimal%20scheduling.pdf$$zPublisher's version$$s288465$$yPublisher's version
000206848 909C0 $$xU12494$$0252423$$pDESL
000206848 909C0 $$pPWRS$$0252287
000206848 909CO $$qGLOBAL_SET$$pconf$$pSTI$$ooai:infoscience.tind.io:206848
000206848 917Z8 $$x156731
000206848 937__ $$aEPFL-CONF-206848
000206848 973__ $$rREVIEWED$$sPUBLISHED$$aEPFL
000206848 980__ $$aCONF