DocumentCode :
1613014
Title :
Distribution network short term scheduling in Smart Grid context
Author :
Silva, M. ; Morais, H. ; Vale, Z.A.
Author_Institution :
Knowledge Eng. & Decision-Support Res. Group, Polytech. Inst. of Porto, Porto, Portugal
fYear :
2011
Firstpage :
1
Lastpage :
8
Abstract :
The large increase of Distributed Generation (DG) in Power Systems (PS) and specially in distribution networks makes the management of distribution generation resources an increasingly important issue. Beyond DG, other resources such as storage systems and demand response must be managed in order to obtain more efficient and “green” operation of PS. More players, such as aggregators or Virtual Power Players (VPP), that operate these kinds of resources will be appearing. This paper proposes a new methodology to solve the distribution network short term scheduling problem in the Smart Grid context. This methodology is based on a Genetic Algorithms (GA) approach for energy resource scheduling optimization and on PSCAD software to obtain realistic results for power system simulation. The paper includes a case study with 99 distributed generators, 208 loads and 27 storage units. The GA results for the determination of the economic dispatch considering the generation forecast, storage management and load curtailment in each period (one hour) are compared with the ones obtained with a Mixed Integer Non-Linear Programming (MINLP) approach.
Keywords :
distributed power generation; distribution networks; energy resources; genetic algorithms; integer programming; nonlinear programming; power generation dispatch; power generation economics; power generation scheduling; smart power grids; distributed generation; distribution network short term scheduling; economic dispatch; energy resource scheduling optimization; generation forecast; genetic algorithms approach; load curtailment; mixed integer nonlinear programming approach; power system simulation; smart grid context; storage management; virtual power players; Discharges; Energy resources; Fuel cells; Genetic algorithms; Optimization; Photovoltaic systems; Energy Resources Scheduling; Genetic Algorithm; Mixed Integer Non-Linear Programming;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power and Energy Society General Meeting, 2011 IEEE
Conference_Location :
San Diego, CA
ISSN :
1944-9925
Print_ISBN :
978-1-4577-1000-1
Electronic_ISBN :
1944-9925
Type :
conf
DOI :
10.1109/PES.2011.6038900
Filename :
6038900
Link To Document :
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