Name
Abstract | ||
|---|---|---|
Plug-in Hybrid Electrical Vehicles (PHEV) are promising to improve energy efficiency and environment friendliness. However, without proper control, their charging will cause harmful impact on the power distribution grid, including load congestion and voltage drop. Instead of using centralized optimization which may need accurate predictions on key parameters, in this paper, a new decentralized random access framework is introduced to schedule the PHEV charging. The proposed distributed solution does not need accurate predictions and can be executed online. Simulation on a semi-urban residential medium voltage grid shows that our algorithm can effectively provide demand response to protect the distribution grid from bus congestion and voltage drop, and also improve its efficiency. Most importantly, this algorithm is simple to deploy. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/TSG.2013.2293733 | IEEE Trans. Smart Grid |
Keywords | Field | DocType |
power distribution control,distribution grid,voltage drop,plug-in hybrid electrical vehicles,bus congestion,hybrid electric vehicles,load congestion,demand response,semiurban residential medium voltage grid,decentralized/randomized phev charging,smart power grids,decentralized random access framework,phev charging scheduling,power distribution grid,smart grid,randomized phev charging,multivariable systems,power generation scheduling,centralized optimization,optimization,prediction algorithms | Smart grid,Load balancing (electrical power),Efficient energy use,Voltage,Demand response,Voltage drop,Electronic engineering,Control engineering,Engineering,Grid,Random access | Journal |
Volume | Issue | ISSN |
5 | 2 | 1949-3053 |
Citations | PageRank | References |
8 | 0.53 | 9 |
Authors | ||
2 | ||