Title :
Market equilibrium of distribution network with alternative energy resources
Author :
Mojdehi, Mohammad Nikkhah ; Ghosh, Prosenjit ; Wilcoxen, Peter
Author_Institution :
Dept. of Electr. Eng. & Comput. Sci., Syracuse Univ., Syracuse, NY, USA
Abstract :
Electricity distribution networks are rapidly becoming more complex. Distributed generation (DG) is increasing and some DG units are intermittent renewables such as solar or wind. Moreover, plug-in electric vehicles (EVs) are expected to be deployed in large numbers over the next decade. These changes present opportunities as well as challenges for reliable and efficient operation of distribution networks. In this paper, we present a new stochastic model in which market clearing prices are endogenously determined. Potential suppliers include the main grid supply, a range of different DG technologies within the distribution network, and EVs operated in vehicle-to-grid (V2G) mode. We allow for supply uncertainties for renewable resources and also allow for uncertainties in EV availability for charging and discharging. Using stochastic optimal power flow (SOPF) based on monte-carlo simulation, we analyze the effects of operating distributed energy resources (DERs) on social welfare considering emission taxes.
Keywords :
Monte Carlo methods; distributed power generation; hybrid electric vehicles; load flow; power distribution reliability; power generation economics; power grids; power markets; pricing; renewable energy sources; stochastic processes; DG units; EV availability; Monte Carlo simulation; SOPF; V2G mode; alternative energy resources; discharging; distributed energy resources; distributed generation; electricity distribution network reliability; intermittent DER; market clearing price; market equilibrium; plug-in electric vehicles; social welfare; stochastic model; stochastic optimal power flow; supply uncertainty; vehicle-to-grid mode; Batteries; Equations; Partial discharges; Production; Smart grids; System-on-chip; Wind speed; Distributed Generation; Electric Vehicle; Gas Emission; Monte-Carlo Simulation; Renewable Energy; Stochastic Modeling;
Conference_Titel :
Smart Energy Grid Engineering (SEGE), 2013 IEEE International Conference on
Conference_Location :
Oshawa, ON
Print_ISBN :
978-1-4799-2774-6
DOI :
10.1109/SEGE.2013.6707900