Abstract:
Since electric power restructured systems caused to raise a competitive markets, using of options that provide active participation in market and maximization freedom action profit to Distribution Company is vital. Hence the purpose of this article is "maximization of distribution company profit with distributed generations units and interruptible loads" and it has been shown that how using of different contracts of load interruption beside planning of distributed generations units causes maximization of distribution company (PBUC) profit. Mixed integer nonlinear programming techniques is used to solve problems and the program implemented in GAMS software environment. The proposed model is implemented in 18-bus system and obtained results shows importance of proposed algorithm.

Abstract:
Enviromental concerns, improvements in renewable energy technologies, governmental incentives for the use of these resources, and increased T&D costs, are the main factors driving the energy sector into a new era, where considerable portions of electrical demand will be met through widespread installation of Distributed Energy Resources (DERS). The Virtual Power Plant (VPP) is a decentralized energy management system tasked to aggregate of capacity some Distributed Generations (DGS), storage facilities, and Dispachable Loads (DLS) for the purpose of energy trading and/or providing system support services. Due of stochastic behavior of the prime sources of some DGS, such of wind speed and temperature, the steady state analysis of the system with integration of such DG unit requires a probabilistic approach. in this thesis, a probabilistic Price Based Unit Commitment (PBUC) approach using Point Estimate Method (PEM) is employed to model the uncertainty in market price and generation sources, for optimal bidding of a VPP in a day-ahead electricity market. Also, the uncertainty of stochastic DGS generation handled through increasing the amount of required reserve. The proposed model allows a VPP to decide on the unit commitment of its DERS, and the optimal sale bids to the day-ahead market. The proposed optimization algorithm is applied to an 18-buses system And solved by GAMS.