| This thesis examines the integration aspects of wind electric generators (WEGs) into distribution systems. The topics addressed include: a) analysis of large scale distribution systems with a large number of WEGs, b) capacitor planning in distribution system with WEGs capturing stochastic information, and c) optimal economic operation of WEGs using stochastic models.;First, a Load Flow method for distribution systems is proposed by formulating a set of equations (SOE) that model a distribution system. Irrespective of the resistance to reactance (R/X) ratio of lines in the system, the SOE preserves a strong diagonal characteristic. The SOE is then solved using a first order Newton-Raphson method. Thereafter, the proposed method is extended using the continuation power flow technique to trace the power-voltage (P-V) curves and to determine the maximum loading point and hence the voltage collapse point in a distribution system. The characteristics of the path traced by the minimum singular value of the system Jacobian in the presence and absence of shunt capacitors are also explored and reported.;Next, a new fuzzy stochastic programming (FSP) method for optimal capacitor planning in a distribution system with WEGs is proposed. The FSP model represents the objectives of capacitor cost and annual energy loss minimization and voltage constraints as fuzzy sets. The proposed FSP technique addresses limitations encountered during the planning stage of a distribution system due to uncertainties in the wind power forecasts and the annual load forecasts. This is achieved by appropriately modeling the wind power forecasts and the annual load demand forecasts with their respective probability density functions.;The later part of the thesis work examines the operation of WEGs as they optimize to bid and sell power into an electricity market through a distribution system. An optimal bidding strategy for WEGs that employ energy storage device for participation in the day-ahead unit commitment process is then proposed. A formulation with objectives to maximize returns from the market considering stochastic characteristics of the market price and the wind forecast and simultaneously minimize risks due to uncertainties in the wind power forecasts is proposed. |
