Capacity Credit Variation in Distribution Systems

Implementation of transmission access arrangements under BETTA, in the UK, has encouraged applications for offers to connect generation to the grid. Network operators have consequently been presented with a vast amount of applications before end of 2004. Boosted by governmental targets of securing 10% of electricity generation from renewable resources by 2010 and 20% by 2020 and widespread public support for renewable energy, Distributed Generators (DGs) are rapidly increasing in electrical power systems. Among the DGs, wind energy conversion systems (WECS) are emerging as the popular choice due to its mature technology and low operation and maintenance costs. This paper utilises the reliability aspects of electrical power systems to provide a probabilistic approach to determine the capacity credit (CC) of distributed generators. Monte Carlo simulations are employed to cater for the stochastic nature of the simulations and each trial is validated using the Newton-Raphson optimal load flow solution. Bernoulli trials are used to simulate the availability of network components. An algorithm to evaluate the capacity credit due to Distributed Generation (DG) connected in the network, is shown. Hence, the amount of conventional generation which can be backed off from the Bulk Supply Point (BSP) of the distribution network can be quantified. The paper further investigates some factors that have an impact on the CC recovered in the test network.