Time Based Distributed Energy Resources (DER) Hosting Capacity Analysis (HCA)

The world’s electricity demand has been increasing at a rapid pace. Due to the falling prices of Distributed Energy Resources (DERs) and the shift in focus from fossil fuels to renewable sources of many countries from fossil fuels to renewable sources, the integration of DERs is expected to see a rise in the future. This can lead to a wide range of power quality problems in the power system, such as voltage violations, overloading of distribution lines and transformers and reverse power flow. Therefore, it is important to study the effects of the integration of DER on the distribution network to mitigate these negative impacts. In this study, two algorithms have been developed based on the modified iterative method and the Particle Swarm Optimization (PSO) method for Hosting Capacity (HC) determination of a single large-scale DER and multiple DERs. These algorithms calculate the optimal HC based on six scenarios of load and DER generation profiles. The developed algorithms have been tested on the IEEE 123 bus network and their results have been compared. It has been found that the modified iterative method outperforms the PSO method for the single large-scale DER case while only the PSO method can be utilized for the multiple DERs case. It has been concluded that the selection of the HC calculation method should be done carefully and in accordance with the application because each method has its strengths and weaknesses. Software programs that only provide the iterative method cannot be used to calculate the maximum HC of the distribution network for multiple DERs integration. Similarly, programs that only employ stochastic methods are inefficient in finding the optimal size and location for a single large-scale DER. The best performance is achieved when multiple HC methods are used in tandem and the weaknesses of one method are rectified by the strengths of the other.