Optimal Location of Distributed Generation to Reduce Loss in Radial Distribution Networks

Abstract

Power losses are always a cause of worry for any power grid. In India, the situation is even worse. Though recent reports by Ministry of Power shows that Aggregate Technical and Commercial losses (AT &C losses) have come down from 36.64% in 2002-03 to 27% in 2011-12, yet they are much higher than the losses seen in many of the developed nations. The reduction shown in power loss is because of the Electricity Act, 2003 and the amendments made to it in 2007 which controlled the commercial losses rather than the technical losses. According to Ministry of Power, technical losses (Transmission & Distribution losses or T&D losses) in India are reported to be 23.65% in 2011-12. However, according to the study done by EPRI, for systems deployed in developed countries, these losses are estimated to be in the range of 7-15.5%. T & D losses occur in four system components namely step-up transformers and high voltage transmission (0.5-1%), step down to in intermediate voltage, transmission and step down to sub transmission voltage level (1.5-3%), sub-transmission system and step down to low voltage for distribution (2-4.5%), and distribution lines (3-7%). 1% of power loss is approximately equivalent to annual loss of Rs 600 million for a single state. Hence, in a year, loss in distribution line alone causes approximate loss of Rs 1.8-4.2 billion per state. Understanding and reducing power losses in distribution lines which contribute nearly 50% of the total T&D losses assume significance and has formed the motivation for the work reported in the thesis. In recent years, the trend has been to encourage users to generate solar power predominantly at residential complexes and captive power plants at industrial complexes. It has been suggested in the literature that Distributed Generation (DG) can not only reduce the load demanded from the power grid but also the power loss. In this thesis, it has been shown that by the choice of proper size and location of DG, the power loss can be reduced substantially as compared to unplanned deployment of DGs. The objective of the thesis is to design strategy for location of distributed user generated power to maximize the reduction in power loss. The thesis begins with a study of distributed generation in primary distribution networks and proceeds to problem formulation, with the aim being to develop an algorithm that can find out the optimal locations for DG allocation in a network. A greedy approximation algorithm, named OPLODER (i.e. Optimal Locations for Distributed Energy Resources), is proposed for the same and its performance on a benchmark data set is observed, which is found to be satisfactory. The thesis then moves on to describe the actual data of 101,881 commercial, residential and industrial consumers of Bangalore metropolitan area. A loss model is discussed and is used to calculate the line losses in LV part of the grid and loss is estimated for the said actual data. The detailed analysis of the losses in the distribution network shows that in most cases the losses are correlated with the sanctioned load. However there are also some outliers indicating otherwise. The analysis concludes that the distributed generated sources need to be optimally located in order to benefit fully. Also presented thereafter is a study about the impact of electrical properties and the structure of the network on power loss. In the second part of the thesis, OPLODER was again used to process the BESCOM data of 101,881 consumers by modeling them to be connected in three topologies namely Bus (i.e. linear structure), Star (i.e. directly connected) and Hybrid (i.e. tree structure). In case of Bus topology, when DG capacity available is 5% of the demand in substation, OPLODER reduced the loss from 14.65% to 10.75%, from 11.63% to 7.71% and from 13.33% to 9.24% for IISc, Brindavan, and Gokula substations respectively. Similarly, for the same amount of DG in case of star topology, OPLODER reduced loss from 1.75% to 1.26%, from 3.39% to 2.59% and from 2.96% to 1.99% for IISc, Brindavan, and Gokula substations respectively. Thereafter, the available real world data is re-modeled as a tree-type structure which is closer to the real world distribution network and OPLODER is run on it. The results obtained are similar to those presented above and are highly encouraging. When applied to the three substations viz. IISc, Brindavan and Gokula, the power loss dips from 9.95% to 7.42%, from 6.01% to 4.44% and from 8.07% to 5.95%, in case of DG used is 5% of the demand in substation. For the optimal strategies worked out in the thesis, additional overheads will be present. These overheads are studied and it has been found that the present infrastructure and technologies will be sufficient to handle the smart distribution network and the optimal strategy for distributed sources.