LOSS ALLOCATION IN DISTRIBUTION NETWORK WITH DISTRIBUTED GENERATION

Abstract

The losses occurring in the transmission and distribution networks have significant economic implications on their performance as a significant portion of total operating cost of the network is due to energy losses. In transmission networks, about 2-4% of total energy transmitted is lost in lines, whereas in Distribution Networks (DNs), this figure is around 4-6%. The costs of network losses are recovered from the users according to their share in total network losses. To determine the contribution of individual users in total losses of the network, a well-justified computational procedure is used, which is referred to as loss allocation. In the past, the problem of loss allocation was addressed only to transmission networks, but due to reforms in electric power industry, integration of Distributed Generation (DG) into existing DNs and the introduction of competition among suppliers and service providers, the problem of loss allocation in DNs has also started seeking the attention of the utilities engaged in distribution of electricity. The integration of DG into existing DNs transforms them from traditional passive networks with unidirectional power flow to active networks with bidirectional power flow. Hence, the integration of DG has a significant technical and economic impact on the performance of DNs directly influencing their losses. Further, there is a non-linear relationship between losses occurring in a branch of DN and the net current flowing through it. Also, the DNs are operated in radial or weakly meshed configuration with a high degree of unbalanced. These facts make the problem of loss allocation a challenging task. For a given DN, its efficient operation, placement of DGs and loads in it, and its reinforcement/expansion largely depend upon the results of loss allocation. Therefore, an appropriate and fair mechanism to allocate the losses of a DN among its users becomes an essential requirement under deregulated environment. Therefore, this thesis work aims to explore and investigate the mechanism of loss allocation in DNs in the presence of DG. It develops a few methodologies for allocation of power and energy losses occurring in radial and weakly meshed DNs with balanced and unbalanced operating conditions. The expression of power loss in a branch contains two types of terms, self-terms due to the square of individual currents and mutual or cross-terms due to two different individuals. The cross-terms reflect the inter-dependency among network users and their presence complicates the loss allocation as it is difficult to segregate them among the users. For effective allocation of network losses, the decomposition of the cross-terms should be equitable, fair, and capture the actual contribution of the contributing currents in the losses. However, in the case of significantly different current flows, the equitable decomposition of the cross-term is questionable. This thesis, therefore, investigates various existing techniques, such as incremental, proportional, quadratic, and geometric methods, for decomposition of the cross-terms. Based on the investigation, a generalized formulation for decomposition of the cross-terms is developed, and few more possible decomposition techniques such as square root, and cubic methods are anai lyzed. Further, since the cross-terms are decomposed in terms of downstream currents, various decomposition techniques are applicable to only radial DNs. Therefore, for decomposition of the cross-terms in weakly meshed DN, suitable modifications are also proposed in weakly meshed DN to convert it into an equivalent radial DN. Considering various decomposition techniques of the cross-terms, the loss allocation is performed on the 17-bus and 33-bus balanced DNs under radial and weakly meshed configurations with different operating conditions. On comparison of the obtained results of loss allocation, it is observed that the loss allocation based on quadratic, geometric, and cubic decomposition methods provide more meaningful results in terms of rewards and penalties to the users for their contributions to total network losses among other techniques. An ideal loss allocation technique should fairly allocate losses to network users; adhere to the fundamentals of electrical circuitry; reflect the impact of users on network losses; be easy to implement on real-time systems; apply to all distribution system scenarios; and be able to send out economic signals aimed at improving the network’s efficiency. However, not even a single method for loss allocation encompasses all of these attributes. The loss allocation is performed by the system operators using a suitable technique to determine the contribution of individual users to the total losses of their networks. The choice of a suitable loss allocation technique for implementation is based on its attributes and can vary depending on the preferences and requirements set by the system operator. However, there is no tool or framework available at present to assist the system operators in deciding a specific technique for allocating the losses as per their preferences and requirements. This thesis, therefore, proposes a framework for evaluating the performance of loss allocation methods based on multi-attributes utility theory. In the developed framework, a hierarchical structure is created to assess loss allocation methods, which includes the objective, sub-objectives and measurable attributes. The developed hierarchical structure is utilized to obtain the utility score of a loss allocation method by aggregating the weighted marginal utility of attributes. The utility score, thus obtained, indicates the suitability of loss allocation techniques. The proposed framework for evaluating the loss allocation methods is tested on 17-bus and 33-bus balanced DNs under various operating conditions. The results indicate that the performance of the cooperative game theory-based loss allocation methods would be better, if their computational complexity was reduced. Among various cooperative game theory-based loss allocation methods, τ -value based solution possesses most of the properties of a fair loss allocation. However, it can be used for loss allocation in a DN, only if the DN satisfies the necessary quasi-balanced condition. Further, like any other cooperative game theory-based solution, the computational complexity associated with τ -value based solution makes it impractical for loss allocation in large DNs with several participants.