Branch Power Loss Research Articles

Superposition Principle-based Method for Power Loss Allocation in Power Systems

The paper presents a novel method for power loss allocation of power systems to demands. This loss allocation technique is based on the contribution of individual demands to the branch power loss of power grids. Results of power flow analysis, precise power system modelling and superposition theorem are deployed in this proposed method. The advantage of the method described in the paper is that it is accurate and ensures fairness among network users. In addition, this allocation method is simple and can be effectively exploited to both meshed and radial electrical networks. A six-node meshed transmission system and an IEEE 33-bus radial distribution grid are utilized to implement power loss allocation based on the proposed method. The influence of demands’ power factor on the power loss allocated is also taken into account using the six-node meshed transmission network.

Research on optimization algorithm of distribution network reconstruction based on cuckoo search-particle swarm optimization

As the distribution network environment becomes more complex, improving the optimization effect and running time is the key to distribution network reconfiguration. In this paper, firstly, the minimum branch power loss is used as the evaluation index of the result, and the hybrid algorithm of PSO algorithm and CS algorithm is selected as the optimization method of the reconstruction problem. Secondly, the mathematical model of the distribution network introduced by DG is simplified, and the static distribution network weight is used. It is a simplified way of power flow solving by introducing DG into the distribution network model. Based on the CS-PSO algorithm, the optimization calculation of the distribution network reconfiguration with DG is carried out. Finally, a calculation example proves the rationality and effectiveness of the method.

Fast distribution network reconfiguration algorithm based on minus feasibility analysis unit

Because of the defects of the nonlinear optimization algorithm and the complexity of the physical constraints of the distribution network reconfiguration, the speed and the convergence of the algorithms are usually poor. A fast algorithm for distribution network reconfiguration based on feasibility analysis unit is presented. Firstly, the network simplification method is presented based on the radial construction of the distribution network, and then the conception of basic loop is proved by using the impedance-branch dissipation power theory. By analyzing the quantitative relationship between load and branch power loss and the characteristics of the nodal impedance matrix, the basic loop that is just the minus feasibility analysis unit of the physical reconfiguration optimization is verified. Based on this theory, the path dissipation factor is presented which formed a novel heuristic rules and an improved branch exchange method in order to solve the distribution network reconfiguration problem. In this proposed method, the processing sequence of all the basic loops is firstly defined by the load dissipation component, and then optimal reconfiguration scheme is simply obtained by repeating the above operation until there is no branch need to exchange. Test results of IEEE-69 buses system verified the efficiency and reliably of the proposed method.

Cross-term Decomposition Method for Loss Allocation in Distribution Systems Considering Load Power Factor

The customers of distribution system are generally encouraged to maintain better power factor through suitable tariff structures. The feeder power loss allocation is a part of tariff. The feeder power losses also depend upon power factor of loads. Therefore, loss allocation method should incorporate suitable rewarding and penalizing strategy for better and poor factors loads. This paper proposes a new distribution loss allocation method that considers load power factor to allocate losses in a more practical way. The proposed method employs bifurcation of cross terms of branch power loss among contributing nodes. The method provides loss allocation to system nodes in such a way that it provides rebates/penalties against variation in load power factor only to the concerned nodes. The proposed method is applied to 30-bus and 33-bus test distribution system and compared with other established methods. The analysis of the application results highlights the importance of the proposed method.

A Loss Allocation Model Based on the Superposition Theorem

This paper presents a new procedure for allocating transmission losses to generators and loads. Based on the superposition theorem, the paper proposes that electrical power flow in transmission line can be separated into a series of power component induced by each individual power supplies, and transmission line power losses can be separated into a series of power loss component induced by each individual power supplies. Thus, each power supplys contribution to the branch power loss is resolved. Based on the theory founded above, corresponding loss allocation model is established. Results illustrate the validity and rationality of the new allocation process with expected results.

Determination of the branch power and loss caused by node injection power

Current methods to determine branch power and loss changes include the DC method, the boundary power flow method and the sensitivity method, however, none of these methods are theoretically correct. Within the framework of an AC power-flow solution the node generation power and node load power are modelled using either a constant impedance or a current source, respectively after being connected to the relevant node. By solving the network current equation, the node voltage can be expressed as a function of the node load power. Similarly, the node voltage can be expressed as a function of the node generation power. Also, the branch power flow and loss caused by the node generation power or the node load power can be obtained by using the proposed expression for the nonlinear function. The branch power loss is allocated to the node power. An example is presented to validate the proposed approach.