Optimal Distributed Generation Placement In Distribution Networks Considering Voltage And Loss

With the rapid increase in electrical energy demand, distributed generation(DG) units have so far found their pivotal roles in the restructured environment of power distribution systems. As an indispensable step toward a more reliable power system, the optimal placement of DG units, deemed to be the most techno-economically efficient and environment-friendly scheme, comes to the play vital roles in distribution networks and is profoundly taken under concentration. In this paper, a hierarchical evaluation system for power quality is also established, and we presentsmethods to rank the DG placement schems from the perspective of the DG’s influence on power quality and loss. The main research contents are summarized as follows:1. With the development of the distributed generation systems and more and more power customers are strict with power quality, both comprehensive evaluation of power quality and governance of power quality have become more important. However, the existing power quality comprehensive evaluation methods are not applicable to distributed generation. In order to study the feasibility of the distributed generation integration, and strengthen the positive guidance for improving the power quality, a new power quality comprehensive evaluation method is needed for distributed generation. The power quality comprehensive evaluation method for distributed generation system using data envelopment analysis(DEA) was proposed and the comprehensive evaluation index system was built. Finally, a case study showed that the proposed method can compare each appraisal object’s efficiency values and then get the ideal solution. The DEA method is suitable for the evaluation of power quality indices in distribution systems with distribution generation, and has practical significance for engineering.2. Power distribution network loss rate is a very important economic indicator(or technical indicator) in power companies. We proposed an improved LSF mehtod approach to evaluate energy losses estimation in power distribution systems, relying on the average current instead of the maximum demand. The physical conceptual analysis on the mathematical derivation of the equivalent hours of maximum loss, loss factor, rms current, average-current and equivalent time of average current loss methods was introduced. The improved loss factor(LSF) mehtod can be regarded as an effective method to enhance the quality of information in loss estimation. It eliminates and weakens the assumed conditions. Furthermore, it is helpful to improve calculation precision. In order to conduct a complete feasibility study for project practices, a large amount of measurement data is used to calculate energy losses in Guangdong power grid using the classical LSF method and the improved loss factor(ILSF) method, respectively. Results of statistical analyses indicate that the real data fall in the proposed three-dimensional region and the use of minimum load factor(MLF) can help improve computational accuracy of energy losses. The classical and improved LSF methods are used to estimate the effect in loss reduction by inserting a distributed generation(DG) in a 43-bus distribution network, and the candidate bus can be identified effectively.3. We devise models for the comprehensive evaluation of the placement of DG units in distribution networks. Power quality and power loss context are those considered objectives in the proposed scheme. To evaluate the impact of DG placement, the methodology of the entropy weighting which can avoid the subjective factors is proposed. The weighted Rank Sum Ration, TOPSIS and catastrophe theory methods are used to obtain final ranking, respectively. The standard IEEE 24-bus reliability test system consists of 10 generators, 24 buses, and 38 lines, is used for the analysis, and the anticipated efficiency of the proposed methods are well verified.4. Considering of photovoltaic-distributed generation(PV-DG) in distribution networks, an adaptive reactive power control model is introduced as to balance the trade-off between the improvement of voltage quality and the minimization of power loss. The optimal allocation problem is formulated as a chance-constrained stochastic programming(CCSP) model for dealing with the randomness of solar power energy. A novel algorithm combining the multi-objective particle swarm optimization(MOPSO) with support vector machines(SVM) is proposed to find the Pareto front consisting of a set of possible solutions. The Pareto solutions are further evaluated using the weighted rank sum ratio(WRSR) method to help the decision-maker obtain the desired solution. Simulation results on a 33-bus radial distribution system show that the optimal allocation method can fully take into account the time-variant characteristics and probability distribution of PV-DG, and obtain the best allocation scheme.