Impact Analysis And Expansion Planning Of Distributed Generation Access To The Distribution Network

With the continuous development of economic construction,the energy consumption of power grids has become more and more serious.Distributed power generation has received more and more attention due to its advantages of environmental friendliness,resource conservation,and participation in grid control.The large-scale distribution of distributed power into the grid can easily affect the stability of the power system.By studying the effects of distributed power on distribution network power quality and network loss,we will figure out how to make full use of the advantages of distributed power.Mid-and long-term load forecasting is the basis of power grid planning and dispatching.Accurate and reasonable forecasting of load is a subject that is unremittingly pursued in the power sector.The traditional expansion method is mainly to expand the capacity of transformers and lines.With the continuous introduction of distributed power to distribution networks,there are more feasible plans for expansion planning.Firstly,the working principle of distributed photovoltaics and establishes related mathematical models is analyzed.An IEEE-33 node distribution network standard system was built,and the original wiring method was improved.The distribution lines were divided into radial and ring networks,and each connection mode was distributed accordingly.The different access modes of the power supply simulate various access modes.Through simulation analysis of various situations,it is verified that the access capacity of the distributed power supply is closely related to its access location and wiring mode.Secondly,the nonlinear constrained support vector machine algorithm based on probabilistic decision-making theory is studied.The algorithm is applied to the medium and long-term load forecasting of a 10 kv distribution network in a certain area.The improved nonlinear constrained support vector machine transforms the quadratic optimization problem into a problem solving linear equations.Combined with the idea of probabilistic decision theory,it overcomes the disadvantages of different models and combines their advantages,thereby improving the speed of problem solving.And the convergence accuracy makes the prediction more accurate.The proposed algorithm was compared with the curve fitted with the trend method.The results show that the proposed algorithm has a smaller error,and the result is closer to the actual load value.Finally,the bi-level expansion planning of distributed power supply and distribution network is studied.Taking the annual comprehensive cost,network loss,and total distributed power capacity as objective functions,the binary particle swarm optimization algorithm is improved.A bi-level planning scheme is adopted to optimize the location and capacity of the selected line and distributed power supply.The improved algorithm not only improves the accuracy of the algorithm,but also reduces the possibility of falling into a local optimum.It also improves the convergence rate of the algorithm to some extent.Through the analysis of the IEEE 33 node and the 10 kv distribution grid predicted by the load in an area,it shows that the access of the distributed power source can effectively reduce the overall investment cost,reduce the line loss,and at the same time improve the voltage quality to some extent.The feasibility of the proposed algorithm and planning scheme is verified.