Research On Distribution Network Planning With Distributed Generation

Distribution network placed in the terminal of the electric power system is an important link that contacts the power and the customer. The power supply capability of power system must be carried out by distribution network. Distribution network is very important to the whole power system. As distributed generation (DG) applications has been more concern and attention at home and abroad, distribution network planning with DG is a hot research now.According to the different stages of the design, the distribution network planning with DG can be divided into two parts:the influence of the DG on distribution network planning and the extended planning of distribution network considered DG. The former takes the feasibility of DG as a starting point, the latter takes the network planning as the starting point. This paper studies the two different conditions.For the impact of DG on the distribution network planning, this paper establishes economic model of DG based distribution network planning. The model takes the minimization of the investment and operation cost as objective function and builds normalized objective function by adding the DG total number, voltage and current limits. Simulated annealing algorithm has done well in solving the issue such as the distribution network planning, hence, improved simulated annealing algorithm used here.Distribution network planning considering DG is a project that makes out the best expansion program of the system reached its capacity limit and take the minimization of the cost of re-expansion.This paper considers system load and market price in the different locations of the eiectricity market, according to the potential investment options, we use multi-objective optimization model to, get higher screening candidates. And then, this paper use Monte Carlo simulation to simulate N market scenes of each candidate, and the re-expansion costs of each scenario will be calculated which can help planner to determine the best flexibility optimal solution.Practical examples prove that the improved simulated annealing algorithm can solve large and complex distribution network planning problem effectively, and demonstrated that install DG in the appropriate location can greatly reduce costs. Numerical results show that the introduction of DG into distribution network can be used to increase flexibility, but also from other side, it's confirms the flexibility indicator can help network planers to optimize the program.