Power Grid Up Grading Methods With Hybrid Quantum Evolutionary Algorithm Planning

Substation planning has been an important subject in operation of the power system in the power system, also is the key point in distribution network planning. The purpose of this paper is to study the regional power grid upgrade location problem in the transformation of new substation, especially for new material industrial S area location problem. Substation planning includes many contents, such as the location of the substation capacity planning, configuration selection, the area of load forecasting, as well as the transformer substation lines to connect many topics, it is an problem, the problem is a complex combination of belonging to contain various constraint conditions. At present, the substation planning, a lot of time through the engineering staff from several feasible schemes in the construction and operation and maintenance costs in comparison to determine the final scheme, but this lack of scientific computing optimization, is likely to result in the waste of resources or re work, more so, this paper focuses on an area the new location problem of substation as the object of study, many factors combined hybrid quantum evolutionary algorithm to research, finally it is significance to the site selection of the transformer substation optimal results.In this paper, according to the actual situation in the S area power grid and considering the new substation cost, maintenance cost, load balance, the reliability of power supply and other factors, the quantum evolutionary algorithm QIEA and greedy randomized adaptive search algorithm (GRASP)integration, is a combination of algorithm global optimization ability strong local search ability strong the algorithm, forming a hybrid quantum inspired evolutionary algorithm (GRQIEA), and the algorithm to solve the S problem in the new substation location planning. It has "exploration" and "Exploitation" ability, making the local and global searching ability of the algorithm to be balanced, to solve the location problem of new practical power system in the substation, as working area power grid planning accuracy, economy, plays a positive role in stability, has the great significance.The main work and research results are as follows:(1) the S regional power grid, the new material industrial park planning aspects of various factors are studied carefully and deeply and a lot of work. The S region’s economic development, the load forecasting research and in-depth analysis of the new materials industry function area layout, analysis of enterprise industry zone of electricity needs. In order to ensure that the results of scientific and practical, field investigation of S area, especially the geography, hydrology, traffic location, new materials industry zone of the meteorological conditions, technical conditions, geological structure, soil conditions, in ensuring the premise of electric reliability, minimize the light substation is completed, the electricity sector operation maintenance costs, as well as the impact on the local environment. (2) a strong local search ability of GRASP into QIEA, and well balanced algorithm of global and local search ability, and in the0/1knapsack problem as the test function, comparative analysis of the other5kinds of quantum evolutionary algorithm, the experimental results show that the hybrid quantum evolutionary algorithm has the global search ability comparison the ideal and local search ability, has a superior performance in solving combinatorial optimization problems.(3) according to the actual situation of the region of S, the application of GRQIEA algorithm to optimize the substation planning in the region, and compared with the methods in literatures. Results show that, this algorithm can solve the problem of substation planning, and can consider the investment most provinces, operation economical and reliable power supply planning optimization.