Cong Zhang

Reactive Power Optimization Under Interval Uncertainty by the Linear Approximation Method and Its Modified Method

Reactive power optimization is a special kind of optimal power flow for optimizing voltage profile and reactive power flow in the steady state based on deterministic sets of the demand load and generation values, thus minimizing the real power losses or improving the voltage quality of the power grid. However, the input data in power systems have a certain degree of uncertainty that requires the reactive power optimization be solved by means of uncertain nonlinear programming, as advocated in the literature. To address this problem, we represent the uncertain input data as intervals and establish a model of the reactive power optimization that incorporates the interval uncertainties to describe the problem. The linear approximation method is formulated using the interval Taylor extension to help solve this type of problem. To obtain more accurate intervals for the state variables, the affine arithmetic-based power flow calculation is used to solve the interval power flow equation instead of crude computation based on the interval arithmetic, and thus the modified linear approximation method is developed. The proposed methods are presented in detail and the numerical results are analyzed to demonstrate their effectiveness and applicability, especially in comparison to the previously proposed chance constrained programming method.

An Interval Power Flow Analysis Through Optimizing-Scenarios Method

Interval power flow (IPF) is a special kind of uncertain power flow problem whose demand load and active power generation are regarded as interval uncertainties. A novel optimizing-scenarios method (OSM) is envisaged in this paper to solve this problem to obtain more accurate results. The OSM includes two kinds of approaches, namely the minimum and maximum programming models, in which the interval uncertainties are regarded as variables with varying bounds, and the objective function under study is set to determine these unknown variables. By solving these nonlinear programming models through the interior point method, the changing variables of the IPF problems are determined. Performance of the proposed approach is compared with that of previously established methods, including the affine arithmetic-based method as well as Monte Carlo simulation method, and the overall simulation results demonstrate the effectiveness and robustness of the proposed OSM.

Pareto front of multi-objective optimal reactive power dispatch

In this paper, we are aimed to search the Pareto front of multi-objective optimal reactive power dispatch by the primal dual interior point method. In the front part are the introductions of optimal reactive power dispatch model, the concepts of Pareto optimum solution and Pareto front, and the primal dual interior point method. In the rear part, the process of searching Pareto front will be presented, followed by the case study which consists of three cases. By conducting case study, we concludes that the primal dual interior point method performs effectively as well as efficiently in searching the Pareto front of multi-objective optimal reactive power dispatch.

Aging state assessment of 110kV XLPE cable based on IRC and AE

To evaluate the aging condition of 110kV XLPE cables accurately, this paper employs the isothermal relaxation current (IRC) method and the activation energy (AE) method, discussing the relationship among the aging factor, the activation energy and the aging condition of cable insulation. The results show that compared with unaged cables, the cables under accelerated thermal aging have 0.348 more on the aging factor and their activation energy is generally lower. Besides, compared with the cables running for 14 years, the cables running for 25 years have 0.327 more on the aging factor, 15.05kJ/mol less on the activation energy and 30.6 years less on the remaining life. All these show that increasing of the internal traps number, deepening of the internal traps depth and the disintegration of chemical bonds are major microeconomic performances on cable aging. The differences in batching system and production technology system of cables can change the chemical structure in XLPE molecules. And assessment results are in line with expectations. Microscopically, evaluating the aging condition by IRC and AE has the accuracy and validity, which provides an effective method for the evaluation of XLPE cables aging condition from electrical and chemical aspects, and guides the maintenance and planning of cables.

Solution of interval reactive power optimization using genetic algorithm

Reactive power optimization is generally used to design an optimal profile of voltage and reactive power of power systems in steady state for deterministic sets of demand load and generation values, and it is a significant procedure in voltage control. However, the input data of power system is actually uncertain in practice, which makes reactive power optimization an uncertain nonlinear programming, and it is not solved properly at present. To address this problem, the input data is considered as interval and reactive power optimization incorporating interval uncertainties is proposed to model this problem. In order to solve this model, genetic algorithm is employed as the solution algorithm, where reliable power flow calculation is used to judge the constraints of the model. The IEEE14 system is tested and analyzed to demonstrate the effectiveness of the proposed method, especially in comparison to previously proposed chance constrained programming.

Coordinated optimization of district electricity and heating system based on genetic algorithm

Interconnection and coupling between electric power, heating and natural gas systems are becoming closer and closer. From the point of view of coordinated optimization, through the establishment of mathematical model of district electricity and heating system, a coordinated optimization model of district electricity and heating system based on genetic algorithm is constructed in this paper. A typical district electricity and heating system in engineering is modelled and analyzed using the above mentioned model, the average convergence characteristics and optimization effect are studied. Through the experimental results, the practicability and validity of the coordinated optimization model of district electricity and heating system based on genetic algorithm are verified. The research contents of this paper lays the foundation for the operation optimization of district electricity and heating system.

A multi-area coordinated voltage control method based on dynamic games

With the development of interconnected power grids, the reactive coupling among areas is growing stronger, and the regional voltage control coordination problem is getting more serious as well. To solve this problem, a multi-area coordinated voltage control method is proposed in this paper, by introducing dynamic games to voltage control. A multi-area coordinated voltage control model based on dynamic games (DGOCVC) is established, and the model is solved by a two-layered iterative numerical algorithm based on the primal-dual interior point method. The simulation results in the New England 10-generator 39-bus power system show the feasibility and advantages of the proposed voltage control method.