The financial crisis has exerted influences of different degrees within a global scope, and, in the meanwhile, has brought about definite risks to the electric charge management in electric network enterprises. This paper makes a comprehensive analysis of prominent risks and characteristic changes in electric charge management in electric network enterprises under influences of the financial cr...

Estimation of the load, particularly of the peak load, is basis for the system state estimation, and for technical, and economic calculations. This makes possible improvement in economic operation, maintenance of electrical equipment, and optimal planning and operating of electrical distribution systems. In the paper, starting from a fuzzy correlation model of the loads, a power flow analysis f...

For fuel economy of power system, Plug-in Hybrid Electric Vehicle (PHEV) should be charged late at night to level a load curve. This paper proposes an electricity pricing algorithm for load leveling, using variation method. Variation method is a mathematical technique that can bring a value of integral functional to the extreme value. We formulate a cost minimization problem of PHEV owners, reg...

The charging of electric vehicles (EVs) places a strain on the transformers in the electric grid in order for it to be able to supply enough power to meet demand. This is set to become more and more of a burden on the grid as EVs become more popular among the general public. The use of demand-side management (DSM) and smart grids have been investigated as a solution to this problem, and the pro...

The problem of short-term electric load forecasting (STLF) is considered. A modified architecture of Elman-type recurrent neural network is proposed. It utilizes a special fuzzification layer to deal with quantitative as well as ordinal and nominal data. The second hidden layer of the network consists of standard Rosenblatt-type neurons with sigmoidal activation functions. The context layer is ...

In this paper, a new model, core vector regression (CVR) optimized by memetic algorithm (MA), is presented to predict electric daily load. Support vector regression (SVR) has obtained wide focus in recent years to solve nonlinear regression problems in many fields. However, it is limited on large scale dataset problem because of its high time and space complexity. Hence, CVR is proposed to impr...

A transformer less hybrid series active filter is proposed to enhance the power quality in singlephase systems with critical loads. This thesis assists the energy management and power quality issues related to electric transportation and focuses on improving electric vehicle load connection to the grid. The control strategy is designed to prevent current harmonic distortions of nonlinear loads ...