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 electric utilities, demand-side management (DSM) can reduce electric load and shift load from peak to off-peak periods. In general, the investor in DSM collects the reward with lower electric bills, excepting a positive externality because of reduced tropospheric and stratospheric air pollution from fossil fuel power plants. In warm climates, DSM options include increasing albedo and vegeta...

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 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...