Random nature of system load

The system load varies continuously with time in a random fashion. Significant changes occur from hour to hour, day to day, month to month and year to year (Gross and Galiana, 1987). Figure 1.20 shows a typical load measured in a distribution substation for a period of four days.

The random nature of system load may be included in power flow studies and this finds useful applications in planning studies and in the growing 'energy stock market'. Some possible approaches for modelling random loads within a power flow study are:

1. modelling the load as a distribution function, e.g. normal distribution;
2. future load is forecast by means of time series analysis based on historic values, then normal power flow studies are performed for each forecast point;
3. the same procedure as in two but load forecasting is achieved using Neural Networks.

Non-linear loads

Many power plant components have the ability to draw non-sinusoidal currents and, under certain conditions, they distort the sinusoidal voltage waveform in the power network. In general, if a plant component is excited with sinusoidal input and produces non-sinusoidal output, then such a component is termed non-linear, otherwise, it is termed linear (Atha and Madrigal, 2001). Among the non-linear power plant components we have: 

Fig. 1.20 A typical load measured at a distribution substation.

• power electronics equipment
• electric arc furnaces
• large concentration of energy saving lamps
• saturated transformers
• rotating machinery.

Some of the more common adverse effects caused by non-linear equipment are:

• the breakdown of sensitive industrial processes
• permanent damage to utility and consumer equipment
• additional expenditure in compensating and filtering equipment
• loss of utility revenue
• additional losses in the network
• overheating of rotating machinery
• electromagnetic compatibility problems in consumer installations
• interference in neighboring communication circuits
• spurious tripping of protective devices.

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