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USELOAD
– a Windows NT-program for calculation of electrical load divided into end-uses

This is a new model mainly for segmenting metered time series into end-use or different customers. It is based upon load curves from national load research projects. The model uses statistical methods and handles climatic dependencies and the diversification in the load from different customers. It can also estimate the coincident peak demand in a network with selected degrees of confidence. The employees for the development of the USELOAD model have been Electricité de France, Sydkraft, VTT Energy, Electricity Association and Energy Piano in Denmark.

USELOAD’s origin is from the international liaison body EDEVE where load-research, demand side management (DSM) and more specific consumption relations are being discussed and elucidated. A general need for more detailed description and modelling of end-uses resulted in a development-project with SINTEF Energy Research as the executive part.

The speciality of USELOAD is great flexibility, basic development of methods and great applicability for different kinds of purposes. Detailed input data is important before the model is operative for a specific region. Typical daily load curves for i.e. lighting, heating, ventilation, hot water and other electrical appliances should be established. Based on these data, the total load curve can be calculated divided into hours for a day or i.e. for a year. Table 1 shows a random example of such results from a specific supply region/transformer with a specific division in households and industry. All levels from one single house and up to e.g. total Norway can be modelled in a very user-friendly way – dependent of the number of single loads or buildings in different customer categories (houses, offices, schools, social etc.)

Table 1: A random example: Coincident peak demand is 11711,4 kW at 09:00 a.m. in week 7. The local peak for household customers is metered at 8,6 kW (95% confidence interval). The lowest temperature is –13 °C.

In figure 1 a calculation result is presented graphical for the day with coincident peak demand, e.g. a cold winter day for the same supply region. The figure shows that the coincident peak demand occurs at 9 a.m.

In figure 2 the load curve for the maximum day is presented segmented into different end-uses independent of the type of building. The calculation also includes network losses with hour interval. The figure clearly shows that space heating is the most important load at low temperature, and that lighting also is important.

The results of the calculation and the possibility for consequence analysis in USELOAD are a good basic for different kinds of analysis. Useload can be an interesting tool in a number of applications:

• The resulting demand of changing to new energy efficient technology i.e. high efficiency lighting
• Calculation of power segmented into different end-uses in different supply regions
• The effect of different kinds of energy control
• Detailed energy and power forecasts at all voltage levels
• The effect of changing to energy flexible solutions
• Detailed classification and mapping of load in different parts of the network where the maximum power or other customer relevant data are available
• Climate correction of energy and power with hour’s division
• Detailed calculation of network losses

Utility value for different needs
The model constitutes as an interesting tool for different parties in the power market. This can shortly be described as following:

• Network owner: Net planning, energy planning, design of tariffs and analysis of customers

• Power supplier: Market analysis, development of energy services and new products

• System operator: Power analysis and forecasts

• Authorities: DSM analyses and design of policy instruments towards customers

An interesting observation is that all the six involved countries focus on the challenges a deregulated power market will bring to better understand and model the energy market.

Figure 1. Segmentation of the load for the day with coincident peak demand for a specific climatic year	Figure 2. Segmentation of the load into different end-use for the day with peak coincident load

For more information about USELOAD, please contact Nicolai Feilberg or Klaus Livik.

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