Software

DAP: Demand Analysis and Planning

DAP is a software tool designed to forecast demand and load and to draw up Demand Side Management actions. DAP includes four applications:

1. Simple trend forecast
2. Sector trend forecast
3. Customer trend forecast
4. DSM forecast

A state-of-the-art software

DAP is based on more than 10 years of experience in demand forecasting and DSM project impact assessment. Up to now, there is apparently no equivalent on the market.

In order to have maximum flexibility, DAP uses a user-defined list of sectors and regions, and a library of determining factors that can be forecasted independently.

In addition, sectors can be identified by codes and be grouped in Types of sectors for clear classification in breakdowns.

Guidelines

All windows provide clear menus and buttons with guidelines to the user, so that there is no need to open a user's guide: DAP is an energy and time saving tool.

Depending on which application is used, forecasting windows will concern determining factors, number of customers, average customer consumption, ownership factors, etc. Linear and exponential forecasts are suggested, and the past increase rate is automatically computed.

For determined forecasts (i.e. linked to a determining factor forecast), the elasticity between the variable to be forecasted and the factor is automatically computed and proposed to make the forecast.

On the right of the screen, there is a screenshot of a typical forecast window.

After forecasting the demand and assigning load profiles, just press a button to get the related peak load forecast.

A library of profiles

Profiles are values that change with time: days, weeks, years. They represent either load profiles or usage profiles of the equipment. As they are expressed in percentages, they can easily be compared and applied to other regions or sectors. The time resolution is 15 minutes.

A library of equipments

For the DSM forecast, equipments are defined with their nominal power. Usage profiles can be associated with the equipment for each sector-region pair. Simultaneity factors are also associated in order to represent the natural (statistical) smoothening of the resulting load curve.

A library of tariffs

Tariffs are represented by polynomials acting on the energy consumed (active, capacitive and inductive) and on the peak load. This allows assessing the financial impact of DSM for a utility.

Forecast your load and simulate your DSM projects

Why 4 methods for demand forecasting?

Depending on the available data and on the time you have, various levels of details can be adopted. DAP allows to forecast from the simplest level to the most detailed level representing all equipments: DSM forecast.

For each sector of each region, one of the following methods, at least, has to be applied: a further aggregation into a national forecast will be proposed.

1. Simple Trend Forecast
   The simplest forecast of the demand or the peak load is the one based on its past values. In a few clicks it will give you a reasonable or an approximate estimate.
2. Sector Trend Forecast
   A first improvement consists in assigning the future evolution of the demand or the peak load to a "determining" factor: for example the population, the regional raw product (or the added value), the industrial production, the occupied surface area (m²), etc. The determining factor should then represent the trend of the sector, in terms of power consumption.
3. Customer Trend Forecast
   In this approach, the demand is on the one hand defined by a number of customers and on the other hand by the average customer consumption: each of these variables can be forecasted separatly, possibly by linking it to a determining factor which is selected to represent the customer's trends.
4. DSM forecast The DSM forecast is a process in 4 steps:
   1. The forecast of the number of customers
   2. 2) The definition of the equipment in each sector, with the selection of one's usage profile and simultaneity factors to be associated.
   3. The forecast of the ownership of equipments in each sector
   4. The computation of the DSM forecast itself (in just one click)

As a result, the user can view his DSM forecast where the share of each equipment is represented between two coloured lines.

For maximum flexibility, the order of the equipments in the graphic is user-defined.

By comparing two DSM forecasts, i.e. a "natural demand" forecast and a "Demand Side Managed forecast", the user can identify the impact of the DSM project on the peak load, on the consumption and on the utility revenues.

National forecasts

After working with the 4 methods, the forecaster will have various forecasts for a given sector in a given region.

He can then assign to each "sector-region" his best forecast (any type) so that a sum can be computed at the regional level or at the national level. The latter allows to take into account losses, due, for example, to the network. So far, DAP is the only tool available which is so full and so flexible for demand forecasting and DSM simulation!

Moreover, when it is Object-oriented programmed, any adaptation of the DAP software for specific needs can easily be made and at low cost.

So far, DAP is the only tool available which is so full and so flexible for demand forecasting and DSM simulation!

Other functions:

All windows presenting results provide the following functions:

• Print graphic
• Copy graphic to clipboard
• Save table to a spreadsheet file