Software

DAP: Demand Analysis and Planning

DAP is a software tool developed for demand and load forecasting and for designing 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, it seems to have no equivalent on the market.

For maximum flexibility, DAP considers 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 for opening a user's guide: DAP is a time-saving tool.

Depending on the application used, forecasting windows will concern determining factors, number of customers, average customer consumption, ownership factors, etc. Linear and exponential forecasts are proposed, 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 for performing 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 click a button for getting the related peak load forecast.

A library of profiles

Profiles are values which evolve with time: days, weeks, years. They represent either load profiles or utilisation profiles of equipments. As they are expressed in percentages, they can be easily 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. Utilization profiles are associated with each equipment in a sector-region. 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 polynomes acting on the energy consumed (active, capacitive and inductive) and on the peak load. This allows for 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 up to the very 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 added value, the industrial production, the real estate m², etc. The determining factor should then represent the trend of the sector.
3. Customer Trend Forecast
   In this approach, the demand is defined by a number of customers and the average customer consumption: each of these variables is to be forecasted, possibly by linking to a determining factor. These should represent customers trends.
4. DSM forecast The DSM forecast is a process in 4 steps:
   1. The forecast of the number of customers
   2. The definition of the equipments in each sector, with the utilisation curve 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 (just a click)

As a result, the user can view his DSM forecast where the share of each equipment is represented between two 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 regional level or at the national level. The latter allows for entering a loss factor (network, ...).

So far, DAP is the only tool available with such a flexibility 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