Small area load forecasting method

Small area forecasting predicts the amount, location and timing of load growth in small zones. The two main methods are trending and simulation (land-use). The simulation method is explained below.

Simulation (land-use) method

The service area is divided into small cells (e.g. a grid of 1–10 hectare squares). Instead of extrapolating past load, the method simulates how land use will change and then converts land use into load.

 Base land-use map + zoning plan
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 Global (system) forecast of growth
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 Allocate growth to cells
 (preference / suitability scores)
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 Future land use in each cell
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 x load density (kW/ha) per class
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 Cell load map --> substations, feeders

Steps:

1. Data collection: present land use of each cell (residential, commercial, industrial, agricultural, vacant, restricted), roads, railways, rivers, zoning by-laws, population and planned projects.
2. Global forecast: total growth of the whole region (customers or kW) is found from econometric/trending studies.
3. Suitability (preference) scoring: each vacant cell is scored for each land-use class from factors such as distance to roads and town centre, nearby land use, slope, and planned infrastructure.
4. Allocation: the global growth is allocated to the highest-scoring cells year by year, so that land use changes in a realistic spatial pattern.
5. Load conversion: future load of each cell = Σ (area of each land use × load density of that class), with end-use load curves giving the coincident peak.
6. Calibration: results are checked against present loads and the global forecast.

Merits: forecasts load in undeveloped areas, gives a load map useful for siting substations and routing feeders, and allows "what-if" scenarios.

Demerits: needs large data and computing effort.

(The trending method, by contrast, fits an S-curve (Gompertz) to each area's past load; it is simpler but fails for areas without load history.)