--- title: "Justify: trending method for large area forecast" subject: "Transmission and Distribution System Design" chapter: 6 key: "semester_8/transmission_and_distribution_system_design:justify-trending-large-area-forecast" source: https://www.bctengineer.com/q/semester_8/transmission_and_distribution_system_design/justify-trending-large-area-forecast site: BCT Engineering --- # Justify: trending method for large area forecast Transmission and Distribution System Design · Chapter 6: Electrical Load Characteristics and Load Forecast - Asked in: 2072 Magh, 2 marks - Answer checked by Claude Opus 5.5 (high effort) on 2026-10-14 - Page: https://www.bctengineer.com/q/semester_8/transmission_and_distribution_system_design/justify-trending-large-area-forecast - Whole chapter: https://www.bctengineer.com/md/semester_8/transmission_and_distribution_system_design/chapter-6 ## Question Justify the following statement in brief: The trending method of the load forecast is more suitable for large area load forecast. ## Short answer Large area loads grow smoothly as random small-area variations average out, allowing curve fitting on long historical records. Only total magnitude is needed for generation/transmission planning, so the trending method is quick, cheap and sufficient. ## Answer **The statement is correct.** The trending method fits a curve (linear, exponential or polynomial) to past load data and extends it into the future. It suits large areas (a whole utility, region or country) because: - The load of a large area is the sum of many small areas at different stages of growth. Their random, step-like changes average out, so the total grows **smoothly and steadily**, which a simple curve can follow. - Large areas have **long, reliable load records** (years of peak demand and energy sales) to fit the curve. - Only the **total amount** of load is needed for generation and transmission planning, not its exact location. - It is quick, cheap and needs no detailed land-use or end-use data. For small areas, load stays near zero and then jumps (S-curve), and history is short, so trending gives poor results there; simulation (land-use) methods are used instead. ## Check yourself The answer's key points as multiple-choice questions, with the correct option and why. 1. Why does trending suit large areas? A. Because large areas have no growth B. Because step-like changes of many small areas average out to smooth growth C. Because land use is known exactly D. Because it uses end-use data Answer: B. A large area is the sum of many small areas at different growth stages, so the total grows smoothly. (Key point: Why large areas trend smoothly) 2. Which is another reason trending works for large areas? A. Long reliable load records exist to fit the curve B. No load history is needed C. It gives exact location of load D. It needs detailed land-use maps Answer: A. Large areas have years of peak demand and energy records, and only total load is needed for planning. (Key point: Data availability) 3. Why does trending give poor results for small areas? A. Their load is perfectly smooth B. Their load stays near zero then jumps (S-curve) and history is short C. They have too much data D. They have no zoning Answer: B. Small area load grows in S-curve jumps with short history; simulation methods are used instead. 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