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Examoogle • User • info@examoogle.com • EE-2024-8821
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The extrapolation method is based on the
Curve fitting to present data
Extrapolation of past data
Extrapolation of present data
Curve fitting to previous data available
Curve fitting to previous data available
Quick Summary: The extrapolation method in load forecasting is based on the principle of trend analysis where a mathematical curve is fitted to historical load data. By identifying the underlying pattern in previous data, this model projects future demand assuming historical trends continue.
The extrapolation method in load forecasting is based on the principle of trend analysis where a mathematical curve is fitted to historical load data. By identifying the underlying pattern in previous data, this model projects future demand assuming historical trends continue.
Lt=a0+a1t+a2t2+...+antn — Polynomial curve fitting equation for trend extrapolation
E=∑i=1N(Lactual,i−Lpredicted,i)2 — Least squares objective function
The method uses time-series analysis to model past consumption as a function of time, L=f(t). By calculating the regression parameters or polynomial coefficients that minimize the error between the model and historical data, the function is extended (extrapolated) into future time intervals to estimate prospective load requirements.
Relies on the assumption that past load patterns provide sufficient information to predict future behavior.
Commonly used for long-term load forecasting (years or decades).
Does not account for external variables like weather or economic changes, which are typically addressed in multi-factor models.
Requires high-quality, continuous historical data to ensure reliable curve fitting.
Simple to implement mathematically.
Requires only historical load data rather than complex exogenous variables.
Susceptible to errors if structural changes occur in the load profile.
Performance degrades as the forecasting horizon extends significantly.
Long-term master planning of power systems.
Initial estimation of future capacity requirements for generation plants.
The accuracy of the extrapolation method is heavily dependent on the degree of the polynomial or the type of trend (linear, exponential, etc.) chosen.
Option A is incorrect because curve fitting without the historical context is insufficient; the method specifically relies on previous data to project into the future.
D is correct — The extrapolation method utilizes mathematical curve fitting based on previously available historical data to forecast future load requirements.
Always distinguish between extrapolation (based on historical trends) and simulation models (based on causal/exogenous variables) when answering questions on power system planning.