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Which of the following equations is used to estimate the trend term in the deterministic part of load?
N ∑ d d σ σ σ = 1 N + ∑ d d σ σ = 1 N ∑ σ σ = 1 N N ∑ σ 2 σ = 1 N + ∑ σ σ = 1 N 2
N ∑ d d σ σ σ = 1 N + ∑ d d σ σ = 1 N ∑ σ σ = 1 N N ∑ σ 2 σ = 1 N + ∑ σ σ = 1 N 2
N ∑ d d σ σ σ = 1 N - ∑ d d σ σ = 1 N ∑ σ σ = 1 N N ∑ σ 2 σ = 1 N - ∑ σ σ = 1 N 2
None of above
N∑ddσσσ=1N-∑ddσσ=1N∑σσ=1NN∑σ2σ=1N-∑σσ=1N2
Quick Summary: The deterministic part of electrical load is often modeled as a linear trend represented by the equation $d_d(\sigma) = a\sigma + b$. The coefficients $a$ and $b$ are determined using the method of least squares regression, where the slope $a$ is calculated to minimize the sum of squared residuals between the observed and predicted values.
The deterministic part of electrical load is often modeled as a linear trend represented by the equation dd(σ)=aσ+b. The coefficients a and b are determined using the method of least squares regression, where the slope a is calculated to minimize the sum of squared residuals between the observed and predicted values.
dd(σ)=aσ+b — Linear trend equation
a=N∑σ2−(∑σ)2N∑(dd(σ)σ)−∑dd(σ)∑σ — Slope of the deterministic trend
In linear regression, to minimize S=∑[dd(σ)−(aσ+b)]2, we take partial derivatives with respect to a and b and set them to zero. Solving the resulting normal equations yields the slope a=N∑σ2−(∑σ)2N∑(dd(σ)σ)−∑dd(σ)∑σ. This provides the best-fit line for the long-term trend in load data.
The deterministic load component represents the predictable long-term growth or seasonal trends.
The least squares method ensures the trend line has the minimum total error.
The denominator represents the variance of the independent variable (time/sigma).
Mathematically precise identification of long-term growth.
Reduces noise from random load fluctuations.
Sensitive to outliers in historical data.
Assumes linear growth which may not hold over very long horizons.
Long-term power system planning.
Peak demand estimation for infrastructure investment.
The variable N denotes the total number of data points.
The numerator represents the covariance between the load and time, scaled by N.
Option A and B are incorrect due to incorrect signs in the denominator leading to divergence.
C is correct — The provided equation represents the standard slope calculation for the least squares regression method used to estimate the deterministic trend of load data.
Remember that for any linear trend estimation y=mx+c via least squares, the denominator must involve the variance of x, which always involves a subtraction: N∑x2−(∑x)2.