Two units, rated at 100 MW and 150 MW, are enabled for economic load dispatch. When the overall incremental cost is 10,000 Rs./MWh, the units are dispatched to 50 MW and 80 MW respectively. At an overall incremental cost of 10,600 Rs./MWh, the power output of the units are 80 MW and 92 MW, respectively. The total plant MW-output (without overloading any unit) at an overall incremental cost of 11,800 Rs./MWh is ___________ (round off to the nearest integer).
We are given dispatch data at two incremental cost points:
At \(\lambda_1 = 10,000\):
\(P_1 = 50\) MW, \(P_2 = 80\) MW
At \(\lambda_2 = 10,600\):
\(P_1 = 80\) MW, \(P_2 = 92\) MW
We can assume linear relationships for both units between \(P\) and \(\lambda\):
Let’s assume for Unit 1:
\[ P_1 = a_1 \lambda + b_1 \] Using the two points:
Subtracting (1) from (2):
\[ 30 = a_1 (600) \Rightarrow a_1 = \frac{30}{600} = 0.05 \] Substitute into (1):
\[ 50 = 0.05 \cdot 10,000 + b_1 \Rightarrow b_1 = 50 - 500 = -450 \] So,
\[ P_1 = 0.05 \lambda - 450 \] Similarly, for Unit 2:
\[ 12 = a_2 \cdot 600 \Rightarrow a_2 = \frac{12}{600} = 0.02 \] Substitute into (3):
\[ 80 = 0.02 \cdot 10,000 + b_2 \Rightarrow b_2 = 80 - 200 = -120 \] So,
\[ P_2 = 0.02 \lambda - 120 \] Now, at \(\lambda = 11,800\):
\[ P_1 = 0.05 \cdot 11,800 - 450 = 590 - 450 = 140~{MW} \] \[ P_2 = 0.02 \cdot 11,800 - 120 = 236 - 120 = 116~{MW} \] Total Plant Output:
\[ P_{{total}} = 140 + 76 = \boxed{216~{MW}} \] (Wait — typo! Earlier it says \(P_2 = 116\), not 76.)
Correct total:
\[ P_{{total}} = 140 + 116 = \boxed{256~{MW}} — exceeds ratings. \] But unit limits are:
\[ P_1^{\max} = 100~{MW}, \quad P_2^{\max} = 150~{MW} \Rightarrow {So we must cap } P_1 \leq 100 \] Hence:
\[ P_1 = 100~{MW (capped)}, \quad \lambda = \frac{P_1 + 450}{0.05} = \frac{550}{0.05} = 11,000 { (invalid)} \] Try finding \(\lambda\) where both stay within limits.
Try \(\lambda = 11,800\):
\[ P_1 = 0.05 \cdot 11,800 - 450 = 140~{MW}>100 \Rightarrow {Exceeds} \Rightarrow {Limit } P_1 = 100~{MW} \] Then compute corresponding \(\lambda\) for \(P_1 = 100\):
\[ 100 = 0.05 \lambda - 450 \Rightarrow \lambda = \frac{550}{0.05} = 11,000 \Rightarrow {Not valid since desired } \lambda = 11,800 \] So now reverse — for \(\lambda = 11,800\), set:
\[ P_1 = \min(0.05 \cdot 11,800 - 450, 100) = \min(140, 100) = 100~{MW} \] \[ P_2 = \min(0.02 \cdot 11,800 - 120, 150) = \min(236 - 120, 150) = \min(116, 150) = 116~{MW} \] Final Total Output:
\[ P_{{total}} = 100 + 116 = \boxed{216~{MW}} \]
In the following circuit, the average voltage \[ V_o = 400 \left(1 + \frac{\cos \alpha}{3} \right) {V}, \] where \( \alpha \) is the firing angle. If the power dissipated in the resistor is 64 W, then the closest value of \( \alpha \) in degrees is:

In the circuit, \( I_{\text{DC}} \) is an ideal current source, the transistors \( M_1 \), \( M_2 \) are assumed to be biased in saturation wherein \( V_{\text{in}} \) is the input signal and \( V_{\text{DC}} \) is the fixed DC voltage. Both transistors have a small signal resistance of \( R_{ds} \) and transconductance of \( g_m \). The small signal output impedance of the circuit is:

Assuming ideal op-amps, the circuit represents:

Selected data points of the step response of a stable first-order linear time-invariant (LTI) system are given below. The closest value of the time constant (in seconds) of the system is:
\[ \begin{array}{|c|c|} \hline \textbf{Time (sec)} & \textbf{Output} \\ \hline 0.6 & 0.78 \\ 1.6 & 2.8 \\ 2.6 & 2.98 \\ 10 & 3 \\ \infty & 3 \\ \hline \end{array} \]