In the optimization of generator scheduling for different power plants, the objective is to minimize the fuel cost while meeting the power demand. This is achieved by determining the optimal allocation of power generation among the available power plants.



Several factors influence the fuel cost associated with power generation. These factors include:

1. Heat Rate: The heat rate of a power plant represents the amount of fuel required to generate a unit of electrical energy. A lower heat rate indicates higher efficiency and lower fuel consumption, resulting in lower fuel costs.

2. Fuel Price: The cost of fuel, such as coal, natural gas, or oil, plays a significant role in the overall fuel cost. The price of fuel may vary due to market conditions, availability, and transportation costs.

3. Power Plant Characteristics: Each power plant has its own unique characteristics, such as startup time, ramp rate, and minimum stable generation level. These characteristics affect the scheduling and operation of the power plants, ultimately impacting the fuel cost.



To determine the optimal generator scheduling and minimize fuel cost, various optimization techniques can be applied. These techniques include:

1. Linear Programming: Linear programming models can be used to optimize generator scheduling by formulating the problem as a linear objective function subject to linear constraints. The objective function represents the total fuel cost, while the constraints ensure that the power demand is met and the power plant operational limits are respected.

2. Dynamic Programming: Dynamic programming techniques can be employed to solve generator scheduling problems by considering the optimal decisions at each time step. This approach takes into account the current state of the system, such as power demand and available power generation, to make the best scheduling decisions and minimize fuel cost.



The minimum fuel cost in generator scheduling is obtained when the optimization algorithm determines the optimal allocation of power generation among the available power plants. The algorithm considers factors such as heat rate, fuel price, and power plant characteristics to minimize the total fuel cost while meeting the power demand.

By iteratively adjusting the power generation levels of each power plant, the optimization algorithm finds the optimal solution that minimizes fuel cost. This solution ensures that the power demand is met while taking advantage of the most efficient and cost-effective power plants.



In conclusion, the minimum fuel cost is obtained in the optimum generator scheduling when the optimization algorithm successfully determines the optimal allocation of power generation among the available power plants. By considering factors such as heat rate, fuel price, and power plant characteristics, the algorithm minimizes the fuel cost while meeting the power demand. The use of linear programming or dynamic programming techniques can aid in solving the generator scheduling problem and achieving the minimum fuel cost.