Economic Load Dispatch with Emission Constraints

In power systems, economic load dispatch represents a critical optimization task aimed at allocating generator outputs to optimal setpoints. The primary objective is to minimize total generation costs while satisfying all load demands. Concurrently, environmental protection requirements necessitate the consideration of emission factors during power generation processes, particularly greenhouse gas emissions. Thus, economic load dispatch with emission constraints forms an essential component of power system optimization.

Practical implementations typically employ mathematical models and computational algorithms to address these challenges. Common approaches include linear programming techniques for convex optimization problems and metaheuristic methods like simulated annealing for non-convex scenarios. The implementation often involves objective functions that combine fuel costs with emission penalties through weighting factors. Key algorithmic components may include constraint handling mechanisms for generator limits, ramp rate constraints, and transmission line capacities.

Code implementations frequently utilize optimization libraries such as MATLAB's fmincon solver or Python's SciPy optimization modules. The solution workflow generally involves: 1) Problem formulation with multi-objective functions, 2) Constraint definition using inequality and equality expressions, 3) Algorithm selection based on problem characteristics, and 4) Convergence criteria setting for optimal solution identification.