Abstract:
Modern living standards, industrial development and population escalation has altered
various aspects of traditional power industry. This changed situation has altered power
generation practice due to concerns like rapidly increasing fuel cost, ever growing electricity
demand, environmental pollution etc. Therefore, competition in electricity market has been
increased to ensure provision of electricity to the consumers with highest quality at minimum
cost.
In power generation, the operational planning is a major activity which includes the
superlative employment of the available energy resources subjected to various constraints.
Economic dispatch (ED) is the extremely challenging part of power system operational
planning and is defined as a complex constrained engineering optimization problem that aims
to calculate power generation of the generating units in a power system for minimum
generation cost, subject to constraints.
Traditionally, Economic Dispatch (ED) has been expressed as a convex optimization problem
solved with the help of conventional optimization techniques. The conventional techniques
Include Equal Incremental Cost Criterion, Newton’s Method, Lambda Iteration Method,
Linear Programming, Non-Linear Programming, Dynamic Programming etc. But economic
dispatch in modern power systems is highly complex due to non-smooth (or non-convex)
objective functions and various newly added constraints. The conventional optimization
techniques are not capable in effectively solving this complex problem. In literature, various
stochastic optimization techniques have been employed to solve non-convex economic
dispatch problem and the research is being continued to achieve the best possible solution.
This research presents implementation of Water Cycle Algorithm (WCA) on economic
dispatch problem. WCA is a novel metaheuristic population based algorithm, recently
introduced for solving constrained engineering optimization problems. In this research, WCA
has been tested on various standard test systems and its effectiveness has been verified by
comparing the simulation results with those of other algorithms in literature. Simulation
results have been calculated using Matlab.
