Evolutionary algorithms for bid-based dynamic economic load dispatch: A large-scale test case

The bid-based dynamic economic load dispatch problem (BBDELD) is an optimization problem that arises in the modern context of a de-regulated national energy market, and involves matching bids from competing generating companies to the demands of consumers (regions) so as to maximize a measure of `social profit'. We present a novel approach to solving the BBDELD, and introduce a large-scale test-case designed to reflect the deregulated Nigerian electricity industry. We build on previous work on smart evolutionary algorithm approaches to the static economic load dispatch (SELD) and dynamic economic load dispatch (DELD) problems, and also the BBELD (the non-dynamic form). We evaluate the performance of two evolutionary algorithm, previously reported on small-scale test cases of the BBELD, on dynamic extensions of those test cases (with demand profiles varied over 24 periods), and we introduce a new large-scale test case based on Nigerian sector data, involving 40 generators, 11 customers in 24 dispatch periods. The results demonstrate that the two approaches reported seem more effective than previous approaches on the previously reported cases (when tested on the non-dynamic versions for which prior results are available), and are capable of dealing successfully with the country's large-scale test case.