article · International Transactions on Electrical Energy Systems
This study evaluates two modern optimisation algorithms, the hurricane optimisation algorithm and the sine-cosine algorithm, to solve non-smooth economic and ecological emission load dispatch problems. A multi-objective framework was established using Pareto principles to simultaneously balance conflicting goals: reducing generation fuel costs and minimising environmental emissions. The algorithms were evaluated across six benchmark test functions and two standard structural engineering problems, specifically tension or compression design and welded beam design. They were subsequently validated on an electrical power system operational model using the standard six-generator, IEEE 30-bus test system. Simulation outcomes show that both algorithms deliver viable performance relative to established optimisation methods. Between the two, the hurricane optimisation algorithm demonstrated superior competitiveness over the sine-cosine algorithm in terms of convergence rate and statistical consistency across both benchmark tasks and engineering applications.
Balancing generation fuel costs against harmful environmental emissions is a central challenge in power grid operation. Testing modern computational optimisation techniques on simulated power networks helps identify reliable algorithmic tools capable of lowering operating expenses while simultaneously curtailing ecological emissions, supporting more sustainable electrical energy management.
The method could enable electricity utilities and grid operators to improve generation scheduling to lower fuel expenses and pollutant outputs. The algorithms have been tested through simulations on benchmark engineering problems and a standard IEEE 30-bus test system. Because the findings are currently limited to model-based simulations, the technology remains at an early stage of research before potential integration into commercial energy management software.
AI-generated from the published abstract. Always read the original work before citing.
In the current research, a comparative study of two modern optimization algorithms is carried out for finding the solution of non-smooth economic/ecological emission load dispatch (EELD) problem. These optimization methods are hurricane optimization algorithm (HOA) and sine-cosine algorithm (SCA). A multi-objective optimization module is successively developed for the competitive algorithms. In the competitive algorithms, random initial populations of the search agents are created in the search space with optimizing the conflicted objectives, economic and emission, simultaneously of the EELD problem. The multi-objective optimal solutions are achieved based on Pareto concepts. The competitive algorithms are tested on six test function and two general standard engineering problems called tension/compression design and welded beam design problem. Then, the optimization algorithms are validated for an important operation issue of power systems by solving the non-smooth EELD on the standard six generators, IEEE 30-bus standard test system. Single and multiobjective frameworks are considered to reduce the generation fuel costs as well as minimizing the corresponding ecological emissions. Simulation results are assessed with previous famous optimizers. Also, these results prove the reasonable performances of the proposed two competitive algorithms compared with previous optimization techniques. In addition, HOA has more competitive performance compared with SCA according to convergence rate and statistical analysis of the studied real engineering problems as well as for benchmarking and design engineering problems. Therefore, these algorithms are considered as efficient and capable algorithms for other non-smooth large-scale complex problems in real power networks.
This page summarises published work. The authoritative version sits with the publisher.
DOI: 10.1002/etep.2716
Is something wrong with this record? Report it or request removal.
Discussion
Have you built on this work, tried to replicate it, or seen it applied in practice? Share what you know. Verified researchers and MARATTO™ domain experts can open a discussion, and any member can reply. Contributions are reviewed before they appear.
No discussion yet. Open the first thread.
New to MARATTO™? Create a free account.
