Formulating an optimization algorithm for optimal planning and assessment of rule-based hybrid load following micro-combined heat and power systems

K. P. Dinakaran, P. Bhanu, C. Sridhathan and L. Umashankar

Energy & Environment, 2025, vol. 36, issue 7, 3268-3293

Abstract: This manuscript presents a logical-based method with a constrained programming approach for making use of the principle. The proposed optimal approach is the improved chameleon swarm algorithm (ICSA). The navigating and hunting behavior of CSA is improved with the crossover and mutation processes, and it is defined as the ICSA approach. The proposed hybrid approach is the number one power consumption, greenhouse gas, and total annual cost (TAC), in addition to including conditions largely based entirely on the monitoring approach, which is a mixture of those standards. These three power-corresponding parameters have been exploited to examine the overall performance of every method corresponding to the absorbed power providers employing the construction call for requests. The calculation of the established effectiveness for four varieties of residents’ homes suggests the not-infrequent place hybrid method. This increases the exploitation of the cogeneration system as well as the proposed method because the most appropriate techniques include measures capable of obtaining excellent conciliation answers done with TAC at 55%, primary energy consumption (PEC) at 14%, and greenhouse generation (GHG) at 9% discounts correspondingly. However, the proposed method obtains optimum discounts in TAC and optimum overall performance for power matching by utilizing identical boundaries for GHG and PEC in assessment to the always infrequent place hybrid technique. The prey-in cost for energy era with nearly 60 in TAC is perceived as the maximum leading monetary constraint for sensibility evaluation when micro-cogeneration units use over 3% gain and are the most disrupted outcome for randomly evaluated.

Keywords: greenhouse fueloline era; power consumption; heat and power systems; greenhouse gas; improved chameleon swarm algorithm (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://journals.sagepub.com/doi/10.1177/0958305X231217635 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:sae:engenv:v:36:y:2025:i:7:p:3268-3293

DOI: 10.1177/0958305X231217635

Access Statistics for this article

More articles in Energy & Environment
Bibliographic data for series maintained by SAGE Publications ().