Welcome to Scholar Publishing Group

Academic Journal of Energy, 2022, 3(3); doi: 10.38007/RE.2022.030304.

Energy Conservation (EC) and Emission Reduction (ER) Technology Based on Genetic Algorithm (GA)


Rod Fensham

Corresponding Author:
Rod Fensham

Universidad Tecnológica del Perú, Lima 15487, Peru


The equipment manufacturing industry is the basic industry for the development of the national economy and an important strategic industry that promotes the transformation of the national energy structure to green and clean energy. As my country accelerates the adjustment of the energy structure, liberalizes and absorbs private capital into the market, the development of the equipment manufacturing industry will be further deepened, refined, and specialized, and the technology and methods of energy saving and ER in the equipment manufacturing process will be studied, so as to achieve "clean energy and clean manufacturing". ", will become an important part of the applied science of environmental engineering. The main purpose of this paper is to conduct research on energy saving and ER technology based on GA. This paper evaluates and analyzes the collected electricity consumption throughout the year. The experiment shows that the annual average electricity consumption of the main workshops is nearly 12000MkW. According to the 80/20 principle, it can be concluded that the total electricity consumption of the first five items accounts for 89.78% of the total electricity consumption. (Other items, hydraulic press, heating furnace, air compressor system, lighting system), which belong to the key energy-consuming equipment of this workshop.


Genetic Algorithms, Energy Consumption, Energy Conservation, Emission Control

Cite This Paper

Rod Fensham. Energy Conservation (EC) and Emission Reduction (ER) Technology Based on Genetic Algorithm (GA). Academic Journal of Energy (2022), Vol. 3, Issue 3: 28-39. https://doi.org/10.38007/RE.2022.030304.


[1] Nshama E W , Msukwa M R , Uchiyama N . A Trade-off Between Energy Saving and Cycle Time Reduction by Pareto Optimal Corner Smoothing in Industrial Feed Drive Systems. IEEE Access, 2021, PP(99):1-1. https://doi.org/10.1109/ACCESS.2021.3056755

[2] Song Y L , Darani K S , Khdair A I , et al. A review on conventional passive cooling methods applicable to arid and warm climates considering economic cost and efficiency analysis in resource-based cities. Energy Reports, 2021, 7(5):2784-2820. https://doi.org/10.1016/j.egyr.2021.04.056

[3] Rehman A U , Wadud Z , Elavarasan R M , et al. An Optimal Power Usage Scheduling in Smart Grid integrated with Renewable Energy Sources for Energy Management. IEEE Access, 2021, PP(99):1-1. https://doi.org/10.1109/ACCESS.2021.3087321

[4] Ammar N R , Seddiek I S . An environmental and economic analysis of emission reduction strategies for container ships with emphasis on the improved energy efficiency indexes. Environmental Science and Pollution Research, 2020, 27(18):23342-23355. https://doi.org/10.1007/s11356-020-08861-7

[5] Pashchenko D , Nikitin M . Forging furnace with thermochemical waste-heat recuperation by natural gas reforming: Fuel saving and heat balance. International Journal of Hydrogen Energy, 2021, 46( 1):100-109.

[6] Abdelaziz G B , Abdelbaky M A , Halim M A , et al. Energy saving via Heat Pipe Heat Exchanger in air conditioning applications "experimental study and economic analysis". Journal of Building Engineering, 2021, 35(102053):1-12. https://doi.org/10.1016/j.jobe.2020.102053

[7] Kim Y J , Guanetti J , Borrelli F . Compact Cooperative Adaptive Cruise Control for Energy Saving: Air Drag Modeling and Simulation. IEEE Transactions on Vehicular Technology, 2021, PP(99):1-1.

[8] Dinh H T , Kim D . An Optimal Energy-Saving Home Energy Management Supporting User Comfort and Electricity Selling With Different Prices. IEEE Access, 2021, PP(99):1-1.

[9] Lopez G , Aoki T , Nkurikiyeyezu K , et al. Model for Thermal Comfort and Energy Saving Based on Individual Sensation Estimation. Sensors and Materials, 2020, 32(2(2)):693-702. https://doi.org/10.18494/SAM.2020.2635

[10] Nguyen D T , Hung N H , Kim H , et al. An Approximate Memory Architecture for Energy Saving in Deep Learning Applications. IEEE Transactions on Circuits and Systems I: Regular Papers, 2020, 67(99):1588-1601.

[11] Hlophe M C , Maharaj B T . QoS provisioning and energy saving scheme for distributed cognitive radio networks using deep learning. Journal of Communications and Networks, 2020, 22(3):185-204. https://doi.org/10.1109/JCN.2020.000013

[12] BingZHANG, GuanhuaLAI, YuanyuanDU, et al. Multi-dimentional road lighting technology with fixed low-mounting height luminaires. Journal of Shenzhen University Science and Engineering, 2022, 38(06):658-663.

[13] Cheong M S , Wu M C , Huang S H . Interpretable Stock Anomaly Detection Based on Spatio-Temporal Relation Networks With Genetic Algorithm. IEEE Access, 2021, PP(99):1-1.

[14] Na A , Fa A , Dsc C , et al. Development and validation of a hybrid aerodynamic design method for curved diffusers using genetic algorithm and ball-spine inverse design method. Alexandria Engineering Journal, 2021, 60( 3):3021-3036. https://doi.org/10.1016/j.aej.2021.01.034

[15] Ansari G J , Shah J H , Farias M , et al. An Optimized Feature Selection Technique In Diversified Natural Scene Text For Classification Using Genetic Algorithm. IEEE Access, 2021, PP(99):1-1. https://doi.org/10.1109/ACCESS.2021.3071169

[16] Hraiech S E , Chebbi A H , Affi Z , et al. Genetic Algorithm Coupled with the Krawczyk Method for Multi-Objective Design Parameters Optimization of the 3-UPU Manipulator. Robotica, 2020, 38(6):1138-1154. https://doi.org/10.1017/S0263574719001292

[17] Baagyere E Y , Agbedemnab A N , Zhen Q , et al. A Multi-Layered Data Encryption and Decryption Scheme Based on Genetic Algorithm and Residual Numbers. IEEE Access, 2020, PP(99):1-1. https://doi.org/10.1109/ACCESS.2020.2997838

[18] Ahn S , Kim J , Park S Y , et al. Explaining Deep Learning-Based Traffic Classification Using a Genetic Algorithm. IEEE Access, 2020, PP(99):1-1.