Increasing power plant efficiency with clustering methods and Variable Importance Index assessment

Duarte, Jéssica; Vieira, Lara Werncke; Marques, Augusto Delavald; Schneider, Paulo Smith; Pumi, Guilherme; Prass, Taiane Schaedler

doi:10.1016/j.egyai.2021.100084

Cited by 7 publications

(2 citation statements)

References 13 publications

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“…The first focused on determining the region's characteristics based on its potential using the method of Principal Component Analysis (PCA) while the second involved grouping the typologies through the Spatial Clustering method based on the weighting results on each of the observation locations. This spatial clustering is a simple concept observed to have been implemented in different areas such as landscape management [31], irrigation management [32], national food policy [33], the efficiency of the infrastructure of the region [34], and to determine the geographical pattern and characterize individual and environmental sociology [35]. Principal Component Analysis (PCA) was used to determine the characteristics of the observations grouped based on the region's potential.…”

Section: Data Collection and Processingmentioning

confidence: 99%

Mapping the Diversity of Regional Characteristics Towards Sustainable Economic Strategic Area Development: A Case Study of West-East Corridor of West Sumatra Province

Amelia¹,

Rustiadi²,

Barus³

et al. 2022

IJSDP

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There are different characteristics distinguishing a region from the others, thereby, leading to the diversities in the regional potentials and problems as well as the strategic regional development policies to be implemented. The East-West Corridor is one of the eleven provincial strategic economic areas in West Sumatra. It covers nine regencies or cities and 65 sub-districts with different characteristics and typologies and this leads to diversity in the strategies to develop this area. This study aims to determine the diversity associated with the characteristics and typologies of the strategic area of the East-West Corridor. This involved using Principal Component Analysis (PCA) analysis technique, spatial clustering analysis, and overlay analysis. Moreover, the regional characteristics and typologies were grouped based on 17 observational variables used in producing four main components including trade and tourism services, agriculture, livestock/fishery, and tourism. The results of spatial clustering analysis produced 3 clusters which are the urban, desa-kota, and rural areas while the overlay analysis produced ten regional characteristics and typologies used as the basis to make strategies and policies for each region’s development and to increase investment opportunities in the strategic area of West-East Corridor and the Province of West Sumatra in general.

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Section: Data Collection and Processingmentioning

confidence: 99%

Mapping the Diversity of Regional Characteristics Towards Sustainable Economic Strategic Area Development: A Case Study of West-East Corridor of West Sumatra Province

Amelia¹,

Rustiadi²,

Barus³

et al. 2022

IJSDP

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“…Firstly, it can help companies and organizations to save money on energy bills by reducing energy waste. Secondly, it can help to reduce the carbon footprint of buildings, which is an important step towards sustainability and environmental protection [7] [12]. Finally, it can help to improve the overall efficiency and productivity of buildings, which can have a positive impact on the bottom line of companies and organization.…”

Section: Introductionmentioning

confidence: 99%

Smart Energy Consumption Control in Commercial Buildings Using Machine Learning and IOT

R.,

et al. 2023

E3S Web Conf.

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In recent years, the use of artificial intelligence (AI) techniques such as Artificial Neural Networks (ANNs) and Support Vector Machines (SVMs), in combination with the Internet of Things (IoT), has gained significant attention for optimizing energy consumption in commercial buildings. With the increasing demand for energy and the rising costs of energy, there is a pressing need for efficient methods for energy management in commercial buildings. Smart energy consumption control systems that utilize machine learning algorithms and IoT devices can provide real-time data on energy usage and automate energy usage decisions in commercial buildings. In this paper, we investigate the potential of ANN and SVM-based smart energy consumption control systems in commercial buildings. We aim to analyze the impact of using these algorithms on energy consumption patterns in commercial buildings and evaluate the efficiency and effectiveness of these systems in reducing energy consumption and costs while maintaining the desired level of comfort for the occupants. Our study will focus on comparing the performance of ANN and SVM-based algorithms in terms of energy consumption reduction and cost savings. The results of this study can provide valuable insights into the application of ANN and SVM-based smart energy consumption control systems in commercial buildings and contribute to the development of more sustainable and energy-efficient buildings.

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Strategic-level performance enhancement of a 660 MWe supercritical power plant and emissions reduction by AI approach

Ashraf

Uddin

Arafat

et al. 2021

Energy Conversion and Management

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Increasing power plant efficiency with clustering methods and Variable Importance Index assessment

Cited by 7 publications

References 13 publications

Mapping the Diversity of Regional Characteristics Towards Sustainable Economic Strategic Area Development: A Case Study of West-East Corridor of West Sumatra Province

Mapping the Diversity of Regional Characteristics Towards Sustainable Economic Strategic Area Development: A Case Study of West-East Corridor of West Sumatra Province

Smart Energy Consumption Control in Commercial Buildings Using Machine Learning and IOT

Strategic-level performance enhancement of a 660 MWe supercritical power plant and emissions reduction by AI approach

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