Plant-level electricity demand response for combined manufacturing system and heating, venting, and air-conditioning (HVAC) system

Sun, Zeyi; Li, Lin; Dababneh, Fadwa

doi:10.1016/j.jclepro.2015.12.098

Cited by 37 publications

(13 citation statements)

References 13 publications

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“…Building thermodynamic is a sub-system that measures the variations between indoor and outdoor temperature. It takes care of the heat losses to the environment and heat flow from the heater [39]. In this context, various optimization methods have been used to manage the indoor temperature prediction without knowledge of solar radiation.…”

Section: • Building Thermodynamic Modelmentioning

confidence: 99%

Fuzzy Based Particle Swarm Optimization for Modeling Home Appliances Towards Energy Saving and Cost Reduction Under Demand Response Consideration

et al. 2020

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Recently, homes consume around 40% of world power and produce 21% of the total greenhouse gas emissions. Thus, the proper management of energy in the domestic sector is a vital element for creating a sustainable environment and cost reduction. In this study, an intelligent home energy management system (HEMS) is developed to control domestic appliances load. The motivation of this work is reduced the electricity cost and power consumption from all the appliances by maintaining the customer's high comfort level using an efficient optimized controller. The domestic household appliances such as heating ventilation and air conditioning (HVAC), electric water heater (EWH) and lighting were modelled and analysed using Simulink/Matlab. The developed models analysed the appliances' energy consumption and cost sceneries during peak, off-peak and both peak and off-peak hours. Fuzzy logic controller (FLC) was developed for the HEMS to perform energy utilization estimation and cost analysis during these periods taking the Malaysian tariff for domestic use into consideration. To improve the FLC outcomes and the membership function constraint, particle swarm optimization (PSO) is developed to ensure an optimal cost and power consumption. The results showed that the developed FLC controller minimized the cost and energy consumption for peak period by 19.72% and 20.34%, 26.71% and 26.67%, 37.5% and 33.33% for HVAC, EWH, and dimmable lamps, respectively. To validate the optimal performance, the obtained results shows that the FLC-PSO can control the home appliances more significantly compared to FLC only. In this regard, the FLC-PSO based optimum scheduled controller for the HEMS minimized power and cost by 36.17%-36.54%, 54.54%-55.76%, and 62.5%-58% per day for HVAC, EWH, and light, respectively. In sum, the PSO shows good performance to reduce the cost and power consumption toward efficient HEMS. Thus, the developed fuzzy-based heuristic optimized controller of HEMS is beneficial towards sustainable energy utilization. INDEX TERMS Home energy management, cost of energy, fuzzy logic controller, particle swarm optimization, home appliances, building energy, energy saving.

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Section: • Building Thermodynamic Modelmentioning

confidence: 99%

Fuzzy Based Particle Swarm Optimization for Modeling Home Appliances Towards Energy Saving and Cost Reduction Under Demand Response Consideration

et al. 2020

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“…They found 21 green practices from the literature that were primarily concerned with environmental impacts. Sun et al [21] proposed an electricity demand response technique for integrated manufacturing and heating, venting and air-conditioning (HVAC) systems taking into account electricity pricing, reducing power demand, production capability and ambient temperature to investigate the optimal electricity demand response strategy considering both production schedule and HVAC control using a numerical case study. Similarly, Wang and Li [22] attempted to increase the energy efficiency and cost-effectiveness of manufacturing systems by proposing a framework for time-of-use based electricity demand while considering the production target constraints.…”

Section: Literature Surveymentioning

confidence: 99%

An Integrated Decision-Making Approach for Cause-And-Effect Analysis of Sustainable Manufacturing Indicators

et al. 2020

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Sustainability is a growing concern for manufacturing companies, as they are major contributors to pollution and consume a substantial portion of the world´s natural resources. Sustainable manufacturing can reduce waste, conserve energy and increase resource efficiency. However, one of the main challenges facing manufacturing organisations to put sustainability into practice is the lack of understanding of the cause-and-effect relationships between critical indicators of sustainable manufacturing. To overcome this challenge, a novel, rigorous and integrated framework, composed of four quantitative methods, is proposed to analyse critical indicators of sustainable manufacturing. The analysis is based on responses from both academic and industry experts. These four methods including DEMATEL (decision-making trial and evaluation laboratory), the MMDE (maximum mean de-entropy) algorithm, ISM (interpretive structural modelling) and SEM (structural equation modelling) are uniquely integrated to present statistically validated relationships between critical indicators using information on varying degrees of relationship between them. The final cause-and-effect models for the respondent groups (i.e., researchers and industry experts) are further validated through gathering the viewpoints of a researcher and an industry practitioner for its robustness. The novelty of our research lies in: (1) proposing a novel and integrated rigorous quantitative framework combined with qualitative research method; (2) applying the proposed framework to analyse contextual relationships between critical indicators of implementing sustainability, in the manufacturing sector as a whole, which to the best of authors' knowledge is the first of its kind; and (3) comparing and contrasting results of researchers and industry practitioners' groups along with a check of their validation and robustness.

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“…Brundage et al [35] stated that modern manufacturing facilities waste energy saving opportunities due to the lack of integration between the facility and production system. Efforts at combining manufacturing level analysis with that of the built environment to achieve a holistic understanding of energy flows has been seen [28], [29], [36]- [39].…”

Section: Previous Related Workmentioning

confidence: 99%

Thermal modelling of manufacturing processes and HVAC systems

Mawson

Hughes

2020

Energy

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The two main energy consumers within a manufacturing plant are the HVAC systems and manufacturing processes. Studies have predominately looked at energy demand associated with manufacturing a single product or a production line, as well as analysis of energy use within a building, but little work has investigated the interaction between manufacturing processes and the surrounding building. Dynamic time based building energy simulation was used to determine the thermal behaviour of the manufacturing facility. The study establishes the importance of analysing manufacturing energy flows alongside that of the building in order to capture all thermal and energy flows. The relationship between the energy demand of HVAC systems with manufacturing productivity is determined. The use of the current degreeday method of building analysis was proven inappropriate for manufacturing facilities, due to such significant heat gains from manufacturing equipment, and impact of equipment on indoor conditions. The need for a proactive HVAC system based on manufacturing demand is introduced, allowing for control of the environment prior to significant temperature or humidity changes.

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Plant-level electricity demand response for combined manufacturing system and heating, venting, and air-conditioning (HVAC) system

Cited by 37 publications

References 13 publications

Fuzzy Based Particle Swarm Optimization for Modeling Home Appliances Towards Energy Saving and Cost Reduction Under Demand Response Consideration

Fuzzy Based Particle Swarm Optimization for Modeling Home Appliances Towards Energy Saving and Cost Reduction Under Demand Response Consideration

An Integrated Decision-Making Approach for Cause-And-Effect Analysis of Sustainable Manufacturing Indicators

Thermal modelling of manufacturing processes and HVAC systems

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