ECG reduction for wearable sensor
- Allami, Ragheed, Stranieri, Andrew, Balasubramanian, Venki, Jelinek, Herbert
- Authors: Allami, Ragheed , Stranieri, Andrew , Balasubramanian, Venki , Jelinek, Herbert
- Date: 2016
- Type: Text , Conference proceedings
- Relation: 2016 12th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS); Naples, Italy; 28th November-1st December 2016 p. 520-525
- Full Text:
- Reviewed:
- Description: The transmission, storage and analysis of electrocardiogram (ECG) data in real-time is essential for remote patient monitoring with wearable ECG devices and mobile ECG contexts. However, this remains a challenge to achieve within the processing power and the storage capacity of mobile devices. ECG reduction algorithms have an important role to play in reducing the processing requirements for mobile devices, however many existing ECG reduction and compression algorithms are computationally expensive to execute in mobile devices and have not been designed for real-time computation and incremental data arrival. In this paper, we describe a computationally naive, yet effective, algorithm that achieves high ECG reduction rates while maintaining key diagnostic features including PR, QRS, ST, QT and RR intervals. While reduction does not enable ECG waves to be reproduced, the ability to transmit key indicators (diagnostic features) using minimal computational resources, is particularly useful in mobile health contexts involving power constrained sensors and devices. Results of the proposed reduction algorithm indicate that the proposed algorithm outperforms other ECG reduction algorithms at a reduction/compression ratio (CR) of 5:1. If power or processing capacity is low, the algorithm can readily switch to a compression ratio of up to 10: 1 while still maintaining an error rate below 10%.
- Authors: Allami, Ragheed , Stranieri, Andrew , Balasubramanian, Venki , Jelinek, Herbert
- Date: 2016
- Type: Text , Conference proceedings
- Relation: 2016 12th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS); Naples, Italy; 28th November-1st December 2016 p. 520-525
- Full Text:
- Reviewed:
- Description: The transmission, storage and analysis of electrocardiogram (ECG) data in real-time is essential for remote patient monitoring with wearable ECG devices and mobile ECG contexts. However, this remains a challenge to achieve within the processing power and the storage capacity of mobile devices. ECG reduction algorithms have an important role to play in reducing the processing requirements for mobile devices, however many existing ECG reduction and compression algorithms are computationally expensive to execute in mobile devices and have not been designed for real-time computation and incremental data arrival. In this paper, we describe a computationally naive, yet effective, algorithm that achieves high ECG reduction rates while maintaining key diagnostic features including PR, QRS, ST, QT and RR intervals. While reduction does not enable ECG waves to be reproduced, the ability to transmit key indicators (diagnostic features) using minimal computational resources, is particularly useful in mobile health contexts involving power constrained sensors and devices. Results of the proposed reduction algorithm indicate that the proposed algorithm outperforms other ECG reduction algorithms at a reduction/compression ratio (CR) of 5:1. If power or processing capacity is low, the algorithm can readily switch to a compression ratio of up to 10: 1 while still maintaining an error rate below 10%.
Automated analysis of performance and energy consumption for cloud applications
- Chen, Feifei, Grundy, John, Schneider, Jean-Guy, Yang, Yun, He, Qiang
- Authors: Chen, Feifei , Grundy, John , Schneider, Jean-Guy , Yang, Yun , He, Qiang
- Date: 2014
- Type: Text , Conference paper
- Relation: Proceedings of the 5th ACM/SPEC international conference on Performance engineering p. 39-50
- Full Text:
- Reviewed:
- Description: In cloud environments, IT solutions are delivered to users via shared infrastructure. One consequence of this model is that large cloud data centres consume large amounts of energy and produce significant carbon footprints. A key objective of cloud providers is thus to develop resource provisioning and management solutions at minimum energy consumption while still guaranteeing Service Level Agreements (SLAs). However, a thorough understanding of both system performance and energy consumption patterns in complex cloud systems is imperative to achieve a balance of energy efficiency and acceptable performance. In this paper, we present StressCloud, a performance and energy consumption analysis tool for cloud systems. StressCloud can automatically generate load tests and profile system performance and energy consumption data. Using StressCloud, we have conducted extensive experiments to profile and analyse system performance and energy consumption with different types and mixes of runtime tasks. We collected fine-grained energy consumption and performance data with different resource allocation strategies, system configurations and workloads. The experimental results show the correlation coefficients of energy consumption, system resource allocation strategies and workload, as well as the performance of the cloud applications. Our results can be used to guide the design and deployment of cloud applications to balance energy and performance requirements.
- Authors: Chen, Feifei , Grundy, John , Schneider, Jean-Guy , Yang, Yun , He, Qiang
- Date: 2014
- Type: Text , Conference paper
- Relation: Proceedings of the 5th ACM/SPEC international conference on Performance engineering p. 39-50
- Full Text:
- Reviewed:
- Description: In cloud environments, IT solutions are delivered to users via shared infrastructure. One consequence of this model is that large cloud data centres consume large amounts of energy and produce significant carbon footprints. A key objective of cloud providers is thus to develop resource provisioning and management solutions at minimum energy consumption while still guaranteeing Service Level Agreements (SLAs). However, a thorough understanding of both system performance and energy consumption patterns in complex cloud systems is imperative to achieve a balance of energy efficiency and acceptable performance. In this paper, we present StressCloud, a performance and energy consumption analysis tool for cloud systems. StressCloud can automatically generate load tests and profile system performance and energy consumption data. Using StressCloud, we have conducted extensive experiments to profile and analyse system performance and energy consumption with different types and mixes of runtime tasks. We collected fine-grained energy consumption and performance data with different resource allocation strategies, system configurations and workloads. The experimental results show the correlation coefficients of energy consumption, system resource allocation strategies and workload, as well as the performance of the cloud applications. Our results can be used to guide the design and deployment of cloud applications to balance energy and performance requirements.
Coupling of cellular processes and their coordinated oscillations under continuous light in Cyanothece sp. ATCC 51142, a diazotrophic unicellular cyanobacterium
- Krishnakumar, Sujatha, Gaudana, Sandeep, Vinh, Nguyen, Viswanathan, Ganesh, Chetty, Madhu, Wangikar, Pramod
- Authors: Krishnakumar, Sujatha , Gaudana, Sandeep , Vinh, Nguyen , Viswanathan, Ganesh , Chetty, Madhu , Wangikar, Pramod
- Date: 2015
- Type: Text , Journal article
- Relation: PLoS ONE Vol. 10, no. 5 (2015), p. 1-23
- Full Text:
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- Description: Unicellular diazotrophic cyanobacteria such as Cyanothece sp. ATCC 51142 (henceforth Cyanothece), temporally separate the oxygen sensitive nitrogen fixation from oxygen evolving photosynthesis not only under diurnal cycles (LD) but also in continuous light (LL). However, recent reports demonstrate that the oscillations in LL occur with a shorter cycle time of ∼11 h. We find that indeed, majority of the genes oscillate in LL with this cycle time. Genes that are upregulated at a particular time of day under diurnal cycle also get upregulated at an equivalent metabolic phase under LL suggesting tight coupling of various cellular events with each other and with the cell's metabolic status. A number of metabolic processes get upregulated in a coordinated fashion during the respiratory phase under LL including glycogen degradation, glycolysis, oxidative pentose phosphate pathway, and tricarboxylic acid cycle. These precede nitrogen fixation apparently to ensure sufficient energy and anoxic environment needed for the nitrogenase enzyme. Photosynthetic phase sees upregulation of photosystem II, carbonate transport, carbon concentrating mechanism, RuBisCO, glycogen synthesis and light harvesting antenna pigment biosynthesis. In Synechococcus elongates PCC 7942, a non-nitrogen fixing cyanobacteria, expression of a relatively smaller fraction of genes oscillates under LL condition with the major periodicity being 24 h. In contrast, the entire cellular machinery of Cyanothece orchestrates coordinated oscillation in anticipation of the ensuing metabolic phase in both LD and LL. These results may have important implications in understanding the timing of various cellular events and in engineering cyanobacteria for biofuel production. © 2015 Krishnakumar et al.
- Authors: Krishnakumar, Sujatha , Gaudana, Sandeep , Vinh, Nguyen , Viswanathan, Ganesh , Chetty, Madhu , Wangikar, Pramod
- Date: 2015
- Type: Text , Journal article
- Relation: PLoS ONE Vol. 10, no. 5 (2015), p. 1-23
- Full Text:
- Reviewed:
- Description: Unicellular diazotrophic cyanobacteria such as Cyanothece sp. ATCC 51142 (henceforth Cyanothece), temporally separate the oxygen sensitive nitrogen fixation from oxygen evolving photosynthesis not only under diurnal cycles (LD) but also in continuous light (LL). However, recent reports demonstrate that the oscillations in LL occur with a shorter cycle time of ∼11 h. We find that indeed, majority of the genes oscillate in LL with this cycle time. Genes that are upregulated at a particular time of day under diurnal cycle also get upregulated at an equivalent metabolic phase under LL suggesting tight coupling of various cellular events with each other and with the cell's metabolic status. A number of metabolic processes get upregulated in a coordinated fashion during the respiratory phase under LL including glycogen degradation, glycolysis, oxidative pentose phosphate pathway, and tricarboxylic acid cycle. These precede nitrogen fixation apparently to ensure sufficient energy and anoxic environment needed for the nitrogenase enzyme. Photosynthetic phase sees upregulation of photosystem II, carbonate transport, carbon concentrating mechanism, RuBisCO, glycogen synthesis and light harvesting antenna pigment biosynthesis. In Synechococcus elongates PCC 7942, a non-nitrogen fixing cyanobacteria, expression of a relatively smaller fraction of genes oscillates under LL condition with the major periodicity being 24 h. In contrast, the entire cellular machinery of Cyanothece orchestrates coordinated oscillation in anticipation of the ensuing metabolic phase in both LD and LL. These results may have important implications in understanding the timing of various cellular events and in engineering cyanobacteria for biofuel production. © 2015 Krishnakumar et al.
A computer-aided sustainable modelling and optimization analysis of cnc milling and turning processes
- Singh, Karmjit, Sultan, Ibrahim
- Authors: Singh, Karmjit , Sultan, Ibrahim
- Date: 2018
- Type: Text , Journal article
- Relation: Journal of Manufacturing and Materials Processing Vol. 2, no. 4 (2018), p.
- Full Text:
- Reviewed:
- Description: The sustainability of a manufacturing process can be measured by three main factors which impact both ecological and financial constraints. These factors are the energy required to achieve a specific job, the material utilized for the job, and the time taken to complete that job. These factors have to be quantified and analysed so that a proper manufacturing system can be designed to optimize process sustainability. For this purpose, a computer package, which utilizes life cycle inventory models has been presented for CNC (Computer Numerical Control) milling and turning processes. Based on utilization of resources and production stages, the job completion time for the turning and milling processes can be divided into process (i.e., machining), idle and basic times. As parameters are different for evaluating the process times, i.e., depth and width of cut in case of milling, initial and final diameters for turning, two different case studies are presented, one for each process. The effect of material selection on the sustainability factors has been studied for different processes. Our simulations show that highly dense and hard materials take more time in finishing the job due to low cutting speed and feed rates as compared to soft materials. In addition, face milling takes longer and consumes more power as compared to peripheral milling due to more retraction time caused by over travel distance and lower vertical transverse speeds than the horizontal transverse speed used in a peripheral retraction process. © 2018 by the authors. Licensee MDPI, Basel, Switzerland.
- Authors: Singh, Karmjit , Sultan, Ibrahim
- Date: 2018
- Type: Text , Journal article
- Relation: Journal of Manufacturing and Materials Processing Vol. 2, no. 4 (2018), p.
- Full Text:
- Reviewed:
- Description: The sustainability of a manufacturing process can be measured by three main factors which impact both ecological and financial constraints. These factors are the energy required to achieve a specific job, the material utilized for the job, and the time taken to complete that job. These factors have to be quantified and analysed so that a proper manufacturing system can be designed to optimize process sustainability. For this purpose, a computer package, which utilizes life cycle inventory models has been presented for CNC (Computer Numerical Control) milling and turning processes. Based on utilization of resources and production stages, the job completion time for the turning and milling processes can be divided into process (i.e., machining), idle and basic times. As parameters are different for evaluating the process times, i.e., depth and width of cut in case of milling, initial and final diameters for turning, two different case studies are presented, one for each process. The effect of material selection on the sustainability factors has been studied for different processes. Our simulations show that highly dense and hard materials take more time in finishing the job due to low cutting speed and feed rates as compared to soft materials. In addition, face milling takes longer and consumes more power as compared to peripheral milling due to more retraction time caused by over travel distance and lower vertical transverse speeds than the horizontal transverse speed used in a peripheral retraction process. © 2018 by the authors. Licensee MDPI, Basel, Switzerland.
Sustainable manufacturing modelling : a case for milling process
- Singh, Karmjit, Sultan, Ibrahim
- Authors: Singh, Karmjit , Sultan, Ibrahim
- Date: 2019
- Type: Text , Journal article
- Relation: International Journal of Materials, Mechanics and Manufacturing Vol. 7, no. 1 (2019), p. 46-50
- Full Text:
- Reviewed:
- Description: In manufacturing industries, metal machining is very important process due to the competitiveness. Every manufacturer needs quick, effective and optimized processes. The experience of the operator plays a major role, but even for a skilled operator it is very difficult to attain the optimum values each time. Sustainability Analysis has attracted growing interests from industry, as an optimum cost estimation system analysis method, and energy consumption progress has been achieved. In this work, scrap production as well as production lead time have to be reduced and machining cost per kg of material is target. To reduce the cost, energy consumption and material wastage impact of the milling process worldwide many aspects of the process are investigated. In the present work, a system has been proposed, which can be used to determine various components of Sustainability analysis of milling process.
- Authors: Singh, Karmjit , Sultan, Ibrahim
- Date: 2019
- Type: Text , Journal article
- Relation: International Journal of Materials, Mechanics and Manufacturing Vol. 7, no. 1 (2019), p. 46-50
- Full Text:
- Reviewed:
- Description: In manufacturing industries, metal machining is very important process due to the competitiveness. Every manufacturer needs quick, effective and optimized processes. The experience of the operator plays a major role, but even for a skilled operator it is very difficult to attain the optimum values each time. Sustainability Analysis has attracted growing interests from industry, as an optimum cost estimation system analysis method, and energy consumption progress has been achieved. In this work, scrap production as well as production lead time have to be reduced and machining cost per kg of material is target. To reduce the cost, energy consumption and material wastage impact of the milling process worldwide many aspects of the process are investigated. In the present work, a system has been proposed, which can be used to determine various components of Sustainability analysis of milling process.
Modeling induction and routing to monitor hospitalized patients in multi-hop mobility-aware body area sensor networks
- Javaid, Nadeem, Ahmad, Ashfaq, Tauqir, Anum, Imran, Muhammad, Guizani, Mohsen, Khan, Zahoor, Qasim, Umar
- Authors: Javaid, Nadeem , Ahmad, Ashfaq , Tauqir, Anum , Imran, Muhammad , Guizani, Mohsen , Khan, Zahoor , Qasim, Umar
- Date: 2016
- Type: Text , Journal article
- Relation: Eurasip Journal on Wireless Communications and Networking Vol. 2016, no. 1 (2016), p.
- Full Text:
- Reviewed:
- Description: In wireless body area sensor networks (WBASNs), energy efficiency is an area of extreme significance. At first, we present a mathematical model for a non-invasive inductive link which is used to recharge the battery of an implanted biomedical device (pacemaker). Afterwards, we propose a distance-aware relaying energy-efficient (DARE) and mutual information-based DARE (MI-DARE) routing protocols for multihop mobility-aware body area sensor networks (MM-BASNs). Both the routing protocols and the non-invasive inductive link model are tested with the consideration of eight patients in a hospital unit under different topologies, where the vital signs of each patient are monitored through seven on-body sensors and an implanted pacemaker. To reduce energy consumption of the network, the sensors communicate with a sink via an on-body relay which is fixed on the chest of each patient. The behavior (static/mobile) and position of the sink are changed in each topology, and the impact of mobility due to postural changes of the patient(s) arms, legs, and head is also investigated. The MI-DARE protocol further prolongs the network lifetime by minimizing the number of transmissions. Simulation results show that the proposed techniques outperform contemporary schemes in terms of the selected performance metrics. © 2016, Javaid et al.
- Authors: Javaid, Nadeem , Ahmad, Ashfaq , Tauqir, Anum , Imran, Muhammad , Guizani, Mohsen , Khan, Zahoor , Qasim, Umar
- Date: 2016
- Type: Text , Journal article
- Relation: Eurasip Journal on Wireless Communications and Networking Vol. 2016, no. 1 (2016), p.
- Full Text:
- Reviewed:
- Description: In wireless body area sensor networks (WBASNs), energy efficiency is an area of extreme significance. At first, we present a mathematical model for a non-invasive inductive link which is used to recharge the battery of an implanted biomedical device (pacemaker). Afterwards, we propose a distance-aware relaying energy-efficient (DARE) and mutual information-based DARE (MI-DARE) routing protocols for multihop mobility-aware body area sensor networks (MM-BASNs). Both the routing protocols and the non-invasive inductive link model are tested with the consideration of eight patients in a hospital unit under different topologies, where the vital signs of each patient are monitored through seven on-body sensors and an implanted pacemaker. To reduce energy consumption of the network, the sensors communicate with a sink via an on-body relay which is fixed on the chest of each patient. The behavior (static/mobile) and position of the sink are changed in each topology, and the impact of mobility due to postural changes of the patient(s) arms, legs, and head is also investigated. The MI-DARE protocol further prolongs the network lifetime by minimizing the number of transmissions. Simulation results show that the proposed techniques outperform contemporary schemes in terms of the selected performance metrics. © 2016, Javaid et al.
Efficient data gathering in 3D linear underwater wireless sensor networks using sink mobility
- Akbar, Mariam, Javaid, Nadeem, Khan, Ayesha, Imran, Muhammad, Shoaib, Muhammad, Vasilakos, Athanasios
- Authors: Akbar, Mariam , Javaid, Nadeem , Khan, Ayesha , Imran, Muhammad , Shoaib, Muhammad , Vasilakos, Athanasios
- Date: 2016
- Type: Text , Journal article
- Relation: Sensors (Switzerland) Vol. 16, no. 3 (2016), p.
- Full Text:
- Reviewed:
- Description: Due to the unpleasant and unpredictable underwater environment, designing an energy-efficient routing protocol for underwater wireless sensor networks (UWSNs) demands more accuracy and extra computations. In the proposed scheme, we introduce a mobile sink (MS), i.e., an autonomous underwater vehicle (AUV), and also courier nodes (CNs), to minimize the energy consumption of nodes. MS and CNs stop at specific stops for data gathering; later on, CNs forward the received data to the MS for further transmission. By the mobility of CNs and MS, the overall energy consumption of nodes is minimized. We perform simulations to investigate the performance of the proposed scheme and compare it to preexisting techniques. Simulation results are compared in terms of network lifetime, throughput, path loss, transmission loss and packet drop ratio. The results show that the proposed technique performs better in terms of network lifetime, throughput, path loss and scalability. © 2016 by the authors; licensee MDPI, Basel, Switzerland.
- Authors: Akbar, Mariam , Javaid, Nadeem , Khan, Ayesha , Imran, Muhammad , Shoaib, Muhammad , Vasilakos, Athanasios
- Date: 2016
- Type: Text , Journal article
- Relation: Sensors (Switzerland) Vol. 16, no. 3 (2016), p.
- Full Text:
- Reviewed:
- Description: Due to the unpleasant and unpredictable underwater environment, designing an energy-efficient routing protocol for underwater wireless sensor networks (UWSNs) demands more accuracy and extra computations. In the proposed scheme, we introduce a mobile sink (MS), i.e., an autonomous underwater vehicle (AUV), and also courier nodes (CNs), to minimize the energy consumption of nodes. MS and CNs stop at specific stops for data gathering; later on, CNs forward the received data to the MS for further transmission. By the mobility of CNs and MS, the overall energy consumption of nodes is minimized. We perform simulations to investigate the performance of the proposed scheme and compare it to preexisting techniques. Simulation results are compared in terms of network lifetime, throughput, path loss, transmission loss and packet drop ratio. The results show that the proposed technique performs better in terms of network lifetime, throughput, path loss and scalability. © 2016 by the authors; licensee MDPI, Basel, Switzerland.
Obfuscated memory malware detection in resource-constrained iot devices for smart city applications
- Shafin, Sakib, Karmakar, Gour, Mareels, Iven
- Authors: Shafin, Sakib , Karmakar, Gour , Mareels, Iven
- Date: 2023
- Type: Text , Journal article
- Relation: Sensors Vol. 23, no. 11 (2023), p. 5348
- Full Text:
- Reviewed:
- Description: Obfuscated Memory Malware (OMM) presents significant threats to interconnected systems, including smart city applications, for its ability to evade detection through concealment tactics. Existing OMM detection methods primarily focus on binary detection. Their multiclass versions consider a few families only and, thereby, fail to detect much existing and emerging malware. Moreover, their large memory size makes them unsuitable to be executed in resource-constrained embedded/IoT devices. To address this problem, in this paper, we propose a multiclass but lightweight malware detection method capable of identifying recent malware and is suitable to execute in embedded devices. For this, the method considers a hybrid model by combining the feature-learning capabilities of convolutional neural networks with the temporal modeling advantage of bidirectional long short-term memory. The proposed architecture exhibits compact size and fast processing speed, making it suitable for deployment in IoT devices that constitute the major components of smart city systems. Extensive experiments with the recent CIC-Malmem-2022 OMM dataset demonstrate that our method outperforms other machine learning-based models proposed in the literature in both detecting OMM and identifying specific attack types. Our proposed method thus offers a robust yet compact model executable in IoT devices for defending against obfuscated malware.
- Authors: Shafin, Sakib , Karmakar, Gour , Mareels, Iven
- Date: 2023
- Type: Text , Journal article
- Relation: Sensors Vol. 23, no. 11 (2023), p. 5348
- Full Text:
- Reviewed:
- Description: Obfuscated Memory Malware (OMM) presents significant threats to interconnected systems, including smart city applications, for its ability to evade detection through concealment tactics. Existing OMM detection methods primarily focus on binary detection. Their multiclass versions consider a few families only and, thereby, fail to detect much existing and emerging malware. Moreover, their large memory size makes them unsuitable to be executed in resource-constrained embedded/IoT devices. To address this problem, in this paper, we propose a multiclass but lightweight malware detection method capable of identifying recent malware and is suitable to execute in embedded devices. For this, the method considers a hybrid model by combining the feature-learning capabilities of convolutional neural networks with the temporal modeling advantage of bidirectional long short-term memory. The proposed architecture exhibits compact size and fast processing speed, making it suitable for deployment in IoT devices that constitute the major components of smart city systems. Extensive experiments with the recent CIC-Malmem-2022 OMM dataset demonstrate that our method outperforms other machine learning-based models proposed in the literature in both detecting OMM and identifying specific attack types. Our proposed method thus offers a robust yet compact model executable in IoT devices for defending against obfuscated malware.
A survey of commercial and industrial demand response flexibility with energy storage systems and renewable energy
- Yasmin, Roksana, Amin, B.M. Ruhu, Shah, Rakibuzzaman, Barton, Andrew
- Authors: Yasmin, Roksana , Amin, B.M. Ruhu , Shah, Rakibuzzaman , Barton, Andrew
- Date: 2024
- Type: Text , Journal article , Review
- Relation: Sustainability (Switzerland) Vol. 16, no. 2 (2024), p.
- Full Text:
- Reviewed:
- Description: The transition from traditional fuel-dependent energy systems to renewable energy-based systems has been extensively embraced worldwide. Demand-side flexibility is essential to support the power grid with carbon-free generation (e.g., solar, wind.) in an intermittent nature. As extensive energy consumers, commercial and industrial (C&I) consumers can play a key role by extending their flexibility and participating in demand response. Onsite renewable generation by consumers can reduce the consumption from the grid, while energy storage systems (ESSs) can support variable generation and shift demand by storing energy for later use. Both technologies can increase the flexibility and benefit by integrating with the demand response. However, a lack of knowledge about the applicability of increasing flexibility hinders the active participation of C&I consumers in demand response programs. This survey paper provides an overview of demand response and energy storage systems in this context following a methodology of a step-by-step literature review covering the period from 2013 to 2023. The literature review focuses on the application of energy storage systems and onsite renewable generation integrated with demand response for C&I consumers and is presented with an extensive analysis. This survey also examines the demand response participation and potential of wastewater treatment plants. The extended research on the wastewater treatment plant identifies the potential opportunities of coupling biogas with PV, extracting the thermal energy and onsite hydrogen production. Finally, the survey analysis is summarised, followed by critical recommendations for future research. © 2024 by the authors.
- Authors: Yasmin, Roksana , Amin, B.M. Ruhu , Shah, Rakibuzzaman , Barton, Andrew
- Date: 2024
- Type: Text , Journal article , Review
- Relation: Sustainability (Switzerland) Vol. 16, no. 2 (2024), p.
- Full Text:
- Reviewed:
- Description: The transition from traditional fuel-dependent energy systems to renewable energy-based systems has been extensively embraced worldwide. Demand-side flexibility is essential to support the power grid with carbon-free generation (e.g., solar, wind.) in an intermittent nature. As extensive energy consumers, commercial and industrial (C&I) consumers can play a key role by extending their flexibility and participating in demand response. Onsite renewable generation by consumers can reduce the consumption from the grid, while energy storage systems (ESSs) can support variable generation and shift demand by storing energy for later use. Both technologies can increase the flexibility and benefit by integrating with the demand response. However, a lack of knowledge about the applicability of increasing flexibility hinders the active participation of C&I consumers in demand response programs. This survey paper provides an overview of demand response and energy storage systems in this context following a methodology of a step-by-step literature review covering the period from 2013 to 2023. The literature review focuses on the application of energy storage systems and onsite renewable generation integrated with demand response for C&I consumers and is presented with an extensive analysis. This survey also examines the demand response participation and potential of wastewater treatment plants. The extended research on the wastewater treatment plant identifies the potential opportunities of coupling biogas with PV, extracting the thermal energy and onsite hydrogen production. Finally, the survey analysis is summarised, followed by critical recommendations for future research. © 2024 by the authors.
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