ORCID Profile
0000-0002-0534-4801
Current Organisation
Monash University Malaysia
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Publisher: Institute of Advanced Engineering and Science
Date: 09-2014
Publisher: IEEE
Date: 12-2014
Publisher: MDPI AG
Date: 21-09-2022
DOI: 10.3390/SU141911913
Abstract: The Sustainable Development Goals (SDGs) play an essential role, emphasizing responsible resource use, production, and consumption, including waste management. In addition, SDG 3, 7, 11, 12, and 13 are directly/indirectly related to waste management. This study aims to determine a suitable waste-to-energy (WtE) technology in Chittagong City, Bangladesh, focusing on cleaner technology. Anaerobic digestion, gasification, incineration, and landfill gas (LFG) recovery were considered as possible alternatives. Technical, economic, environmental, and social issues have been considered as necessary criteria for evaluation. An analytical hierarchy process was applied to rank these technologies based on stakeholders’ perceptions. The study found that anaerobic digestion (AD) ranked first, receiving 38% of overall weight. The second preferred technology is LFG (27%). Gasification and incineration stood at third and fourth, respectively (21% and 14%). According to a sensitivity study, the decision is only sensitive to the economy. LFG will become the most favoured solution for WtE conversion if the economy prioritizes more than 38%. Subsequently, this study’s findings will help achieve Bangladesh’s SDG agenda.
Publisher: MDPI AG
Date: 02-06-2021
DOI: 10.3390/MI12060653
Abstract: Conventional wireless sensor networks (WSNs) in smart home-building (SHB) are typically driven by batteries, limiting their lifespan and the maximum number of deployable units. To satisfy the energy demand for the next generation of SHB which can interconnect WSNs to make the internet of smart home-building (IoSHB), this study introduces the design and implementation of a 250 mW to 2.3 W energy harvesting device. The proposed device is dynamically autonomous owing to the integration of embedded solar photovoltaic (PV) modules and power storage through a supercapacitor (SC 5 V, 0.47 F) capable of powering WSNs for 95 s (up to 4.11 V). The deployed device can harvest indoor and outdoor ambient light at a minimum illumination of 50 lux and a maximum illumination of 200 lux. Moreover, the proposed system supports wireless fidelity (Wi-Fi) and Bluetooth Low Energy (BLE) to do data transfer to a webserver as a complete internet of things (IoT) device. A customized android dashboard is further developed for data monitoring on a smartphone. All in all, this self-powered WSN node can interface with the users of the SHBs for displaying ambient data, which demonstrates its promising applicability and stability.
Publisher: MDPI AG
Date: 23-11-2021
DOI: 10.3390/EN14237857
Abstract: Distributed generation (DG) is gaining importance as electrical energy demand increases. DG is used to decrease power losses, operating costs, and improve voltage stability. Most DG resources have less environmental impact. In a particular region, the sizing and location of DG resources significantly affect the planned DG integrated distribution network (DN). The voltage profiles of the DN will change or even become excessively increased. An enormous DG active power, inserted into an improper node of the distribution network, may bring a larger current greater than the conductor’s maximum value, resulting in an overcurrent distribution network. Therefore, DG sizing and DG location optimization is required for a systematic DG operation to fully exploit distributed energy and achieve mutual energy harmony across existing distribution networks, which creates an economically viable, secure, stable, and dependable power distribution system. DG needs to access the location and capacity for rational planning. The objective function of this paper is to minimize the sum of investment cost, operation cost, and line loss cost utilizing DG access. The probabilistic power flow calculation technique based on the two-point estimation method is chosen for this paper’s load flow computation. The location and size of the DG distribution network are determined using a genetic algorithm in a MATLAB environment. For the optimum solution, the actual power load is estimated using historical data. The proposed system is based on the China distribution system, and the currency is used in Yuan. After DG access, active and reactive power losses are reduced by 53% and 26%, respectively. The line operating cost and the total annual cost are decreased by 53.7% and 12%, respectively.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2021
Publisher: IEEE
Date: 05-2015
Location: Bangladesh
Location: Bangladesh
Location: Bangladesh
Location: Malaysia
Location: Malaysia
No related grants have been discovered for Md. Rokonuzzaman.