Faculty of Engineering Research Unit (ERU & MERCon)http://dl.lib.uom.lk/handle/123/146702024-03-29T10:29:06Z2024-03-29T10:29:06ZFeasibility of vapour absorption based air- conditioning in industries: a case studyWijayatunga, PDCAttalage, RASugathapala, AGThttp://dl.lib.uom.lk/handle/123/93252020-02-19T08:15:17Z1999-01-01T00:00:00ZFeasibility of vapour absorption based air- conditioning in industries: a case study
Wijayatunga, PDC; Attalage, RA; Sugathapala, AGT
This paper presents the results of financial and technical feasibility of vapour absorption based air- conditioning systems (VAAC) in an industrial environment in comparison to vapour compression based systems (VCAC). The financial analysis of the study involves three possible scenarios including a waste heat recovery based system. It is concluded that the most attractive option is to install VAAC systems at the initial stages of construction of the factory premises. The other options involving existing industrial installations where waste heat recovery from standby generator units can be utilised, provide internal rates of return (IRR) varying from 1.9% to 24% and simple pay back periods vaiying from 11 years to 5 years respectively. The latter two options are applicable to existing installations.
The most attractive option for the industrial installation selected in the case study is where a VAAC system is provided to supplement the existing VCAC system. This is likely to give an IRR of 14% and a simple pay back period of 8 years under present conditions.
1999-01-01T00:00:00ZMoratuwa Engineering Research Conference 2023 (Pre Text)http://dl.lib.uom.lk/handle/123/223882024-03-26T01:10:23Z2023-12-09T00:00:00ZMoratuwa Engineering Research Conference 2023 (Pre Text)
Abeysooriya, R; Adikariwattage, V; Hemachandra, K
2023-12-09T00:00:00ZImplementation of a large piezoresistive sensor array scanning mechanism based on xilinx zynq apsocWarnakulasuriya, ADe Silva, AChttp://dl.lib.uom.lk/handle/123/223872024-03-26T01:38:31Z2023-12-09T00:00:00ZImplementation of a large piezoresistive sensor array scanning mechanism based on xilinx zynq apsoc
Warnakulasuriya, A; De Silva, AC
Abeysooriya, R; Adikariwattage, V; Hemachandra, K
The foremost complication of scanning a large sensor
array is the increased number of sensors which generate large
volumes of data. Hence, a suitable hardware based implementation
is necessary to manage such data efficiently. We formulated
a scanning mechanism for a large piezoresistive sensor array
using a Xilinx Zynq device and custom developed RTL modules.
The zynq device acts as the brain of the scanning mechanism
issuing control signals and acquiring ADC readings. Therefore,
we developed a scanning mechanism using a combination of
Xilinx standard IP cores and custom made RTL modules, and
deployed it in a zynq device. Performance of the implemented
mechanism depends primarily on the developed adc 0 module.
It inherits bulk of the functionality of the developed system.
Hence, behavioral simulations were conducted on Vivado design
suite with respect to data buffering capability, control signal
issuance, data alignment and transmission for the adc 0 module.
Subsequent overall analysis conducted on the system indicated
that the developed system is efficiently functioning.
2023-12-09T00:00:00ZDevelopment of ai-based optimum energy resource management system for prosumers with solar rooftopsWeerasekara, DHNRWella Arachchi, WAPKWellala, SRGRodrigo, AShttp://dl.lib.uom.lk/handle/123/223862024-03-26T01:24:33Z2023-12-09T00:00:00ZDevelopment of ai-based optimum energy resource management system for prosumers with solar rooftops
Weerasekara, DHNR; Wella Arachchi, WAPK; Wellala, SRG; Rodrigo, AS
Abeysooriya, R; Adikariwattage, V; Hemachandra, K
Solar installations are becoming popular around the
world and have emerged as a promising solution to address
the increased energy needs while reducing carbon emissions. To
harness the full potential of solar photovoltaic (PV) systems,
efficient resource management systems play a vital role. This
research paper proposes an efficient solar PV energy resource
management system to optimize performance and increase the
profits of the prosumers. Utility providers have introduced several
tariff systems for the financial motivation of customers. In the
proposed method, the load demand and Solar PV generation are
forecasted for the next 48 hours using the Long Short-Term Memory
(LSTM) model. Then, the cost function is optimized using
the Sequential Least Squares Programming (SLSQP) algorithm,
and an energy dispatch schedule is provided for the customer.
The results of the study show that the electricity cost is reduced
for the prosumer by the proposed method than the conventional
rule-based energy management systems.
2023-12-09T00:00:00Z