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Evaluating IoT based passive water catchment monitoring system data acquisition and analysis Muhammad Aznil Ab Aziz; M. F. Abas; Mohamad Khairul Anwar Abu Bashri; N. Md. Saad; M. H. Ariff
Bulletin of Electrical Engineering and Informatics Vol 8, No 4: December 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (815.5 KB) | DOI: 10.11591/eei.v8i4.1583

Abstract

Water quality is the main aspect to determine the quality of aquatic systems. Poor water quality will pose a health risk for people and ecosystems. The old methods such as collecting samples of water manually and testing and analysing at lab will cause the time consuming, wastage of man power and not economical. A system is needed to provide a real-time data for environmental protection and tracking pollution sources. This paper aims to describe on how to monitor water quality continuously through IoT platform. Water Quality Catchment Monitoring System was introduced to check and monitor water quality continuously. It’s features five sensors which are temperature sensor, light intensity sensor, pH sensor, GPS tracker and Inertia Movement Unit (IMU). IMU is a new feature in the system where the direction of x and y is determined for planning and find out where a water quality problem exists by determining the flow of water. The system uses an internet wireless connection using the ESP8266 Wi-Fi Shield Module as a connection between Arduino Mega2560 and laptop. ThingSpeak application acts as an IoT platform used for real-time data monitoring.
Evaluating IoT based passive water catchment monitoring system data acquisition and analysis Muhammad Aznil Ab Aziz; M. F. Abas; Mohamad Khairul Anwar Abu Bashri; N. Md. Saad; M. H. Ariff
Bulletin of Electrical Engineering and Informatics Vol 8, No 4: December 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (815.5 KB) | DOI: 10.11591/eei.v8i4.1583

Abstract

Water quality is the main aspect to determine the quality of aquatic systems. Poor water quality will pose a health risk for people and ecosystems. The old methods such as collecting samples of water manually and testing and analysing at lab will cause the time consuming, wastage of man power and not economical. A system is needed to provide a real-time data for environmental protection and tracking pollution sources. This paper aims to describe on how to monitor water quality continuously through IoT platform. Water Quality Catchment Monitoring System was introduced to check and monitor water quality continuously. It’s features five sensors which are temperature sensor, light intensity sensor, pH sensor, GPS tracker and Inertia Movement Unit (IMU). IMU is a new feature in the system where the direction of x and y is determined for planning and find out where a water quality problem exists by determining the flow of water. The system uses an internet wireless connection using the ESP8266 Wi-Fi Shield Module as a connection between Arduino Mega2560 and laptop. ThingSpeak application acts as an IoT platform used for real-time data monitoring.
Solar irradiance uncertainty management based on Monte Carlo-beta probability density function: case in Malaysian tropical climate N. Md. Saad; M. Z. Sujod; M. I. M. Ridzuan; M. F. Abas; M. S. Jadin; M. S. Bakar; A. Z. Ahmad
Bulletin of Electrical Engineering and Informatics Vol 8, No 3: September 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1812.039 KB) | DOI: 10.11591/eei.v8i4.1581

Abstract

In recent years, solar PV power generation has seen a rapid growth due to environmental benefits and zero fuel costs. In Malaysia, due to its location near the equator, makes solar energy the most utilized renewable energy resources. Unlike conventional power generation, solar energy is considered as uncertain generation sources which will cause unstable energy supplied. The uncertainty of solar resource needs to be managed for the planning of the PV system to produce its maximum power. The statistical method is the most prominent to manage and model the solar irradiance uncertainty patterns. Based on one-minute time interval meteorological data taken in Pekan, Pahang, West Malaysia, the Monte Carlo-Beta probability density function (Beta PDF) is performed to model continuous random variable of solar irradiance. The uncertainty studies are needed to optimally plan the photovoltaic system for the development of solar PV technologies in generating electricity and enhance the utilization of renewable energy; especially in tropical climate region.
Evaluating IoT based passive water catchment monitoring system data acquisition and analysis Muhammad Aznil Ab Aziz; M. F. Abas; Mohamad Khairul Anwar Abu Bashri; N. Md. Saad; M. H. Ariff
Bulletin of Electrical Engineering and Informatics Vol 8, No 4: December 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (815.5 KB) | DOI: 10.11591/eei.v8i4.1583

Abstract

Water quality is the main aspect to determine the quality of aquatic systems. Poor water quality will pose a health risk for people and ecosystems. The old methods such as collecting samples of water manually and testing and analysing at lab will cause the time consuming, wastage of man power and not economical. A system is needed to provide a real-time data for environmental protection and tracking pollution sources. This paper aims to describe on how to monitor water quality continuously through IoT platform. Water Quality Catchment Monitoring System was introduced to check and monitor water quality continuously. It’s features five sensors which are temperature sensor, light intensity sensor, pH sensor, GPS tracker and Inertia Movement Unit (IMU). IMU is a new feature in the system where the direction of x and y is determined for planning and find out where a water quality problem exists by determining the flow of water. The system uses an internet wireless connection using the ESP8266 Wi-Fi Shield Module as a connection between Arduino Mega2560 and laptop. ThingSpeak application acts as an IoT platform used for real-time data monitoring.
Impacts of Photovoltaic Distributed Generation Location and Size on Distribution Power System Network N. Md. Saad; M. Z. Sujod; Lee Hui Ming; M. F. Abas; M. S. Jadin; M. R. Ishak; N. R. H. Abdullah
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 9, No 2: June 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (793.705 KB) | DOI: 10.11591/ijpeds.v9.i2.pp905-913

Abstract

As the rapid development of photovoltaic (PV) technology in recent years with the growth of electricity demand, integration of photovoltaic distributed generation (PVDG) to the distribution system is emerging to fulfil the demand. There are benefits and drawbacks to the distribution system due to the penetration of PVDG. This paper discussed and investigated the impacts of PVDG location and size on distribution power systems. The medium voltage distribution network is connected to the grid with the load being supplied by PVDG. Load flow and short circuit calculation are analyzed by using DigSILENT Power Factory Software. Comparisons have been made between the typical distribution system and the distribution system with the penetration of PVDG. Impacts in which PVDG location and size integrates with distribution system are investigated with the results given from the load flow and short circuit analysis. The results indicate positive impacts on the system interconnected with PVDG such as improving voltage profile, reducing power losses, releasing transmission and distribution grid capacity. It also shows that optimal locations and sizes of DGs are needed to minimize the system’s power losses. On the other hand, it shows that PVDG interconnection to the system can cause reverse power flow at improper DG size and location and increases short circuit level.
Solar irradiance uncertainty management based on Monte Carlo-beta probability density function: case in Malaysian tropical climate N. Md. Saad; M. Z. Sujod; M. I. M. Ridzuan; M. F. Abas; M. S. Jadin; M. S. Bakar; A. Z. Ahmad
Bulletin of Electrical Engineering and Informatics Vol 8, No 3: September 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1812.039 KB) | DOI: 10.11591/eei.v8i3.1581

Abstract

In recent years, solar PV power generation has seen a rapid growth due to environmental benefits and zero fuel costs. In Malaysia, due to its location near the equator, makes solar energy the most utilized renewable energy resources. Unlike conventional power generation, solar energy is considered as uncertain generation sources which will cause unstable energy supplied. The uncertainty of solar resource needs to be managed for the planning of the PV system to produce its maximum power. The statistical method is the most prominent to manage and model the solar irradiance uncertainty patterns. Based on one-minute time interval meteorological data taken in Pekan, Pahang, West Malaysia, the Monte Carlo-Beta probability density function (Beta PDF) is performed to model continuous random variable of solar irradiance. The uncertainty studies are needed to optimally plan the photovoltaic system for the development of solar PV technologies in generating electricity and enhance the utilization of renewable energy; especially in tropical climate region.
Solar irradiance uncertainty management based on Monte Carlo-beta probability density function: case in Malaysian tropical climate N. Md. Saad; M. Z. Sujod; M. I. M. Ridzuan; M. F. Abas; M. S. Jadin; M. S. Bakar; A. Z. Ahmad
Bulletin of Electrical Engineering and Informatics Vol 8, No 3: September 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1812.039 KB) | DOI: 10.11591/eei.v8i4.1581

Abstract

In recent years, solar PV power generation has seen a rapid growth due to environmental benefits and zero fuel costs. In Malaysia, due to its location near the equator, makes solar energy the most utilized renewable energy resources. Unlike conventional power generation, solar energy is considered as uncertain generation sources which will cause unstable energy supplied. The uncertainty of solar resource needs to be managed for the planning of the PV system to produce its maximum power. The statistical method is the most prominent to manage and model the solar irradiance uncertainty patterns. Based on one-minute time interval meteorological data taken in Pekan, Pahang, West Malaysia, the Monte Carlo-Beta probability density function (Beta PDF) is performed to model continuous random variable of solar irradiance. The uncertainty studies are needed to optimally plan the photovoltaic system for the development of solar PV technologies in generating electricity and enhance the utilization of renewable energy; especially in tropical climate region.