19-05-2012, 11:36 AM
REMOTE MONITORING AND CONTROL OF PHOTOVOLTAIC SYSTEM USING WIRELESS SENSOR NETWORK
ABSTRACT
Efficient energy yield is a major concern in photovoltaic systems in solar energy supply. Smart photovoltaic modules offer a potential solution to allow solar generators to maximize their productivity.
This paper describes details of the design and instrumentation of smart photovoltaic modules, a wireless sensor network, and software for real-time sensing and control of a photovoltaic system with maximum power point tracking at module level.
Field condition is monitored by voltage, current, irradiance, and temperature sensors distributed across the photovoltaic field. The sensory data are periodically sampled and transmitted to a base station. The power point is controlled by a integrated DC-DC converter.
The output voltage in the converter is regulated by a digital controller. The reference voltage is calculated based on a neural network model, which is used to identify maximum power point.
The communication data for remote monitoring and distributed control are successfully transmitted using a low-cost ZigBee wireless network. The web-based software developed in this paper offers stable remote access to field conditions and real-time control of the power points in the smart photovoltaic system.
ABSTRACT
Efficient energy yield is a major concern in photovoltaic systems in solar energy supply. Smart photovoltaic modules offer a potential solution to allow solar generators to maximize their productivity.
This paper describes details of the design and instrumentation of smart photovoltaic modules, a wireless sensor network, and software for real-time sensing and control of a photovoltaic system with maximum power point tracking at module level.
Field condition is monitored by voltage, current, irradiance, and temperature sensors distributed across the photovoltaic field. The sensory data are periodically sampled and transmitted to a base station. The power point is controlled by a integrated DC-DC converter.
The output voltage in the converter is regulated by a digital controller. The reference voltage is calculated based on a neural network model, which is used to identify maximum power point.
The communication data for remote monitoring and distributed control are successfully transmitted using a low-cost ZigBee wireless network. The web-based software developed in this paper offers stable remote access to field conditions and real-time control of the power points in the smart photovoltaic system.