Intelligent energy facilities, e.g., smart grids and microgrids are the evolution of traditional energy grids through digital transformation. These modern paradigms are expected to foster the utilization of renewable energies, sustainable development, and resilience of the power grid. A barrier found when deploying experimental smart grids and microgrids consists of handling the heterogeneity of the required hardware and software components as well as the available commercial equipment. Despite the fact that there is various architecture proposed in previous literature, it commonly lacks experimental validation, specification of involved equipment concerning industrial/proprietary or open-source nature, and concretization of communication protocols. To overcome such drawbacks, this paper proposes an innovative multi-layered architecture to deploy heterogeneous automation and monitoring systems for microgrids. The architecture is structured into six functional layers to organize the hardware and software equipment in an integrated manner. The open protocol Modbus TCP is chosen to harmonize communications, enabling the interconnection of equipment from industrial and energy scopes, indeed of open-source nature. An experimental photovoltaic-based smart microgrid is reported as the application case to demonstrate the suitability and validity of the proposal.
Smart grids and smart microgrids (SMGs) require proper monitoring for their operation. To this end, measuring, data acquisition, and storage, as well as remote online visualization of real-time information, must be performed using suitable equipment. An experimental SMG is being deployed that combines photovoltaics and the energy carrier hydrogen through the interconnection of photovoltaic panels, electrolyser, fuel cell, and load around a voltage bus powered by a lithium battery. This paper presents a monitoring system based on open-source hardware and software for tracking the temperature of the photovoltaic generator in such an SMG. In fact, the increases in temperature in PV modules lead to a decrease in their efficiency, so this parameter needs to be measured in order to monitor and evaluate the operation. Specifically, the developed monitoring system consists of a network of digital temperature sensors connected to an Arduino microcontroller, which feeds the acquired data to a Raspberry Pi microcomputer. The latter is accessed by a cloud-enabled user/operator interface implemented in Grafana. The monitoring system is expounded and experimental results are reported to validate the proposal.
Photovoltaic (PV) energy is a renewable energy resource which is being widely integrated in intelligent power grids, smart grids, and microgrids. To characterize and monitor the behavior of PV modules, current-voltage (I-V) curves are essential. In this regard, Internet of Things (IoT) technologies provide versatile and powerful tools, constituting a modern trend in the design of sensing and data acquisition systems for I-V curve tracing. This paper presents a novel I-V curve tracer based on IoT open-source hardware and software. Namely, a Raspberry Pi microcomputer composes the hardware level, whilst the applied software comprises mariaDB, Python, and Grafana. All the tasks required for curve tracing are automated: load sweep, data acquisition, data storage, communications, and real-time visualization. Modern and legacy communication protocols are handled for seamless data exchange with a programmable logic controller and a programmable load. The development of the system is expounded, and experimental results are reported to prove the suitability and validity of the proposal. In particular, I-V curve tracing of a monocrystalline PV generator under real operating conditions is successfully conducted.
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