DEVELOPMENT OF IoT BASED SMART INVERTER FOR ENERGY METERING AND CONTROL

Insufficient power generation has facilitated the search for alternative power generation, as the world is gradually making the transition to renewable green energy sources as a replacement for fossil fuels and other conventional power generation methods that causes environmental pollution. One of these methods is the use of solar energy for electricity generation through the use of the photovoltaic solar inverter which harnesses the power from the sun to generate electricity. The inability of electricity distributors to provide enough and sustainable power supply for homes and businesses, coupled with the need to live a smart life has made humans sort for an easier control method of electricity generation and usage. Hence, this research presents a smart voice and mobile application control modular inverter integrated with a smart metered energy distribution system, which equally distributes power amongst the users for effective and smart energy usage. A test of applied load on the inverter as compared to normal electricity usage deduced an 8% error rate giving a 92% accuracy for the inverter. The mobile app was tested for both online and offline usage and a 67% accuracy was deduced as the overall accuracy of the software. This gives an inference that the system can be fully operated by a user in the luxury of their comfort. For smart meter monitoring and energy allocation, 93.33% and 96.8% accuracy and precision were achieved respectively. This research makes the usage of green energy more efficient with its feature which allows for equal distribution of energy. The system also helps prevent energy theft or misuse by providing only the proper user with alerts and administrative control.

Power Conversion Performance of a Single-Phase PV Inverter with Fuzzy Logic Algorithm

The paper presents a low-power conversion system focusing on implementing new solar inverter control techniques implemented with Fuzzy Logic. The power generated by a solar panel requires robust approaches and efficient methods to be used at its maximum. Therefore, a promising strategy is a Fuzzy Logic based on the Maximum Power Point Tracking (MPPT) algorithm. To gather efficient power conversion, our proposed model uses a control loop composed of Fuzzy Proportional Integrative (PI) regulators, Clarke and Park transform, followed by a synchronization grid mechanism Second-order generalized integrator (SOGI) based phase-locked loops (PLLs). The proposed technique examines photovoltaic system (PV) performance with respect to its non-linearities and eventual shaded conditions that can occur in the PV array. The shading effect is tested by varying the irradiance, which determines the variation of the output current and implicitly of the output power. The simulation results show that the inverter control system is very efficient, generating stable and nearly sinusoidal current and voltage characteristics. Thus, the inverter converts over 99 % of the power generated by PV arrays.

Outline and Testing of Portable Solar Inverter

In this study we talk about ,a simulacrum of one phase inverter using solar energy, The main aim is use of solar energy for electricity to study about Portable inverter, to use solar energy for electricity . Inverter circuits consists of Ups , battery module and battery charger. The main work of Inverter is to convert D.C voltage to A.C voltage .Inverter circuit are divided into 3 parts Bjt switch ,control circuit which is use for generate pluses thorough micro controller ,filter part consists of capacitor, Resistor which is use to overcome of harmonics. The main purpose of this work, to be simple such as for as assessing knowledge about solar movable inverter with minimum cost and uses. Keywords: Solar panel, Regulator, battery charger, Inverter circuit, switching device, Transformer.

Techno-economic-enviro optimization analysis of diesel/PV/wind with pumped hydro storage for Mentawai Island microgrid

This paper presents a techno-economic analysis and environment assessment of hybrid photovoltaic (PV), wind turbine (WT), and diesel genset (DG) with pumped hydro storage (PHS) for a rural microgrid system. The analysis is carried out for a case study with Mentawai community load demand of 165.44 kWh/day at a peak load of 20.46 kW. The Homer simulation results show that there are eight feasible configurations, which the optimal hybrid system configuration to supply community load is the configuration with PV/DG/PHS. An optimal system has been achieved for the lowest NPC of Indonesian rupiah (IDR) 3,00 B consist of 15 kWp PV modules, 1 unit of PHS and a solar inverter with a size 25 kW. The net present cost and payback period are in accordance with criteria for the economic feasibility analysis method of a project. However, the cost of energy is greater than the electrical utility tariff, but this value can be considered for applications in the remote island area. Therefore, the project still feasible to be implemented. Since the renewable fraction of the system is increased hence this proposed system will have the lowest carbon emission.

Design and Analysis of a Grid-Integrated Residential Solar PV System

Controlling the single-phase PV system improves system performance, safety, reliability, and controllability while interacting with the energy grid. The primary goal of this research is to create an Artificial Neural Network (ANN) vector control method for a single-phase solar inverter. The ANN controller is trained using approximation dynamic programming to obtain optimum control. To evaluate an ANN-based solar PV system, models of PV system behaviour for grid integration and maximum power extraction from solar PV arrays in a genuine residential PV application, as well as the development of an experimental solar PV system, are employed. The findings show that an ANN-controlled PV system outperforms a typical vector-controlled PV system in terms of performance.