Integration of renewable energy sources (RESs) into electric power grids is increasing day by day. In the world, solar energy potential is at a high level among RESs. Thus, solar PV power plant installations are increasing in many countries. These RESs can bring huge problems to the rural power system grid such as transmission lines congestion. Due to the causative factors nature, congestion can continually happen and maintain for a long commutative time. Thus, transmission efficiency is a key factor when relieving congestion. Phase-shifting transformers (PSTs) can remove these congestions. Compared to other power flow controllers, phase-shifting transformers have advantages in rural power systems such as flexibility and economic characteristic. A phase-shifting transformer controls power flow by changing the phase shift angle between the sending and receiving ends. PST increases the transmission capacity of the power system. A comprehensive study is carried out for the proper selection of the appropriate phase-shifted transformer to improve power quality and energy efficiency, and to ensure grid reliability and power flow control in smart grids emerged with the integration of renewable energy plants into electric grids. This chapter proposes a review of PSTs, consisting of classifications of PST studies and applications according to power rating, types of configurations and winding connection of PST, control and optimization techniques used for PSTs and power systems with PSTs, protection techniques and parallel operation of phase-shifting transformers in literature. A dynamic model of a solar PV power plant integrated with a 10-stage 50 MVA 380-V/154-kV phase shift transformer is presented. Also, artificial intelligence-based apparent power estimation analysis of a PST is realized using manufactured 150 MVA 330/161-kV PST for rural power systems. FANN and PSO-FANN hybrid estimation methods are used to estimate the apparent power of the PST. This study aims to contribute to researchers and application engineers with a comprehensive perspective on the status of PST studies. A list of more than 150 references on the subject will also be added for quick reference.

Stand-alone solar photovoltaic (PV) systems are a convenient way to provide electricity for people far from the electric grid or for people who want electric power with a slight dependence on the utility grid, to run their usual activities either at home or at businesses. These PV systems, combined with storage components, are considered distributed energy resources (DERs). In fact, DERs connected to distribution grids are increasing, especially PV systems, which pose several challenges to fault location, isolation, and restoration service (FLIRS) integrated into distribution automation systems (DAS). While most studies paid attention to issues focused on background knowledge or impedance-based fault location, others only adopted simplified PV models that cannot ensure accurate presentation of actual PV fault behaviors. Therefore, this chapter aims to extensively investigate the impacts of increased PV integration on the existing FLIRS performance, when PV systems become more intelligent by integrating inverters with the Internet of Things (IoT) to efficiently control the system and optimize power generation through maximum power point tracking algorithms. Since Danang Power Company put a commercial advanced FLIRS function integrated with DAS in operation along with the orientation of transforming into a smart grid, considering the extremely rapid development of PV systems in medium-voltage (MV) distribution networks, it has become a typical model for studying faults occurring in MV systems when PV penetration is high. A total of 2,700 error scenarios were carried out for comprehensive investigation purposes. All the network components relevant to the study are simulated with great detail in an environment of PowerFactory/DIgSILENT software, which can communicate with DAS through communication methods. From then, can be built IoT solutions that support modern PV system monitoring and control, which can predict and evaluate outputs from available data, possibly from Big Data.

On the worldwide renewables market, photovoltaic (PV) generation systems (PGS) are gaining in popularity. Particularly in areas where energy is difficult to utilize, such as rural villages and mountain villages, the PGS plays a significant role due to its clean, inexpensive, and robust delivery. The PGS demonstrates a high-power conversion efficiency under an ideal condition. However, it exhibits low output efficiency under various non-ideal conditions such as the mismatch among PV modules or submodules. This chapter describes a new distributed maximum power point tracking (DMPPT) system to counter the complex and variable external environment. The low-rated power and simple management of the DC-DC converter in DMPPT technology allow the hardware's small size and low complexity, which is excellent for embedding into the junction-box behind the PV panel to produce a highly integrated module.

This chapter in this book will focus on the study of a remote photovoltaic (PV) installation using a tracker system in a rural area in Morocco. We start our work by designing a general concept of a solar tracker system in an off-grid site to respond to the need for energy needs for a small farm which is taken as an example in this study. This system will be studied based on different phases of the study life: design, installation, operation, and maintenance.

Solar plants are often established in desert and arid areas characterized by harsh environmental conditions (e.g. dust scattering, rainfall scarcity). Dust soiling accumulation on photovoltaic (PV) panels adversely influences their efficiency in such a way, the PV power decreases considerably. Once dust soiling concentration exceeds a certain level, the cleaning process becomes a necessity. In this chapter, we propose a novel image processing-based system that allows achieving two-fold measurements, starting with, the quantification of dust-soiling concentration on solar panels' surface, then, estimating the corresponding produced power decrease rate of the targeted solar panels. The proposed system compares the energy production of two solar panels, the first one is kept clean, whereas the second one undergoes an under-control dust accumulation (DA) process. This system acquires two images of basic telltales placed near the panels, in such a way that they receive the same DA as the two solar panels. By observing that the contrast variation of the captured telltale images follows up the variation of energy production, we propose a process, based on image analysis, that ensures the prediction of the lost production proportion caused by DA. The proposed system turned out more beneficial compared to the existing systems, which require complex and expensive equipment. The performed experiments have been undertaken in the field under real-like DA conditions (simulated thanks to an own-made dust particles blower) that commonly affect solar plant installation.

Solar rooftop program has become very popular in the domestic, industrial, and agricultural sector. The high conversion efficiency of the solar panel is obtained if they are operated at Standard Test Condition (STC). As a result of shading due to dust particles and temperature rise above the STC of the solar panel, there is a significant reduction in power generation, conversion efficiency, and life of the cell. A controlled water spraying system using a NodeMCU board was found to be a good and economic solution to the current problem. The Suryashtmikaran system is built on the Adafruit IO cloud service, through which users may navigate real-time PV array temperature and water level of tanks. The purpose of this study is to cool and clean the PV panels with the least quantity of water and energy. The result shows the efficiency and power output reaching a maximum of 17.47% and 113.75 W, respectively, when the panel was cleaned and cooled from 9.81% and 64.60 W before cooling and cleaning. Suryashtmikaran with these user-friendly features might be a boon for investors and startups to design and develop various solar-based devices.

In the recent trend, energy management is one of the criteria in various sectors (industrial, agricultural, residential, and commercial accessibilities). The energy conservation is a key role for consuming and utilization of power in all the sectors but in the case of conserve energy, but still, it is an uncontrolled consumption process in various sectors. The existing systems of farmers are utilizing the energy in the agricultural activities, but the consumption of energy is not measured by the farmers and most of them can be an unutilized source of power or loss of energy through various electrical and thermal processes. The unutilized usage of energy will be used for other agricultural activity for pumping of water (irrigation activity). Aforementioned problems can be minimized by block chain technology (digital technology) in rural and remote areas. It is a decentralized mechanism of sharing the energy in the present situation of agriculture and it is vital role for sharing the energy in all the way by decentralized access. In this system, energy will be shared to all the farmers and consumption of energy is calculated based on their utilization in the farmland. If consumption power is more utilize by the farmers, automatically the information would be transferred to their mobile based on the consumption from the slab. This system is very helpful to the government for analyzing and tracking the consumption of power utilization not only by farmers but also control the unwanted energy level in rural area (home and other sectors). The result of the system would be shown that quality of the service will be provided to the farmers in addition to that maximize the throughput for saving and control the utilization of energy. This chapter summarizes the recent trends in solar photovoltaic system in agricultural applications and discussed the techniques and algorithm for energy conservation by implementation of block chain technology.