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Energy is very important in daily life. The smart power system provides an energy management system using various techniques. Among other load types, campus microgrids are very important, and they consume large amounts of energy. Energy management systems in campus prosumer microgrids have been addressed in different works. A comprehensive study of previous works has not reviewed the architecture, tools, and energy storage systems of campus microgrids. In this paper, a survey of campus prosumer microgrids is presented considering their energy management schemes, optimization techniques, architectures, storage types, and design tools. The survey is comprised of one decade of past works for a true analysis. In the optimization techniques, deterministic and metaheuristic methods are reviewed considering their pros and cons. Smart grids are being installed in different campuses all over the world, and these are considered the best alternatives to conventional power systems. However, efficient energy management techniques and tools are required to make these grids more economical and stable. [ABSTRACT FROM AUTHOR]

Solar photovoltaics (PV) are susceptible to environmental and operational stresses due to their operation in an open atmosphere. Early detection and treatment of stress prevents hotspots and the total failure of solar panels. In response, the literature has proposed several approaches, each with its own limitations, such as high processing system requirements, large amounts of memory, long execution times, fewer types of faults diagnosed, failure to extract relevant features, and so on. Therefore, this research proposes a fast framework with the least memory and computing system requirements for the six different faults of a solar panel. Infrared thermographs from solar panels are fed into intense and architecturally complex deep convolutional networks capable of differentiating one million images into 1000 classes. Features without backpropagation are calculated to reduce execution time. Afterward, deep features are fed to shallow classifiers due to their fast training time. The proposed approach trains the shallow classifier in approximately 13 s with 95.5% testing accuracy. The approach is validated by manually extracting thermograph features and through the transfer of learned deep neural network approaches in terms of accuracy and speed. The proposed method is also compared with other existing methods. [ABSTRACT FROM AUTHOR]

This research presents an optimal scheme for the integration of renewable resources with the utility grid to minimize the operational cost of the residential and industrial microgrids. With the changing paradigm of solar photovoltaic in low-voltage distribution networks, utilities have allowed net metering and feed-in tariff (FiT). These incentives encourage residential and industrial consumers to contribute toward energy generation. However, in conventional mode, the system may underperform if resources are not scheduled optimally. To compensate for the price difference during off-peak and on-peak hours, the energy should be taken from the grid when electricity prices are lower and supplied to the grid when the electricity price is higher. The proposed models will therefore allow optimal resource utilization considering intermittent renewable generation as well as a time-varying utility tariff. A complete comparative analysis of on-grid and off-grid models was carried out. The results indicate that the daily average saving is about 32.0% by using the proposed on-grid scheme, where a feed-in tariff is available. [ABSTRACT FROM AUTHOR]

Partial shading and other non-ideal conditions cause electrical mismatches that reduce the output power generated by a photovoltaic (PV) system. It affects the overall performance and efficiency of PV systems. Therefore, a model is developed in MATLAB, which analyses the performance of the PV systems under real irradiance profiles and temperatures for various available mismatch mitigation methodologies, i.e., bypass diode, DC power optimizer, and differential power processing (DPP). More specifically, this study will help to understand the best mismatch reduction methodologies for a solar PV system under different scenarios. The results also are validated by comparing them with a similar PV system installed in SolarTechLAB, which also operates under the same irradiance and temperature conditions under which these models are tested. This study also presents novel results, covering discussions on the reverse voltage distribution under mismatch scenarios among bypass diode, DC power optimizer, and DPP techniques. [ABSTRACT FROM AUTHOR]

The paper investigates the system efficiency for power distribution in residential localities considering daily load variations. Relevant system modeling is presented. A mathematical model is devised, which is based on the data from the Energy Information Administration (EIA), USA, for analysis. The results reveal that the DC distribution system can present an equivalent or even better efficiency compared to the AC distribution network with an efficiency advantage of 2.3%, averaged over a day. Furthermore, the distribution systems are compared under various capacities of solar PV accounting for the effect of variation in solar irradiation over time. [ABSTRACT FROM AUTHOR]

A reconfiguration technique using a switched-capacitor (SC)-based voltage equalizer differential power processing (DPP) concept is proposed in this paper for photovoltaic (PV) systems at a cell/subpanel/panel-level. The proposed active diffusion charge redistribution (ADCR) architecture increases the energy yield during mismatch and adds a voltage boosting capability to the PV system under no mismatch by connected the available PV cells/panels in series. The technique performs a reconfiguration by measuring the PV cell/panel voltages and their irradiances. The power balancing is achieved by charge redistribution through SC under mismatch conditions, e.g., partial shading. Moreover, PV cells/panels remain in series under no mismatch. Overall, this paper analyzes, simulates, and evaluates the effectiveness of the proposed DPP architecture through a simulation-based model prepared in PSIM. Additionally, the effectiveness is also demonstrated by comparing it with existing conventional DPP and traditional bypass diode architecture. [ABSTRACT FROM AUTHOR]

Partial shading affects the energy harvested from photovoltaic (PV) modules, leading to a mismatch in PV systems and causing energy losses. For this purpose, differential power processing (DPP) converters are the emerging power electronic-based topologies used to address the mismatch issues. Normally, PV modules are connected in series and DPP converters are used to extract the power from these PV modules by only processing the fraction of power called mismatched power. In this work, a switched-capacitor-inductor (SCL)-based DPP converter is presented, which mitigates the non-ideal conditions in solar PV systems. A proposed SCL-based DPP technique utilizes a simple control strategy to extract the maximum power from the partially shaded PV modules by only processing a fraction of the power. Furthermore, an operational principle and loss analysis for the proposed converter is presented. The proposed topology is examined and compared with the traditional bypass diode technique through simulations and experimental tests. The efficiency of the proposed DPP is validated by the experiment and simulation. The results demonstrate the performance in terms of higher energy yield without bypassing the low-producing PV module by using a simple control. The results indicate that achieved efficiency is higher than 98% under severe mismatch (higher than 50%). [ABSTRACT FROM AUTHOR]

Photovoltaic (PV) energy has been competitive in power generation as an alternative to fossil energy resources over the past decades. The installation of grid-connected solar energy systems is expected to increase rapidly with the fast development of the power electronics technology. As the key to the interface of the PV energy and the grid, power converters should be reliable, efficient and comply with the grid requirements. Considering the nature of PV energy, the power conversion should be flexible (e.g., high step-up DC-DC conversion and harmonic-free DC-AC conversion). Accordingly, many power electronic converters have been reported in literature. Compared with isolated inverters, transformerless inverters show great advantages. This paper thus presents an overview of the transformerless step-up single-phase inverters for PV applications based on the dc-link configurations. Grid-connected PV inverters are classified as constant dc-link voltage structures, pseudo-dc-link voltage structures, pulsating dc-link voltage structures and integrated dc-link voltage structures. The discussion on the composition of different dc-link structures is presented, which provides guidance to select appropriate transformerless inverter topologies for PV applications. [ABSTRACT FROM AUTHOR]

In recent times, concerns over fossil fuel consumption and severe environmental pollution have grabbed attention in marine vessels. The fast development in solar technology and the significant reduction in cost over the past decade have allowed the integration of solar technology in marine vessels. However, the highly intermittent nature of photovoltaic (PV) modules might cause instability in shipboard microgrids. Moreover, the penetration is much more in the case of utilizing PV panels on ships due to the continuous movement. This paper, therefore, presents a frequency sharing approach to smooth the effect of the highly intermittent nature of PV panels integrated with the shipboard microgrids. A hybrid system based on an ultra-capacitor and a lithium-ion battery is developed such that high power and short term fluctuations are catered by an ultra-capacitor, whereas long duration and high energy density fluctuations are catered by the lithium-ion battery. Further, in order to cater for the fluctuations caused by weather or variation in sea states, a battery energy storage system (BESS) is utilized in parallel to the dc-link capacitor using a buck-boost converter. Hence, to verify the dynamic behavior of the proposed approach, the model is designed in MATLAB/SIMULINK. The simulation results illustrate that the proposed model helps to smooth the fluctuations and to stabilize the DC bus voltage. [ABSTRACT FROM AUTHOR]

Partial shading on photovoltaic (PV) arrays reduces the overall output power and causes multiple maximas on the output power characteristics. Due to the introduction of multiple maximas, mismatch power losses become apparent among multiple PV modules. These mismatch power losses are not only a function of shading characteristics, but also depend on the placement and interconnection patterns of the shaded modules within the array. This research work is aimed to assess the performance of 4 × 4 PV array under different shading conditions. The desired objective is to attain the maximum output power from PV modules at different possible shading patterns by using power electronic-based differential power processing (DPP) techniques. Various PV array interconnection configurations, including the series-parallel (SP), total-cross-tied (TCT), bridge-linked (BL), and center-cross-tied (CCT) are considered under the designed shading patterns. A comparative performance analysis is carried out by analyzing the output power from the DPP-based architecture and the traditional Schottky diode-based architecture. Simulation results show the gain in the output power by using the DPP-based architecture in comparison to the traditional bypassing diode method. [ABSTRACT FROM AUTHOR]

In recent years, concerns about severe environmental pollution and fossil fuel consumption has grabbed attention in the transportation industry, particularly in marine vessels. Another key challenge in ships is the fluctuations caused by high dynamic loads. In order to have a higher reliability in shipboard power systems, presently more generators are kept online operating much below their efficient point. Hence, to improve the fuel efficiency of shipboard power systems, the minimum generator operation with N-1 safety can be considered as a simple solution, a tradeoff between fuel economy and reliability. It is based on the fact that the fewer the number of generators that are brought online, the more load is on each generator such that allowing the generators to run on better fuel efficiency region. In all-electric ships, the propulsion and service loads are integrated to a common network in order to attain improved fuel consumption with lesser emissions in contrast to traditional approaches where propulsion and service loads are fed by separate generators. In order to make the shipboard power system more reliable, integration of energy storage system (ESS) is found out to be an effective solution. Energy storage devices, which are currently being used in several applications consist of batteries, ultra-capacitor, flywheel, and fuel cell. Among the batteries, lithium-ion is one of the most used type battery in fully electric zero-emission ferries with the shorter route (around 5 to 10 km). Hybrid energy storage systems (HESSs) are one of the solutions, which can be implemented in high power/energy density applications. In this case, two or more energy storage devices can be hybridized to achieve the benefits from both of them, although it is still a challenge to apply presently such application by a single energy storage device. The aim of this paper is to review several types of energy storage devices that have been extensively used to improve the reliability, fuel consumption, dynamic behavior, and other shortcomings for shipboard power systems. Besides, a summary is conducted to address most of the applied technologies mentioned in the literature with the aim of highlighting the challenges of integrating the ESS in the shipboard microgrids. [ABSTRACT FROM AUTHOR]