Photovoltaic Generation System Research Articles

A Low-Cost IoT System for Real-Time Monitoring of Climatic Variables and Photovoltaic Generation for Smart Grid Application.

Monitoring and data acquisition are essential to recognize the renewable resources available on-site, evaluate electrical conversion efficiency, detect failures, and optimize electrical production. Commercial monitoring systems for the photovoltaic system are generally expensive and closed for modifications. This work proposes a low-cost real-time internet of things system for micro and mini photovoltaic generation systems that can monitor continuous voltage, continuous current, alternating power, and seven meteorological variables. The proposed system measures all relevant meteorological variables and directly acquires photovoltaic generation data from the plant (not from the inverter). The system is implemented using open software, connects to the internet without cables, stores data locally and in the cloud, and uses the network time protocol to synchronize the devices’ clocks. To the best of our knowledge, no work reported in the literature presents these features altogether. Furthermore, experiments carried out with the proposed system showed good effectiveness and reliability. This system enables fog and cloud computing in a photovoltaic system, creating a time series measurements data set, enabling the future use of machine learning to create smart photovoltaic systems.

Service Restoring Reconfiguration for Distribution Networks Considering Uncertainty in Available Information

The recent growth in the penetration of photovoltaic generation systems (PVs) has brought new difficulties in the operating and planning of electric power distribution networks. This is because operators of the distribution networks normally cannot monitor or control the output of the PVs, which introduces additional uncertainty into the available information that operations must rely on. This paper focuses on the service restoration of the distribution networks, and the authors propose a problem framework and its solution method that finds the optimal restoration configuration under extensive PV installation. The service restoration problems have been formulated as combinatorial optimization problems. They do, however, require accurate information on load sections, which is impractical in distribution networks with extensively installed PVs. A combined framework of robust optimization and two-stage stochastic programming adopted in the proposed problem formulation enables us to deal with the PV-originated uncertainty using readily available information only. In addition, this problem framework can be treated by a traditional solution method with slight extensions. The validity of the authors’ proposal is verified through numerical simulations on a real-scale distribution network model and a discussion of their results.

Integration of distributed energy resource models in the VSC control for microgrid applications

Studies related to the integration of distributed energy resources (DERs) face challenges in considering models for the primary energy source, the conversion equipment, the inverters, and the microgrid. Most of the current approaches only consider some of these models, then the complete modelling is uncommon, leading to simplified system representations. As a solution, this paper presents a three-stage approach to easily integrate the generation and storage system models into the dq0 control algorithm of a voltage source converter (VSC), useful in microgrid studies. The considered DERs, correspond to battery energy storage system (BESS), wind generation and photovoltaic (PV) generation systems; then, the model influence and the variation of the primary energy source modify the control references. This approach allows an appropriate balance between model accuracy and simplicity of steady-state and dynamic equivalent models for converter integrated DER (CIDER). The results show how this modelling facilitates the steady and dynamic state studies, as is evidenced in the tests performed in a CIGRE based microgrid.

Adaptive single carrier multilevel modulation for grid connected single phase modular multilevel inverter

In this paper, an adaptive single carrier multilevel (ASCM) Modulation technique is proposed to simplify the implementation of the single phase modular multilevel converter based on the grid connected to string inverter (MMSI) for the photovoltaic generation system applications. The main characteristics of adaptive single carrier multilevel modulation are reduction in switching losses and the harmonics performance improvement. The control configuration of MMSI, includes the proposed ASCM modulation scheme is designed. In order to investigate the performance of the proposed methods, the simulation model of the MMSI is developed in the MATLAB/SIMULINK environmental to verify the performance of the ASCM technique. The laboratory prototype for MMSI is developed using the DSP TMS32F2407. The experimental results are included to support the simulation result.

Hybrid and Adaptive P&O Maximum Power Point Tracking Techniques for PV Generation Systems

Maximum power point tracking (MPPT) techniques work to track the maximum power from the PV cell. A lot of conventional MPPT techniques, such as the perturb and observe (P&O), succeed in catch the maximum power point (MPP) with a good performance. However, they suffer many problems during fast varying weather conditions, where slow time response and high oscillations are dominant. Also, it is difficult to select the right direction for new steps. This article illustrates two new P&O MPPT techniques for PV generation systems. They operate on the power-voltage (P-V) curve under different weather conditions. The first is an adaptive perturb and observe (A-PO) technique, which changes the perturbation step-size adeptly to deal with the rapidly varying weather conditions. The second is a hybrid perturb and observe technique (H-PO), which uses a variable step-size according to the location of the operating point relative to the MPP. The MATLAB/SIMULINK software is used to study the truth of the proposed techniques. The results demonstrate that both techniques attain the MPP faster than the conventional techniques and at a reduced oscillation rate.

Most Valuable Player Algorithm based Maximum Power Point Tracking for a Partially Shaded PV Generation System

Inclusion of bypass diodes at the output terminal of the PV array mitigates the effect of partial shading (PS) but causes multiple peaks of power at the output. The conventional hill climbing and perturb and observe algorithms cannot track the optimal point during partial shading phenomena for multiple peaks corresponding to the different shading pattern on the Power-Voltage (P-V) curve. Fuzzy logic controller and artificial neural network-based methods for Maximum Power Point Tracking (MPPT) provide satisfactory results but at the cost of increased memory and computational burden. Recent work to incorporate exploration and exploitation phenomena of nature-inspired algorithms to track optimal power point have shown encouraging results by preventing convergence to local maxima and posing less burden on the processor. However, due to performance variation between different algorithms of this category newer algorithms with improved performances are still a requirement. In this paper, a novel most valuable player algorithm (MVPA) has been used to track the optimal operation point for extracting maximum power from a solar PV system. The algorithm's performance is compared with the commonly employed particle swarm optimization (PSO) and the recently proposed Jaya algorithm's modified form. It is observed that the proposed algorithm outperformed both the algorithms with a considerable improvement in terms of tracking speed, power tracking efficiency, robustness, faster decision for convergence after tracking the maximum power and lesser number of power fluctuations for different shading patterns.

Proposal of New PCCS Method for PCS in a PV Generation System

Proposal of New PCCS Method for PCS in a PV Generation System

Performance Analysis of Maximum Power Point Tracking for Two Techniques with Direct Control of Photovoltaic Grid -Connected Systems

ABSTRACT The present study presents two techniques of Maximum Power Point Tracking (MPPT) via DC/DC converter to enhance the performance of the grid-connected Photovoltaic (PV) generation system to participate effectively within microgrids. The two techniques of MPPT are Perturb-Observe (P&O) and Incremental Conductance (IC). The variation of the solar radiation and temperature is considered during employing the two MPPT techniques. Besides, the performance of the system under the random variation of solar radiation was investigated. The authors used two types of controllers at the three-phase inverter, Proportional Integral (PI) and H-infinity Control (H∞C). The output voltage, current, and power at each type of inverter controller are compared along with the two techniques of MPPT. The effectiveness of the developed controllers together with MPPT techniques is demonstrated by comparing the obtained results with some previously reported research in the literature. In the case of MPPT via P&O and IC techniques along with the H∞C controller, the results show that the technique of IC is more robust, and the obtained output power is well matched with the references one as compared with the P&O technique which records a 7% error from MPP. Besides, the P&O technique has a high voltage and current ripple with a percentage of 20% at the starting time of the simulation.

Buildings-to-distribution-network integration for coordinated voltage regulation and building energy management via distributed resource flexibility

Electricity demand for building-related activities is steadily increasing due to urbanization. Combined with the increasing penetration of renewable energy, this trend brings new challenges to distribution network operators in maintaining nodal voltage and minimizing active power losses. At the same time, building operators require more effective methods of reducing building operational costs. Therefore, as a critical step towards smart cities, it is imperative to optimally manage and coordinate the resources across building and power distribution networks to improve the overall system's efficiency and reliability. To this end, this paper develops a novel framework for Buildings-to-Distribution-Network (B2DN) integration. The framework couples commercial, residential buildings, and DERs, including photovoltaic (PV) generation and battery energy storage systems (BESS), with the power distribution network, enabling buildings and the distribution networks to be optimized simultaneously while respecting both building and distribution network constraints. The proposed B2DN framework is implemented in a receding horizon manner by solving a quadratically constrained quadratic programming (QCQP) problem. The framework’s capabilities are demonstrated on the IEEE 13-, 33-, and SB 129-node distribution networks integrated with 90, 192, and 481 buildings and DERs. The simulation results reveal that the B2DN controller successfully minimizes distribution network active power losses and enhances voltage regulation while at the same time minimizing building energy costs and maintaining occupant's comfort in comparison with decoupled designs, where buildings and distribution networks are independently managed. Finally, uncertainty analysis shows a minimal decrease in the B2DN controller's performance in the presence of randomness in weather variables, building internal heat gains, and distribution network nodal base demands.

Active–passive combined energy-efficient retrofit of rural residence with non-benchmarked construction: A case study in Shandong province, China

Unlike standard-restricted and well-equipped urban residential buildings, a large portion of rural buildings sacrifice indoor comfort and energy efficiency to reduce the initial investment. Therefore, cost-effective retrofit strategies for rural buildings are urgently needed to better living conditions and create higher energy efficiency. This study developed a framework to choose the optimal economical retrofitting strategies for existing rural buildings by taking both active and passive approaches into consideration. The building retrofitting measurements were a combination of thermal performance improvement for external walls and a solar photovoltaic generation system for the rooftop. With the case of a rural dwelling in Shandong province, this study first assessed the thermal transmittance of the external walls and collected geometry and operational schedules to create a building model for the later energy simulation. Environmental monitoring was also conducted for two months – in February for winter and August for summer – to obtain actual indoor temperatures, which were used to calibrate the energy model within a 10% error rate. In total, 17 retrofitting plans were then set up and analyzed in this study. The results showed that when applying the cost-optimal retrofit plan, there is the great potential to reduce energy use by 20.5% and to balance the annual building energy consumption with a payback period of 10.7 years. Finally, the proposed framework was proven to be accurate and feasible and was expected to be widely used in the improvement of living conditions in Chinese rural areas.

Integrated technical paradigm based novel approach towards photovoltaic power generation technology

Photovoltaic (PV) has been regarded as the most promising, technically viable large-scale renewable energy source for a sustainable society. However, as the demand for solar energy is generally rising, the world needs to fundamentally reconsider the development of PV generation technology. The objective of this study is to propose a comprehensive method to study the role of technological paradigms in the development of PV generation, and to contribute to PV generation policy recommendations and system management. A novel document data mining analysis system and the technological paradigm theory are used to conduct the study. PV generation technology paradigm composed of paradigm competition, diffusion and shift is established to explain the technological changes in the use of PV energy. In this paper, the autoregressive moving average model is used to make short-term forecasts of the PV generation installed capacity, and to compare with the data predicted by Prospective Industry Research Institute. The results show that the forecasting method herein is effective and reliable. Also, this paper discusses the benefits and barriers of PV generation technology. However, to achieve higher market share in electricity generation, more support policies, multi-level cooperation, technical support and capital investment are needed. Moreover, this study provides an analysis framework for the soft path analysis of PV generation technology to achieve sustainable PV technological development.

A bilevel programming approach for real‐time pricing strategy of smart grid considering multi‐microgrids connection

As an important method for demand-side management, the real-time pricing can not only adjust the power balance between the supply and demand-sides, but also effectively promote the internal energy dispatching behavior of the microgrid. In this article, a bilevel programming model is proposed based on the demand response to coordinate the master-slave hierarchical relationship in the electricity market. At the upper level, the main grid determines the prices and generation for the supplier's maximum profit. At the lower level, we consider multiple microgrids, which operate in isolated-island or grid-connected mode, with photovoltaic generation system, energy storage system, and loads. Then, the optimal energy strategy is emerged for the user's maximum welfare according to the dynamic prices. Furthermore, we solve the upper and lower models separately to avoid user privacy being violated. The upper problem uses the genetic algorithm (GA), while the lower problem is handled by the branch and bound algorithm (BBA). A novel distributed algorithm named GA-BBA is developed accordingly. Finally, taking an example of a smart grid system with three microgrids, the model and algorithm are simulated and compared. The results show that the peak-to-average ratio under the real-time pricing is reduced from 1.6547 (fixed electricity price) and 1.4513 (time-of-use) to 1.2545. The peak-to-valley difference is also decreased by approximately 14.33%. In addition, the total social welfare of the system is increased by 145.53 kCNY (Chinese Yuan) through comparison with the existing model. The conclusions verify that the proposed bilevel programming model not only effectively reduces peak load but also increases the social welfare, which is more reasonable and realistic. Novelty Statement A novel bilevel optimization energy management system is proposed to optimize the hierarchical market structure between the main grid and multi-microgrids (MMGs). A RTP mechanism based on demand response is formulated to balance the benefits between the main grid and MMGs. Moreover, the optimal energy strategy is obtained along with the dynamic price. Besides the operating cost, users' utility in microgrids are taken to our model. A hybrid distributed GA-BBA is developed to protect the user's utility privacy.

Modelling and Performance Analysis of Synchronous Reference Frame Phase-Locked Loop for Three-phase Grid-connected PV Generation System

Due to the introduction of the feed-in tariff policy mechanism in many countries, the grid-connected Photovoltaic (PV) generation system becomes new attractions as it encourages the energy producers to generate and supplies electricity to the grid. The characteristic of the inverter’s voltage waveform, its amplitude, phase-angle and phase sequence are vital parameters for effective PV-grid synchronization. This paper presents a double stage converter, DC-DC boost conversion included to maximum power point tracking (MPPT) is achieved. Second stage DC-AC conversion is achieved using voltage source inverter (VSI). Grid connected synchronization is achieved by using synchronous reference (SRF) base phase locked loop (PLL). A details design and model for each section of the proposed system are also presented. The result shows that the implementation of synchronous reference frame (SRF) with PLL able to good achieved.

Current control of grid connected three phase current source inverter based on medium power renewable energy system

Current source inverter (CSI) features simple converter structure and inherent voltage boost capability. In addition, it provides low instantaneous rate of voltage change with respect to time in comparison to voltage source inverter (VSI) and multilevel inverter (MLI). Nonetheless, CSI does not outshine as grid interfacing unit in photovoltaic (PV) generation system. This is because of requirement of large sizing of dc-link inductor and sluggish performance during light load condition. Contemplating both advantages and disadvantages of CSI, this work is aimed to investigate and analyze the superiority of CSI in PV system. The proposed system employs direct regular-sampled pulse width modulation (DRSPWM) as modulator and multi-loop proportional-integral (PI) in synchronous frame as the controller. The grid-connected CSI system is further evaluated along with photovoltaic maximum power point tracking (PV-MPPT) control. Simulation verification highlighted that the option of using CSI as medium power PV grid integration unit in exchanging active-reactive power with grid network is very satisfactory. In addition, balanced sinusoidal output currents with acceptable harmonic limit are successfully achieved; like other topologies in PV grid integration. The proposed CSI system is proved to be able to track the references in event of varying input condition from PV array. The theoretical equations and modeling are described, and the simulation are conducted in MATLAB / Simulink platform.

Smart Home Automation System

This paper presents a low cost, flexible and scalable Smart Home Automation System based on Arduino Technology and Wi-Fi connection, in addition to apply specific techniques for reduction of power consumption and load management. The system will be accessible anywhere, anytime for controlling and monitoring. This study relies on Arduino Technology and Node-MCU boards, the electrical appliances are connected to a cloud database that communicates with the user by an android application connected to the internet. A prototype for a specific house has been built, the proposed system is able to control all home electrical units and appliances like: lighting, sockets, HVAC units, fire, gas and intruder siren systems, in addition to monitor the real time power consumption, the house PV system generation and the current room's temperature and humidity. Furthermore, the system is able to reduce power consumption using predefined algorithms.

Flexible Control Strategy for Enhancing Power Injection Capability of Three-Phase Four-Wire Inverter During Asymmetrical Grid Faults

A three-phase four-wire inverter is highly suitable for low-voltage distributed grids owing to its zero sequence control; however, essential aspects of grid-following inverters during faults, such as the power oscillation control flexibility and power injection capability, are rarely discussed in detail. Thus, by introducing zero sequence instantaneous power into a four-wire system, this article proposes a flexible control strategy that enhances the power injection capability of the inverter in the photovoltaic generation system during asymmetrical grid faults. First, a generalized reference current generation with flexible control of positive, negative, zero sequence current (FPNZSC), and power oscillations is presented. Second, a maximum allowable power injection (MAPI) algorithm based on the actual value constraints of power oscillations and peak current is presented according to the requirement. The proposed MAPI-FPNZSC strategy further extends the existing fault ride through methods in three-wire inverter systems, which is also suitable for single line-to-ground and double line-to-ground faults and can be easily realized in the natural or stationary frame. The effectiveness of the proposed strategy is verified by comparing the provided three typical objectives with the traditional method, and tested in a real-time hardware-in-the loop experimental platform.

A state-of-the-art differential evolution algorithm for parameter estimation of solar photovoltaic models

Photovoltaic (PV) generation systems are vital to the utilization of the sustainable and pollution-free solar energy. However, the parameter estimation of PV systems remains very challenging due to its inherent nonlinear, multi-variable, and multi-modal characteristics. In this paper, we propose a state-of-the-art optimization method, namely, directional permutation differential evolution algorithm (DPDE), to tackle the parameter estimation of several kinds of solar PV models. By fully utilizing the information arisen from the search population and the direction of differential vectors, DPDE can possess a strong global exploration ability of jumping out of the local optima. To verify the performance of DPDE, six groups of experiments based on single, double, triple diode models and PV module models are conducted. Extensive comparative results between DPDE and other fifteen representative algorithms show that DPDE outperforms its peers in terms of the solution accuracy. Additionally, statistical results based on Wilcoxon rank-sum and Friedman tests indicate that DPDE is the most robust and best-performing algorithm for the parameter estimation of PV systems.

The Survey of MPPT under non-uniform atmospheric conditions for the Photovoltaic Generation Systems

Among the undeletable sources, the PV Generation System is the most suitable resource. The main challenge for the PV generation system is changing climatic conditions and grid integration. The ongoing research is focusing on the tracking point of peak power, increasing the efficiency with reduced operating costs, and explores the challenges associated with the solar PV array under non-uniform atmospheric conditions. The weather conditions and intensity of the sunlight vary all over the day. One critical aspect of the PV cells is its non-linear P–V characteristic and possess multiple peaks under non- uniform irradiances. There is a requisite to figure out the point of maximum power, which governs the converter to extort the maximal power from the PV system. The work in this ground reiterated that the fluctuating weather situations such as temperature variation, sectional shading, etc. and grid integration demands an undisputable need of MPPT. To lessen such difficulty the paper suggests a comprehensive and relative analysis of different MPPT. The evaluation will help in selecting the PV generation system for a particular location. The review of MPPT techniques has been grouped into two groups. The first group includes all the benchmark facilities. The second group includes the intelligent techniques that explain the fuzzy-based MPPT, ANN-based MPPT evolutionary techniques, hybrid method, and MPPT techniques used in energy harvesting”.

Economic viability and optimization of solar microgrids with hybrid storage in a non-interconnected zone in Colombia

A developing country that does not have adequate energy solutions in non-interconnected zones (ZNIs) undoubtedly experiences adverse effects in terms of its competitiveness, as well as economic and social development. The primary sources of electrical energy in these communities are diesel generators, which are expensive and not environment-friendly. This paper seeks to describe how to reduce the consumption of this fossil fuel in ZNIs. The technical and economical implementation of a small-scale photovoltaic system with and without a hybrid energy storage system connected to the grid is studied, based on the incentive policy of the Colombian regulation. A mixed-integer nonlinear programming optimization model was developed, which includes the storage costs of a lead-acid battery and supercapacitor, to analyze the benefits of the electricity tariff and to maximize the revenues of the photovoltaic generation system. The conclusions of this study offer policy suggestions and economic incentives to enhance the use of renewable energy sources in the ZNIs of Colombia.

Evaluation of Fuzzy Membership Function Effects for Maximum Power Point Tracking Technique of Photovoltaic System

The photovoltaic generation system (PGS) is considered a potential renewable energy harvesting system. However, the low conversion efficiency of PGS and maximum power point tracking (MPPT) technique are the main challenges that must be solved. In addition, the switching frequency of the converters employed also affects the MPPT system performance. A high gain voltage DC-DC converter is proposed to replace conventional power converter and fuzzy logic controller (FLC) is applied in the MPPT for optimizing solar energy harvesting system. Nevertheless, evaluation of suitable fuzzy membership function is needed for optimal MPPT technique of photovoltaic system. In this paper, FLC of MPPT for photovoltaic application system was built using various membership functions in MATLAB/Simulink environment. The switching frequency of the high gain voltage DC-DC converter is varied to test the robustness of the performance of each FLC membership function. The results showed that the FLC-based MPPT technique for high gain voltage DC-DC converter with GBell membership function type has the capability to track the maximum power point (MPP) accurately and to achieve optimum power conversion. Furthermore, GBell membership showed having stable and consistent performance at various switching frequencies.