Hybrid Wind-photovoltaic System Research Articles

Capacity Optimization of Pumped–Hydro–Wind–Photovoltaic Hybrid System Based on Normal Boundary Intersection Method

Introducing pumped storage to retrofit existing cascade hydropower plants into hybrid pumped storage hydropower plants (HPSPs) could increase the regulating capacity of hydropower. From this perspective, a capacity configuration optimization method for a multi-energy complementary power generation system comprising hydro, wind, and photovoltaic power is developed. Firstly, to address the uncertainty of wind and photovoltaic power outputs, the K-means clustering algorithm is applied to deal with historical data on load and photovoltaic, wind, and water inflow within a specific region over the past year. This process helps reduce the number of scenarios, resulting in 12 representative scenarios and their corresponding probabilities. Secondly, with the aim of enhancing outbound transmission channel utilization and decreasing the peak–valley difference for the receiving-end power grid’s load curve, a multi-objective optimization model based on the normal boundary intersection (NBI) algorithm is developed for the capacity optimization of the multi-energy complementary power generation system. The result shows that retrofitting cascade hydropower plants with pumped storage units to construct HPSPs enhances their ability to accommodate wind and photovoltaic power. The optimal capacity of wind and photovoltaic power is increased, the utilization rate of the system’s transmission channel is improved, and the peak-to-valley difference for the residual load of the receiving-end power grid is reduced.

An optimal sizing framework of a microgrid system with hydrogen storage considering component availability and system scalability by a novel approach based on quantum theory

This paper introduces an innovative framework for optimizing a hybrid photovoltaic-wind system with integrated hydrogen storage, taking into account component availability and system scalability. The primary objective is to minimize the total net present cost (TNPC) while enhancing system reliability based on the Loss of Power Supply probability (LPSP). The decision variables include the determination of the number of photovoltaic (PV) panels, wind turbines (WTs), hydrogen storage mass, fuel cell capacity, electrolyzer capacity, and inverter capacity. To achieve this optimization, the Quantum Beluga Whale Optimization (QBWO) algorithm is employed, which is an improved version of the Beluga Whale Optimization (BWO) algorithm. QBWO overcomes some limitations of BWO by incorporating principles from quantum theory and addressing challenges related to the scarcity of population diversity and stagnation in local optima. Simulations were conducted for scenarios involving WT/FC, PV/FC, and PV/WT/FC systems. The results indicate that within a microgrid context, the PV/WT/FC configuration proves to be the most cost-effective approach for supplying local loads. Under certain conditions, it achieved the best TNPC with 0.8176 M$, Levelized Cost of Energy (LCOE) with 0.264 $/kWh, and LPSP with 0.04687. However, considering components availability and system scalability changes indicate a significant effect on the system cost and reliability. Overall, this framework provides a precise method for designing energy systems, considering factors such as electricity generation costs and reliability enhancements in the face of uncertainties. QBWO outperforms original BWO, Particle Swarm Optimization (PSO), and Crow Search Algorithm (CSA) by achieving lower design costs and improved reliability. This study contributes to developing environmentally friendly electrification plans and provides valuable insights for power investments in energy-deprived Southwest Morocco.

REVIEW OF MONITORING TECHNOLOGIES USED IN HYBRID PHOTOVOLTAIC SYSTEMS

In the present context, due to the increase in global energy demand and the need to reduce greenhouse gases, hybrid systems that produce electricity and heat from renewable sources have been proposed, designed and implemented. Most of the available solar energy is captured using photovoltaic systems and converted into electricity. Today's modern systems refer to combinations of photovoltaic and thermal panels (PV/T) to obtain electricity and domestic hot water, and systems consisting of photovoltaic panels with wind turbines which provides only electricity. With an optimal design, PV/T systems can provide buildings with 100% renewable electricity and heat. This is done in a more cost-effective and efficient way compared to using photovoltaic and solar thermal systems separately. The areas required to install photovoltaic systems can be reduced by using hybrid energy production systems. The introduction of a hybrid photovoltaic-wind system reduces the land area from 1.5 ha/MW to 0.4 ha/MW. Due to the influence of environmental factors affecting the functionality of hybrid systems and the need to achieve optimal performance, the development and implementation of advanced monitoring methods has become a mandatory requirement. The paper presents different methods of monitoring hybrid systems, their progress and performance.

Long-term operation rules of a hydro–wind–photovoltaic hybrid system considering forecast information

The large-scale integration of wind and solar energy into cascade hydropower stations increases the complexity of hydraulic/electrical relationships and requires a modification of conventional scheduling mode for better energy system performance. This study focuses on the long-term operation rules for hydro–wind–photovoltaics (PV) hybrid energy systems (HESs). Based on the conventional operation chart, a cascade energy operation chart that couples wind, PV output, and runoff forecasts is proposed to obtain the total output of HES, which can promote the utilization of the joint regulation of cascade hydropower stations. A total output allocation method based on the cascade energy operation chart is established to coordinate the operation of each power station. Then an operation chart optimization model with objectives of maximizing power generation and output reliability is proposed to improve HES performance. The case study reveals that compared with the conventional reservoir operation chart, 1) the optimized cascade energy operation chart increased power generation of HES by 9.2 %; 2) the reservoir impounding timing was delayed, the drawdown timing was brought forward, and the drawdown depth was increased; 3) the reliability of HES power output was improved, and the output corresponding to the 95 % guaranteed rate requirement was increased by 18 %.

Energy management in hybrid photovoltaic–wind system using optimized neural network

Energy management in hybrid photovoltaic–wind system using optimized neural network

Power management of grid-connected PV wind hybrid system incorporated with energy storage system

Renewable Energy Sources (RES) such as solar photovoltaic (PV) and wind-based generation cannot meet dynamic load demand all the time because of their intermittent nature. Battery Energy Storage System (BESS) is integrated with RES to meet dynamic load demands. Proper power management is needed for the efficient and reliable performance of the system. This paper presents power management of PV-Wind- Battery hybrid system for both grid-connected and islanded modes of operation as well. The power balance is maintained by a power management system (PMS) under different environmental conditions and load conditions, and modes of operation. The control method for state-of-charge (SOC) and battery charge/discharge is applied to ensure efficient performance and safe operation of BESS. Different cases, such as surplus/deficit power available from RES with respect to load demand and battery capacity, have been considered and carried out to verify the performance of PMS using the MATLAB/Simulink platform.

Ecological impact due to the implementation of a modeled and optimized hybrid system

<span lang="EN-US">This paper presents a very alarming forecasts about our future and particularly for a medium and long-term future. That is to say, several actions are being carried out by different civil and state parties to deal with these very concrete threats. And it is within this framework that this paper fits, and its objective is to highlight the hybrid systems and more precisely the photovoltaic-wind hybrid systems coupled with storage batteries, as an efficient alternative to the classical means of electricity production. This work will adopt a method of obtaining results called performance evaluation, so this manuscript will present firstly the mathematical model of this hybrid system to best conceive what it is about, then as second part will determine the exact figures of the largest amount of carbon dioxide (CO<sub>2</sub>) that can be avoided using this technology and following a precise methodology, this can be applied to our situation, i.e., a simple house or to any other type of installation.</span>

Mitigation of Lightning-Induced Transient Effects on a Hybrid Photovoltaic–Wind System Based on Lightning Protection Standards

Installing surge protection devices in a hybrid photovoltaic (PV)–wind system is essential to guarantee the survival of the system’s components. If the surge arresters are connected without taking into account the recommendations given by standards, the equipment to be protected might be damaged despite the energy coordination of the arresters. In this study, nonlinear surge protective devices (SPDs) are designed for a multi-MW hybrid system based on lightning protection standards with optimised threat level ratings to investigate the mitigation of lightning transients to an acceptable level. The system is implemented using Power System Computer-Aided Design for Electromagnetic Transients including Direct Current (PSCAD/EMTDC) software. It comprises a 2 MW PV farm, a 2 MW wind farm, and a backup energy storage system (ESS), which are all connected to a 132 kV grid via a step-up transformer and a transmission line. The results were obtained at critical system nodes for two standard lightning current surges, i.e., 1/10 µs and 10/350 µs, considering two lightning strike point scenarios with and without a lightning protection system (LPS). The simulation results showed that the connected SPDs could successfully limit the transient overvoltage in the system to an acceptable level. The analysis in this work is crucial for designing, operating, and maintaining a hybrid PV–wind system. It can help to find the potential vulnerability areas within such a system and implement appropriate protection measures since there is no available lightning standard for such systems. Additionally, it assists the system operators in increasing the uptime and dependability of their RE systems, limiting expensive downtime and environmental effects while optimising energy output. Based on the results obtained, recommendations were made for lightning protection developers.

Techno-Economic Analysis and Simulation of a Photovoltaic-Wind Hybrid System for Grid-Independent Applications

Techno-Economic Analysis and Simulation of a Photovoltaic-Wind Hybrid System for Grid-Independent Applications

Robust Current Control of a Small-Scale Wind–Photovoltaic Hybrid System Based on the Multiport DC Converter

In this paper, a robust current control of the hybrid renewable energy system (HRES), based on the PV-Wind system, is proposed. The HRES is connected to a multiport converter to synchronize the multi-source system with one DC-Bus. Due to their ability to integrate many renewable energy sources (RES) individually or simultaneously, multiport converters (MPC) are an innovative method suitable for renewable energy applications. Recently, many DC-DC converter designs and topologies have emerged to ensure the highest possible efficiency of hybrid RESs. The multiport converter is a typical coupling system with several modes of operation. Thus, the design of its controller become complicated. To stabilize the DC-Bus voltage, a battery has been added to the system. In this HRES configuration, all sources are connected in parallel via the multiport DC converter. We used the multiport DC converter to minimize the intermittent character of solar and wind and control the energy flow between the different power sources and the load, as well as to increase the performance of the system. The nonlinear robust control structure is based on Lyapunov approach to overcome the nonlinear model of the system to improve robustness and guarantees the asymptotic stability. The proposed control law is implemented and tested on dSPACE-DS1104. The results show the effectiveness and the feasibility of the proposed controller.

A novel cloud-based framework for optimal design of stand-alone hybrid renewable energy system considering uncertainty and battery aging

This paper performs a new optimal framework for a hybrid photovoltaic-wind system design integrated with battery storage (PV/WT/Battery), considering cloud-based uncertainty modeling and battery degradation based on real meteorological data from the Sarein-Ardabil region in Iran. The objective function is presented as minimizing the total net present cost (NPC), load loss, and battery degradation cost. The decision variables include the number of PVs, WTs, batteries, inverter power, and the angle of PVs installation, which is optimally determined via a new meta-heuristic optimization algorithm named opposition-based learning and Gradient-based optimizer (OBLGBO). In the proposed framework, the cloud theory method based on combining fuzzy theory and probability statistics has been applied for modeling the energy resources and load demand uncertainties. The simulation results indicate that considering battery degradation costs increases the overall cost of designing hybrid systems. As the cost of degradation increases, reliability indices improve due to an increase in the number of wind turbines and a decrease in the number of batteries. Also, the results demonstrated that incorporating the uncertainties based on the cloud theory increases the design cost, and the system reliability is weakened. Therefore, the proposed optimal framework has presented a real and accurate approach to the optimal design of energy systems with more accurate knowledge of electricity generation costs and the cost of improving reliability in conditions of uncertainties. Moreover, the superior capability of the OBLGBO compared with traditional GBO and the well-known particle swarm optimization (PSO) and grey wolf optimizer (GWO) is proved to achieve lower design cost and better reliability indices.

Energy Independence of a Small Office Community Powered by Photovoltaic-Wind Hybrid Systems in Widely Different Climates

Hybrid renewable energy systems are an optimal solution for small energy communities’ energy supply. One of the critical issues is the strong correlation of these systems with outdoor climatic conditions. The goal is to make local communities increasingly energy independent. To this end, an in-depth analysis of the behaviour of hybrid photovoltaic (PV)–wind systems powering small office communities in 48 locations around the world characterized by widely varying climates was conducted. System sizes, assumed to be stand-alone or grid-connected, were varied, for a total of 343 system power configurations. Highest satisfied load fraction (SLF) values are obtained with a significant predominance of PV over wind; the trend is more pronounced in dry and continental climates (zones B and D according to the Köppen climate classification). The utilization factor (UF) values of 1 are rarely reached and never in the wind-only or PV-only configurations. In all climates, the grid energy interaction factor (GEIF) values of zero are never reached but come very close. The benefit-cost ratio (BCR) of grid-connected systems is significantly higher than stand-alone systems.

Analysis and Power Quality Improvement in Hybrid Distributed Generation System with Utilization of Unified Power Quality Conditioner

This paper presents a comprehensive study that includes the sizing and power flow by series and parallel inverters in a distributed generation system (DGs) that integrates the system of hybrid wind photovoltaic with a unified power quality conditioner (UPQC). In addition to supplying active power to the utility grid, the system of hybrid wind photovoltaic functions as a UPQC, compensating reactive power and suppressing the harmonic load currents. Additionally, the load is supplied with harmonic-free, balanced and regulated output voltages. Since PVWind-UPQC is established on a dual compensation scheme, the series inverter works like a sinusoidal current source, while the parallel inverter works like a sinusoidal voltage source. Consequently, a smooth alteration from interconnected operating modes to island operating modes and vice versa can be achieved without load voltage transients. Since PV-Wind-UPQC inverters handle the energy generated through the hybrid wind photovoltaic system and the energy demanded through the load, the converters should be sized cautiously. A detailed study of the flow of power via the PV-Wind-UPQC is imperative to gain a complete understanding of the system operation and the proper design of the converters. Thus, curves that allow the sizing of the power converters according to the power flow via the converters are presented and discussed. Simulation results are presented to assess both steady state and dynamic performances of the grid connected hybrid system of PV-Wind-UPQC. This investigation is verified by simulating and analyzing the results with Matlab/Simulink.

Improvement of the energy production of a photovoltaic-wind hybrid system using NF-PSO MPPT

This manuscript gives a contribution to the optimization of a hybrid Photovoltaic-Wind Turbine system with a storage system. In order to capture the maximum power that can be produced by each source, while maintaining the rotor speed of the wind turbine at its maximum values according to wind variations, the Neuro-Fuzzy-Particle Swarm Optimization (NF-PSO) controller is proposed. The Neuro-Fuzzy method is used here because it allows an automatic generation of fuzzy rules, and the Particle Swarm Optimization to find an optimal gain allowing to readjust the dynamics of the fuzzy rules by reducing the power losses (oscillations). For the proper functioning of such a system, we have developed a fuzzy supervisor in order to have an optimal control of the system according to the variations of the requested load and the produced power by considering the storage system and the load shedding. The simulation results of the system confirmed the better performance of this method in terms of speed with a response time of 0.2s on the wind side and 0.025s on the side photovoltaic, of efficiency with 99.87% on the photovoltaic side and 99.6% on the wind side, and above all in term of oscillation reduction with practically a negligible oscillation rate compared to the NF and the Cuckoo algorithm.

Study and optimization of a Photovoltaic-Wind Hybrid System in Telico Mamou

Study and optimization of a Photovoltaic-Wind Hybrid System in Telico Mamou

Design, modeling and control of a hybrid grid-connected photovoltaic-wind system for the region of Adrar, Algeria.

The use of fossil energy for electricity production is an evident source of pollution, global warming and climate change. Consequently, researchers have been working to shift toward sustainable and clean energy by exploiting renewable an environmentally friendly resources such as wind and solar energies. On the other hand, energy security can only be achieved by considering multiple resources. Large-scale renewable energy power plants are a key solution for diversifying the total energy mix and ensuring energy security. This paper presents a contribution to diversify the energy mix in Algeria and help mitigate power shortages and improve grid performance. In particular, the paper aims at designing and modeling a large-scale hybrid photovoltaic-wind system that is grid connected. An innovative control approach using improved particle swarm optimized PI controllers is proposed to control the hybrid system and generate the maximum power from the available wind and solar energy resources. Furthermore, economic, environmental and feasibility studies of the project were conducted using HOMER software to assess the viability of the system and its contribution to reduce greenhouse gas emissions.

Optimal sizing of hybrid PV–Wind–Battery storage system for Net Zero Energy Buildings to reduce grid burden

Accessing reliable, clean and affordable energy can be achieved by hybridization of renewable energy sources (RES) such as solar and wind. Such a hybrid photovoltaic (PV) and wind system along with battery storage (BS) has been considered for this work to realize the concept of Net Zero Energy (NZE) for a group of buildings (NZEBs). Generally, optimal sizing of hybrid PV–Wind system for NZEBs are carried out to ensure the minimum Loss of Power Supply Probability (LPSP) and cost with NZE balance constraints. But, the energy transfer between the buildings and grid has not been considered which is a vital parameter in optimal sizing of renewable energy generators for NZEBs. In NZEBs, over sizing/under sizing of renewable energy generator leads to greater energy export/import between the building and grid, which eventually increases burden on the electrical grid. So, in this work, minimization of total energy transfer (TET) is considered as the third objective function along with LPSP and cost to minimize the grid burden. A Non-dominated Sorting Genetic Algorithm II (NSGA-II) has been utilized for optimization of three objective functions such as annualized cost of the system (ACS), LPSP and TET, which are conflicting and incomparable. Based on the proposed sizing technique, the size of hybrid PV–Wind generators and BS capacity are determined from the pareto front solutions. To exemplify the reduced grid burden by reducing the TET, the results of proposed three objective function sizing technique are compared with the results of two objective function (cost and LPSP) sizing technique and analyzed for two different conditions of LPSP. The results confirm that the reduced TET has been achieved through the proposed sizing technique.

Energy production features of rooftop hybrid photovoltaic–wind system and matching analysis with building energy use

Rooftop photovoltaic (PV)–wind hybrid systems serve as a promising energy supply source to mitigate environmental concerns and satisfy high energy demands. Most of energy matching studies focused on the matching capability of photovoltaic generation with building load, and the application of wind power to complement PV was rarely considered. In the context, this study explored the production aspects of PV–wind turbine (WT) hybrid systems and their potential to meet building energy use demands in densely built urban areas. Both solar and wind resources in 18 cities in eastern China were classified into three energy output levels, and Hangzhou was selected as a representative city for analysis of the complementarity of the two resources. Based on the modeling of hybrid PV–wind system generation, a PV/WT production feature curve was generated by k-means clustering. The matching between renewable energy production and building energy use and the influences of different wind resources and building heights were analyzed for rooftop hybrid systems in two typical residential buildings. The results reveal that the wind and solar resources in Hangzhou are partly complementary in terms of time sequence and power output. For the multi-story and high-rise residential building considered, a rooftop hybrid PV–WT system was concluded to be beneficial in improving energy generation, reliability, and load matching performance in a limited space. The technical performance for the high-rise case was inferior to that for the multi-story case considered. In the case of residential buildings, the matching between on-site supply and load is influenced by the local wind resources and building height. The richer the urban wind resource, the greater the load cover ratio and the self-sufficiency of the installed rooftop hybrid system. However, the load matching performance declines with increasing building height. The proposed general method for analyzing rooftop hybrid PV–WT systems can enable widespread and efficient solar and wind energy utilization in densely populated and built urban areas.

Embedded solution for data acquisition and management strategy dedicated to a hybrid renewable energy source for remote electricity supply

Electrifying people using renewable energy is a promising alternative that is gaining increasing importance for remote areas needs, but this solution is quite sensitive to the intermittent nature of environmental data, which puts more strain on the designer to overcome these problems to surely electrify consumers. In this work, the authors tackle a key topic of energetic and environmental data acquisition and energy management for electrifying a typical remote zone using a hybrid photovoltaic-wind system associated to an electrochemical storage system. An innovative alternative for data acquisition and intelligent on-board management of this system based on a Raspberry PI programmable target is presented. The first part of this article outlines the photovoltaic-wind turbine-batteries generation system architecture. The data acquisition and energy management methodology is described in the second part of this article. The results are finally discussed from the point of view of the suitability of the proposed embedded solution.

Study and optimization of a Photovoltaic-Wind Hybrid System in Telico Mamou.

Study and optimization of a Photovoltaic-Wind Hybrid System in Telico Mamou.