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This paper studies a Hybrid Renewable Energy System (HRES) as a reliable source of the power supply in the case of the connection to the grid. The grid connection imposes restrictions to the power delivered and harmonic content on the HRES. This causes the HRES to use multiple control systems and subsystems, as the normalization of the measurements, the current control, active harmonic compensation, synchronization, etc., described in this paper. Particular attention was paid to interactions in the storage system of the HRES. The durability of the HRES can be increased by the combination of the supercapacitors and batteries. This requires a power management solution for controlling the energy storage system. The aim of the supercapacitors is to absorb/inject the high-frequency fluctuations of the power and to smooth out the power of the batteries system of the HRES. This can be possible owing to the use of a low-pass second order filter, explained in this paper, which separates the high-frequency component of the storage system reference for the supercapacitor from the low-frequency component for the batteries system. This solution greatly increases the reliability and durability of the HRES.

This paper involves the hybrid power potential implementation in view of six climatic zones in Indian state of Tamil Nadu. An intertwined techno-economic feasible study and energy management analysis of Hybrid Renewable Energy System (HRES) has been proposed to cater to need of the electrical energy requirement in un-electrified village hamlets of Tamil Nadu. The HRES feasibility, size optimization, cost and sensitivity analyses are performed to satisfy the electrical energy requirements of the considered area. A combination of Demand Side Management (DSM) and optimum tilt solar panel approach has also been analyzed through HOMER Energy ® simulation. The selection of HRES configuration is based on real-time data collected from six different climatic zones. The optimization results of the considered system are presented and compared with and without DSM strategy. The optimum planning of HRES is based on ranking scheme which includes technical and ecological aspects for sustainable development. In addition, to evaluate the most feasible consideration of the system, sensitivity analysis has been performed upon the load variation, biomass and diesel price too. The simulation results of the proposed HRES configuration can improve the renewable fraction and offer more employment opportunities to the local people, compared to the existing PV-DG-Battery HRES. [ABSTRACT FROM AUTHOR]

Due to the scarcity of conventional energy resources and the greenhouse effect, renewable energies have gained more attention. This paper proposes methods for multi-objective optimal design of hybrid renewable energy system (HRES) in both isolated-island and grid-connected modes. In each mode, the optimal design aims to find suitable configurations of photovoltaic (PV) panels, wind turbines, batteries and diesel generators in HRES such that the system cost and the fuel emission are minimized, and the system reliability/renewable ability (corresponding to different modes) is maximized. To effectively solve this multi-objective problem (MOP), the multi-objective evolutionary algorithm based on decomposition (MOEA/D) using localized penalty-based boundary intersection (LPBI) method is proposed. The algorithm denoted as MOEA/D-LPBI is demonstrated to outperform its competitors on the HRES model as well as a set of benchmarks. Moreover, it effectively obtains a good approximation of Pareto optimal HRES configurations. By further considering a decision maker’s preference, the most satisfied configuration of the HRES can be identified. [ABSTRACT FROM AUTHOR]

In the current smart grid scenario, the evolution of a proficient and robust maximum power point tracking (MPPT) algorithm for a PV subsystem has become imperative due to the fluctuating meteorological conditions. In this paper, an adaptive feedback linearization-based NeuroFuzzy MPPT (AFBLNF-MPPT) algorithm for a photovoltaic (PV) subsystem in a grid-integrated hybrid renewable energy system (HRES) is proposed. The performance of the stated (AFBLNF-MPPT) control strategy is approved through a comprehensive grid-tied HRES test-bed established in MATLAB/Simulink. It outperforms the incremental conductance (IC) based adaptive indirect NeuroFuzzy (IC-AIndir-NF) control scheme, IC-based adaptive direct NeuroFuzzy (IC-ADir-NF) control system, IC-based adaptive proportional-integral-derivative (IC-AdapPID) control scheme, and conventional IC algorithm for a PV subsystem in both transient as well as steady-state modes for varying temperature and irradiance profiles. The comparative analyses were carried out on the basis of performance indexes and efficiency of MPPT.

• Viability of a HRES designed to meet the electric demand in Moroccan residential buildings. • New design based on the synergic interaction between building simulation and HRES optimization. • Hybridization of SDS and WT technologies including the power-to-hydrogen is studied. • Optimal design configuration was determined for each studied locations. In this work, an Hybrid Renewable Energy System (HRES) based on microgrid power is proposed and optimized to meet the electric demand of a sustainable multi-family buildings with possible generation of clean hydrogen. Hourly building simulation is carried out based on meteorological data to predict the year-round electrical consumption of the designed buildings. The proposed hybrid system includes a Solar Dish Stirling (SDS) technology combined with a Wind Turbine (WT) for power generation, an electrolyzer, a hydrogen storage tank, as well as a battery bank. The novelty of the study resides in the replacement of conventional hybrid systems, such as a photovoltaic PV/WT assembly, with an SDS/WT system that has the potential to reach higher efficiencies and economic competitiveness. An optimization process is investigated to evidence the optimum HRES design based on the lowest Net Present Cost (NPC). Sensitivity studies are performed to illustrate the effect of main functioning parameters and how they impact the overall project viability. Moreover, the performance of the model is evaluated in two selected sites in Morocco, namely Ouarzazate and Dakhla, and a comprehensive techno-economic study of the integrated system is investigated. The findings indicate that the HRES design and configuration are site-dependent due to discrepancies in wind and solar energy potential of the examined sites. The optimum architecture of the assessed HRES in Dakhla greatly promote the implementation of WT technology with a NPC/ LCOE of about 3.053 M€/0.0697 €/kWh, respectively. In Ouarzazate, it was found that the optimum design configuration relies exclusively on the SDS technology and correspond to NPC/ LCOE of 3.391 M€/ 0.126 €/kWh, respectively. LCOH values obtained by the optimum HRES configuration were determined 21.4 €/kg and 23.6 €/kg for Dakhla and Ouarzazate, respectively. This study demonstrates the viability of SDS implementation in future HRESs and open the perspectives for its role in carbon–neutral buildings. [ABSTRACT FROM AUTHOR]

In recent times, hybrid renewable energy systems are increasingly being utilized to provide electricity in remote areas especially where the grid extension is considered too expensive. This study presents the results of techno-economic analysis of hybrid system comprising of solar and wind energy for powering a specific remote mobile base transceiver station ( BTS) in Nigeria. All the necessary modeling, simulation, and techno-economic evaluation are carried out using the assessment software package HOMER (Hybrid Optimization Model for Electric Renewable). Two best optimal system configurations namely PV-diesel-battery and PV-wind-diesel-battery systems are compared with the conventional stand-alone diesel generator (DG) system. Findings indicated that PV array (10 kW) - DG (5.5 kW) - battery (64 units Trojan L16P) is the most economically viable option with the total net present cost of $69,811 and per unit cost of electricity of $0.409. The sensitivity analysis is also carried out to find the effects of probable variation in solar radiation, wind speed, and diesel price in the optimal system configurations. Finally, the environmental benefit of hybrid systems over the conventional stand-alone diesel system is described. The obtained results show that the hybrid PV-diesel-battery system provides a reduction in CO2 emissions of about 16.4 tons per year as compared to the stand-alone DG system. [ABSTRACT FROM AUTHOR]

The demographic growth and the irreversible decline of fossil fuel deposits argue for alternative resources to meet energy demand. The main challenge is to make renewable energy sources (RES) and hydrogen carriers work synergistically to minimise waste and increase sustainability. Hybrid renewable energy systems (HRES) tackle this task by integrating RES and other resources to provide energy. Recently, Power-to-X (P2X) has been gaining attention for its versatility in converting hydrogen into different energy carriers. This review provides a comprehensive overview of the HRES literature and the current state of the art, highlighting key features, analysis, and methods. Future research trends are discussed, emphasising the need to integrate other energy carriers, including hydrogen. A survey of the Power-to-X possible uses in HRESs is carried out, describing which Power-to-X technologies belong to HRES state-of-the-art. Power-to-X paths not yet explored are discussed, remarking the benefit and potential uses as a means to increase the reliability of the energy system of each HRES Power-to-X technology integration, highlighting the unexplored paths. In addition, future developments and gaps in the current state of the art according to HRES with Power-to-X are highlighted. Finally, recommendations on hybrid renewable energy systems, including Power-to-X, are highlighted by outlining future research areas. • HRESs scientific literature and current state-of-the-art. • HRES future research trends. • HRES with P2X state-of-the-art. • Current gaps and trends on P2X in HRES integration. [ABSTRACT FROM AUTHOR]

Abstract: Research works on hybrid renewable energy systems for rural electrifications have been quite intensive in recent years. Traditional power systems for remote or rural areas are based on fossil fuels. After addition of renewable energy resources, solar energy applications have become popular in remote energy systems. The recent study and research works show that adding other possible renewable energy resources such as wind, hydro and biomass could make a hybrid system more cost-effective and environmentally friendly. Hence, in the present study, an overview of applied hybrid renewable energy system (HRES) for worldwide villages with special attention on Malaysia has been proposed to help present and future works for better achievement in this field. Furthermore, a proper design and analysis for one village in Malaysia based on proposed combination is provided. The results show that combination of photovoltaic-wind -battery is defined as a cost-effective HRES for villages in Malaysia. [Copyright &y& Elsevier]

The scientific literature lacks methodologies for assessing HRES investments because of complex interactions among HRES components, conflicting objectives, and uncertainty in the energy demand. This work fills this gap by presenting a methodology to assess long-term investments in HRES for off-grid buildings. To strengthen the reliability of the assessment, the methodology exploits an HRES optimal synthesis, sizing and operation simulating the system and embodying the interactions among HRES components for both electrical and heat generation, the building loads evaluation, and the verification of the effect of uncertainties in the energy demand. These aspects have already been investigated, but, to our best knowledge, have never been considered in a concurrent and integrated way. The resulting designs are optimised through an NSGA-II algorithm that minimises the system CO 2 emissions and differential cost with respect to a solution that does not use renewable energy sources. The soundness of the solutions is evaluated through a scenario analysis and a sensitivity analysis using the Morris method. The applicability of the proposal was verified through a case study in an off-grid facility, showing possible savings up to 47 k€ and 320 t CO 2. The methodology is thus strongly consistent with the building decarbonisation addresses set by the policymakers. • The methodology optimises HRES synthesis, sizing and control in off-grid building. • The methodology is applied to a case study of a farm hostel in Italy. • The Pareto frontier is created considering environmental and economic aspects. • Five optimal solutions are analysed, distinct for total costs and caused emissions. • Scenario and sensitivity analyses corroborate the robustness of the solutions. [ABSTRACT FROM AUTHOR]

• Direct sizing of wind/solar energy systems via averaged meteorological parameters. • No need for annual detailed wind and irradiation data for wind/solar system sizing. • Implementation of size estimation function by polynomial regression and SVR. Solar and wind energies are suitable alternatives to fossil-based electricity generation. Hybrid utilization of wind and solar generators are preferred to reduce the intermittency of output power. Hybrid renewable energy systems (HRES) have to be sized optimally in the design stage. In this regard, wind speed and solar irradiation data have to be measured and collected at short intervals and for at least one year at the site location, which means a delay in the design and construction of HRES. The purpose of this paper is to eliminate the need for detailed and long-term data in the HRES sizing process by replacing wind speed and solar irradiation data with averaged and usually-available values of meteorological parameters of the site, e.g., air temperature, elevation, relative humidity, roughness length, latitude, longitude, and precipitation. In this paper, the size of the wind/photovoltaic/battery/diesel HRES is estimated as a function of site parameters using polynomial regression and support vector regression models. 105 sites from Iran have been studied as training data to build these models and test them. Sensitivity analysis shows that estimation accuracy increases by increasing training data. Thus, it is expected that by using a sufficient number of training data with global distribution, the accuracy of the models approach the accuracy of current optimal sizing methods while the time-consuming wind speed and solar radiation data collection have been eliminated in the proposed method. For example, by increasing the training data from 40 to 100 sites, the mean absolute percentage error (MAPE) of estimating the HRES size reduced by 2.3 to 3.5 times. [ABSTRACT FROM AUTHOR]

This paper presents a comprehensive review of machine learning (ML) based approaches, especially artificial neural networks (ANNs) in time series data prediction problems. According to literature, around 80% of the world's total energy demand is supplied either through fuel-based sources such as oil, gas, and coal or through nuclear-based sources. Literature also shows that a shortage of fossil fuels is inevitable and the world will face this problem sooner or later. Moreover, the remote and rural areas that suffer from not being able to reach traditional grid power electricity need alternative sources of energy. A "hybrid-renewable-energy system" (HRES) involving different renewable resources can be used to supply sustainable power in these areas. The uncertain nature of renewable energy resources and the intelligent ability of the neural network approach to process complex time series inputs have inspired the use of ANN methods in renewable energy forecasting. Thus, this study aims to study the different data driven models of ANN approaches that can provide accurate predictions of renewable energy, like solar, wind, or hydro-power generation. Various refinement architectures of neural networks, such as "multi-layer perception" (MLP), "recurrent-neural network" (RNN), and "convolutional-neural network" (CNN), as well as "long-short-term memory" (LSTM) models, have been offered in the applications of renewable energy forecasting. These models are able to perform short-term time-series prediction in renewable energy sources and to use prior information that influences its value in future prediction. [ABSTRACT FROM AUTHOR]

Renewable energy technologies can not only help in mitigating the greenhouse gas (GHG) emissions but it can also be very useful for electricity generation at remote locations, where no other means of power are available. The present study focuses on the techno-economic optimum design of a small hybrid renewable energy system (HRES) consisting of wind-solar as primary energy sources. The HRES was modelled for a remote island (Deokjeok-do Island, South Korea) using real electricity consumption data for one complete year. A daily mean load of 24,720 kWh was entered at Deokjeok-do Island with a peak load of 2291.54 kW. Average annual values of wind speed and daily solar radiations were estimated to be 3.6 m/s (10 m height) and 4.13 kWh/m2, respectively. A total of 8760 simulations were performed to achieve the hourly load demand of the mentioned island. In order to deal with the surplus and electricity deficit, two different types of energy storage systems (ESS) were modelled i.e., battery and pumped hydro storage (PHS). Four different HRESs were also evaluated as the most suitable based on levelized cost of energy (LCOE) and net present cost (NPC). A detailed economic break-down of each component and the impact of different sensitivity variables on decision making have also been discussed in detail. [ABSTRACT FROM AUTHOR]

Human work has been automated and replaced by various smart appliances at residential buildings with an objective to save time and energy. So, there is a massive upsurge of energy consumption everywhere and in due course, it resulted in increased electrical bills than before. In order to meet the growing utilization of more electricity by consumers at residences, internalization of renewable energy systems are firmly recommended for a better transformation. Hither, the IEMS is principally aiming to truncate the rate of electricity bills to consumers. Likewise, scheduling the usage of smart appliances and implementing load management practices prudently, a peak load reduction can be certainly accomplished by effectively using Solar Power, Batteries and Utility Grid. Already existing TOU tariff is employed in the process along with restructured components and renewable resources to manage the loads of different smart appliances according to their usage priority at different times of a day. This automated system is able to manage multiple heavy loads smartly with the help of renewable energy resources even at peak hours of a day. • Introducing a new Pre-emptive Priority based load scheduling approach to achieve the peak load reduction of the premises. • Analysing the behavioural Load Modelling impacts on Time of Use (TOU) tariff in utility bill. • Numerous operating modes of REMS were considered and found the Techno -Economic performance evident through a case study. [ABSTRACT FROM AUTHOR]

In this study, a techno‐economic feasibility study of off‐grid hybrid power systems is performed for a rural area, which is located at a significant distance from the grid connection in Bushehr province of Iran, beside the Persian Gulf. HOMER simulation software is used to determine the economic feasibility of the systems. The simulations were focused on net present cost which includes cost of energy (COE) and renewable fraction of the hybrid configurations. The results indicate that the wind/PV/diesel/battery hybrid renewable system configuration is the optimum system, primarily based on COE and achieving a 61.4% renewable energy fraction. The proposed hybrid power system not only exhibits better performance in fuel consumption but also reduces carbon dioxide emissions. It could mitigate the emission of 664 tons of greenhouse gases to the local atmosphere of the village, as well as other air pollution emissions, which could offer substantial benefit to both residence and environment. Furthermore, a sensitivity analysis shows that a rise in fuel prices will derive more demand for alternative energy sources. For instance, when the fuel price is more than $0.5/L, the optimal energy option would be the wind/PV/battery system. In that case, it is no longer economical to use the diesel generator and renewable energy penetration becomes 100%. © 2019 American Institute of Chemical Engineers Environ Prog, 38:e13146, 2019 [ABSTRACT FROM AUTHOR]

This paper studies a Hybrid Renewable Energy System (HRES) as a reliable source of the power supply in the case of the connection to the grid. The grid connection imposes restrictions to the power delivered and harmonic content on the HRES. This causes the HRES to use multiple control systems and subsystems, as the normalization of the measurements, the current control, active harmonic compensation, synchronization, etc., described in this paper. Particular attention was paid to interactions in the storage system of the HRES. The durability of the HRES can be increased by the combination of the supercapacitors and batteries. This requires a power management solution for controlling the energy storage system. The aim of the supercapacitors is to absorb/inject the high-frequency fluctuations of the power and to smooth out the power of the batteries system of the HRES. This can be possible owing to the use of a low-pass second order filter, explained in this paper, which separates the high-frequency component of the storage system reference for the supercapacitor from the low-frequency component for the batteries system. This solution greatly increases the reliability and durability of the HRES. [ABSTRACT FROM AUTHOR]