Reliable Renewable Energy System Research Articles

Theoretical models for predicting ventilation performance of vertical solar chimneys in tunnels

Solar chimney as a reliable renewable energy system has been primarily utilized for building ventilation, but its application in the tunnel is rarely explored. This study develops theoretical models to predict the ventilation performance of vertical solar chimney in urban tunnel. Five temperature distribution types within the chimney cavity are analyzed, including uniform, vertically linear, horizontally semi-parabolic, two piecewise semi-parabolic in the depth direction, and three-dimensional parabolic profiles. The theoretical models consider the effect of chimney configuration, tunnel geometry, glazing materials, and solar radiation intensity on airflow rate through solar chimney. Validation against experimental data and numerical simulation shows that considering three-dimensional temperature distributions results in an average 11 % deviation from validation data, outperforming assumptions of uniform (29.3 % deviation) or lower-dimensional profiles. The volumetric flow rate through solar chimney exponentially decreased with h/w and h/d that the optimum ratio of h/d is 10. The airflow rate linearly increased with 0.14 power of glazing absorptivity. This analysis provides technical guidance for optimizing solar chimney design in tunnels, enhancing natural ventilation, and reducing energy consumption for mechanical ventilation systems.

SkyGPT: Probabilistic ultra-short-term solar forecasting using synthetic sky images from physics-constrained VideoGPT

The variability of solar photovoltaic (PV) power output, driven by rapidly changing cloud dynamics, hinders the transition to reliable renewable energy systems. Information on future sky conditions, especially cloud coverage, holds the promise for improving PV output forecasting. Leveraging recent advances in generative artificial intelligence (AI), we introduce SkyGPT, a physics-constrained stochastic video prediction model, which predicts plausible future images of the sky using historical sky images. We show that SkyGPT can accurately capture cloud dynamics, producing highly realistic and diverse future sky images. We further demonstrate its efficacy in 15-minute-ahead probabilistic PV output forecasting using real-world power generation data from a 30-kW rooftop PV system. By coupling SkyGPT with a U-Net-based PV power prediction model, we observe superior prediction reliability and sharpness compared with several benchmark methods. The propose approach achieves a continuous ranked probability score (CRPS) of 2.81 kW, outperforming a classic convolutional neural network (CNN) baseline by 13% and the smart persistence model by 23%. The findings of this research could aid efficient and resilient management of solar electricity generation, particularly as we transition to renewable-heavy grids. The study also provides valuable insights into stochastic cloud modeling for a broad research community, encompassing fields such as solar energy meteorology and atmospheric sciences.

ELECTRICAL ENGINEERING IN RENEWABLE ENERGY SYSTEMS: A REVIEW OF DESIGN AND INTEGRATION CHALLENGES

As the global pursuit of sustainable energy intensifies, the integration of renewable energy sources into existing power systems has become a critical focal point for electrical engineers. This review explores the challenges and advancements in the field of Electrical Engineering concerning the design and integration of renewable energy systems. The transition from traditional fossil fuels to renewable sources, such as solar, wind, and hydroelectric power, necessitates a comprehensive understanding of the intricate engineering aspects involved. The first section of the review delves into the design challenges faced by electrical engineers when developing efficient and reliable renewable energy systems. This encompasses the optimization of power generation from intermittent sources, the enhancement of energy conversion technologies, and the development of energy storage solutions to mitigate the inherent variability of renewables. Cutting-edge design methodologies and innovative materials are discussed to highlight the ongoing efforts to improve the performance and reliability of renewable energy systems. The second section focuses on the integration challenges encountered during the incorporation of renewable energy into existing power grids. Grid stability, power quality, and the management of decentralized energy sources pose significant hurdles. Electrical engineers are addressing these challenges through the implementation of advanced control systems, smart grid technologies, and energy management strategies. The review also explores the role of energy storage systems and the potential of emerging technologies like microgrids in facilitating seamless integration. Furthermore, the review examines the interdisciplinary nature of electrical engineering in the context of renewable energy, emphasizing the collaboration between electrical engineers, environmental scientists, and policymakers. The synergy between these disciplines is crucial for developing holistic solutions that address not only technical challenges but also environmental and regulatory considerations. This review provides a comprehensive overview of the design and integration challenges faced by electrical engineers in the realm of renewable energy systems. By understanding and overcoming these challenges, the global community can accelerate the transition towards a sustainable and resilient energy future.
 Keywords: Renewable energy, Energy Integration, Challenges, Electrical, Engineering, Review.

Optimizing performance of a reduced switch multi‐level inverter with moth‐flame algorithm and SHE‐PWM

AbstractMulti‐level inverters are widely used in high‐voltage and high‐power applications due to the increasing demand for renewable energy. This study proposes a novel single‐phase reduced switch multi‐level inverter topology that generates 11 levels of output voltage steps, operates in asymmetric mode, and uses fewer power electronic switches with efficient switching control. To optimize the inverter's performance, Moth Flame Optimization (MFO), Particle Swarm Optimization (PSO), and Whale Optimization Technique (WOA) are utilized to apply the selective harmonic elimination technique. The proposed circuit is implemented in PSIM software using optimized switching angles, and the fitness functions and switching angles for the three optimizers are evaluated and reported. The inverter's performance at optimal modulation points for the three optimizers is computed and analyzed, with the Total Harmonic Distortion (THD) measured at 0.82 modulation point before and after filtering. Results show that MFO outperforms PSO and WOA with the lowest THD values of 0.85% and 0.78%, respectively; therefore, complying with the IEEE 519 standard. The experimental validation of MFO's superiority is performed using the Typhoon HIL‐402 hardware device. This study provides a promising solution for the design and optimization of multi‐level inverters, paving the way for more efficient and reliable renewable energy systems.

Photoelectrochemical Devices for Oxygen and Fuel Production on Moon and Mars

Human space exploration and the realisation of a green energy economy on Earth are confronted with the same challenge: both require efficient, stable and reliable renewable energy systems.1 Currently existing solutions such as the water electrolyzer in operation on the International Space Station (ISS) for oxygen and hydrogen production are not feasible in future lunar and Martian habitats as they are too bulky and heavy to transport and they lack the required reliability and efficiency2. Photoelectrochemical (PEC) devices not only meet the weight and volume constraints imposed onto devices for space applications by utilising a monolithic design for light absorption, charge separation and catalysis,3 they can also directly be coupled to solar concentrators in order to harvest the abundant solar energy available in space. Despite the advantages, PEC devices are nearly exclusively researched and developed for terrestrial applications and only a very few examples explore the possibility of utilizing the integrated semiconductor-electrocatalyst systems for space applications.4 Here, we present an unprecedented theoretical analysis of the applicability of PEC devices for lunar solar water-splitting and Martian CO2 reduction. These target reactions are in line with roadmaps of international space organisations aiming at a habitat establishment on the lunar South Pole, where water ice is assumed to be present in the Shackleton Crater. Furthermore, the atmosphere on Mars is composed of about 96% gaseous CO2, motivating our choice to investigate Martian CO2 to CO and CH4 conversion.5 Both reaction products could be used as propulsion additives or as precursors for the synthesis of hydrocarbon-based molecules in analogy to terrestrial applications. Firstly, we calculated a refined Martian solar irradiance spectrum and established the theoretical framework to describe PEC devices on Moon and Mars before calculating device limiting efficiencies and expected product rates for realistic devices at different solar irradiance scenarios. Our findings emphasise that PEC devices are indeed applicable on Moon and Mars, particularly when coupled to solar concentrators. In addition, it is evident that gas diffusion electrodes (GDEs), which mark a significant part of CO2 reduction devices investigated terrestrially, are surprisingly not necessarily viable in situations of limited solar irradiance such as present on Mars.References Ross B, Haussener S, Brinkert K. Photoelectrochemical devices for oxygen and fuel production on Moon and Mars. In review. Brinkert K, Mandin P. Fundamentals and future applications of electrochemical energy conversion in space. npj Microgravity 8, (2022).Cheng W-H, et al. Monolithic Photoelectrochemical Device for Direct Water Splitting with 19% Efficiency. ACS Energy Letters 3, 1795-1800 (2018). Brinkert K, et al. Efficient solar hydrogen generation in microgravity environment. Nature Communications 9, (2018). Yoshizaki T, McDonough WF. The composition of Mars. Geochimica et Cosmochimica Acta 273, 137-162 (2020).

Effect of geopolitical risk and economic uncertainty indices on renewable energy

In this study, the relationships between five renewable energy sub-sectors markets and the geopolitical risk (GPR) and economic uncertainty indices (EUI) were examined using daily data from March 30, 2012, to April 1, 2022. Convergent cross mapping results show that the renewable energy indices have definite relationships with the GPR and EUI. The renewable energy indices show differences in response directions, speed and trends for a standard information difference impulse from the GPR and the EUI. A positive dynamic conditional correlation between renewable energies and EUI was observed in the first and second waves of the COVID-19 outbreak. In contrast, there was a relatively decreased effect for two risk indices during the Russia–Ukraine conflict of February–March 2022. Our results show that renewable energy may act as a time-varying hedge against economic uncertainty and GPR owing to its safe-haven properties at various scales. Moreover, building more secure and reliable renewable energy systems can help countries to increase their energy independence, which protects them against the risks of political and economic uncertainty.

Comprehensive Analysis of Multi-Objective Optimization Algorithms for Sustainable Hybrid Electric Vehicle Charging Systems

This study presents a multi-objective optimization approach for designing hybrid renewable energy systems for electric vehicle (EV) charging stations that considers both economic and reliability factors as well as seasonal variations in energy production and consumption. Four algorithms, MOPSO, NSGA-II, NSGA-III, and MOEA/D, were evaluated in terms of their convergence, diversity, efficiency, and robustness. Unlike previous studies that focused on single-objective optimization or ignored seasonal variations, our approach results in a more comprehensive and sustainable design for EV charging systems. The proposed system includes a 223-kW photovoltaic system, an 80-kW wind turbine, and seven Lithium-Ion battery banks, achieving a total net present cost of USD 564,846, a levelized cost of electricity of 0.2521 USD/kWh, and a loss of power supply probability of 1.21%. NSGA-II outperforms the other algorithms in terms of convergence and diversity, while NSGA-III is the most efficient, and MOEA/D has the highest robustness. The findings contribute to the development of efficient and reliable renewable energy systems for urban areas, emphasizing the importance of considering both economic and reliability factors in the design process. Our study represents a significant advance in the field of hybrid renewable energy systems for EV charging stations.

External wind on the optimum designing parameters of a wall solar chimney in building

Solar chimney is a reliable renewable energy system that enhances the natural ventilation to reduce the energy consumption in buildings. Under the fact that previous optimization designs usually ignore the external wind, the impacts of external wind on the optimum designing parameters are then investigated. It is confirmed that external wind could affect its optimum designing parameters, which are different from those previously obtained value in the literature without considering the external wind. For the analysed wall solar chimney, it was known that previously obtained optimal cavity depth of 0.2–0.3 m is no longer applicable under the external wind, and the optimal value rises to 0.4–0.5 m, while the same applies to inlet height/area. Solar chimney performance is enhanced under the external wind, which is not only because of the incoming wind flow from the room opening but also the reduced air resistance. It was observed that increased solar intensity shows limited influences on the overall airflow characteristics. Solar chimney performance also presented a generally enhanced trend under a low external wind speed, but a strong wind could dominate its performance with limited fluctuation even though the wind angle is higher as 45°. It was known that the airflow rates through the solar chimney are largely hampered with a small cavity depth (i.e., smaller than 0.2 m) and inlet height under the external wind. And the airflow profiles are less affected when both of cavity depth and inlet height are bigger than 0.2 m. The obtained research outcomes could provide a technical guide on the optimization design of solar chimney in buildings.

Trombe wall for a residential building in Sichuan-Tibet alpine valley – A case study

Trombe wall (also called T-Wall) as a reliable renewable energy system has attracted increasing attention from both academics and engineers under the current energy crisis. This study then focused on a Tibetan dwelling retrofitting in the Sichuan-Tibet Alpine Valley, adopting T-wall as a passive heating solution. We investigated a classic T-wall in the target building based on field measurement, orthogonal experiment, and numerical simulation methods. It was known that the maximum average indoor temperature of the master room can reach 18.87 °C in the coldest month (January) of the Sichuan-Tibet Alpine Valley. Six key influencing factors were analyzed accordingly, including the south T-wall-to-wall ratio, inlet/outlet height, glazing inclination angle, storage wall thickness, storage wall material and cavity gap. Among those analyzed factors, it was obtained that the highly significant factors are the south T-wall-to-wall ratio and glazing inclination angle. The larger the proportion of the south T-wall-to-wall ratio, the better the indoor temperature is. The best glazing inclination angle was obtained as 100 for the target residential building under the local conditions. Solar passive technology as a cost-effective solution can improve the indoor thermal environment of the Tibetan dwellings in the Qinghai-Tibet Plateau. The total annual energy consumption of the Tibetan dwelling using the optimal combination can be reduced by about 72% compared to that of the existing Tibetan houses. The research outcomes can provide a practical guide on the future design of passive solar technologies.

Integration of Renewable Energy Systems for Optimal Energy Needs- a review

The thrust for the energy need is ever long persisted to sustain the peak varying demands in all over the countries. The focus is to obtain feasible, sustainable and mainly reliable renewable energy systems to meet the power demands. This is the fact that global modernization and revolutions cause an impact on energy requirements. As of primary concern, the rural energy demands should be met with an uninterrupted reliable supply of energy demands. The development of the rural energy sector through the integration of renewable energy systems, in turn, will pave the way to accomplish the growing demands of power. This can be done through a better understanding of the integration of renewable energy systems. The problem is the type of integration selected for the study will suit the energy needs of the rural site under consideration. This paper presents the view of optimal methods adopted to obtain the optimization with different types of integration of the systems. The proposed models are reviewed for simulation and factors or parameters in their studies. This study also reveals the facts, management of integrated system and problems in integrating renewable energy systems.

Generating synthetic sequences of global horizontal irradiation

When designing renewable energy systems it is common practice to use a short period of historical weather data or Typical Meteorological Year (TMY) data to evaluate the performance of a renewable energy system for a particular location. However, short periods of historical data or TMY data do not capture enough of the variation required to design a reliable renewable energy system. Longer data sequences are necessary to include a greater variety of sequences; synthetic sequences are useful because they can include sequences that have not occurred in the recorded data but are nonetheless as likely to occur as the observed data.We propose a method to generate synthetic sequences of daily and hourly global horizontal irradiation (GHI) by developing a model to deal with the deterministic component of GHI, and then adding a stochastic component using a nonparametric bootstrapping technique. We use our synthetic daily and hourly models separately and reconcile them to match afterwards, unlike other studies that generate synthetic GHI data downscaled/interpolated from observed data. This is a fundamental difference to the literature.The synthetic daily and hourly GHI sequences can be used, for example, as input for testing the performance and operation of a solar energy system for a wider range of scenarios than previously observed data. Further, one could incorporate synthetic GHI with other synthetic renewable energy data, such as synthetic wind farm electricity output. Both of these approaches would be useful when designing a reliable renewable energy system.The synthetic sequences of daily and hourly GHI exhibit the same statistical properties as the real data. The two-sample Kolmogorov-Smirnov (KS) test shows that the distribution of the synthetic sequences of daily and hourly GHI match the distribution of the observed daily and hourly GHI respectively. The synthetic sequences of daily GHI have the same serial correlation structure as the observed data, an autoregressive model of order 1, AR(1), with similar AR(1) coefficients. Also, the synthetic sequences of hourly GHI have the same serial correlation structure as the observed data, an autoregressive model of order 3, AR(3), with similar AR(3) coefficients.

Techno-Economic Assessment of Installing a Reliable Renewable Energy System for Electric Power Generation at Koforidua Polytechnic

Ghana has been experiencing a lot of power outages over the years, mainly due to the heavy reliance on hydroelectric power plants, poor maintenance culture for existing plants as well as rising energy demand for development. These shortages have hindered the smooth running of businesses and academic institutions in the country. Institutions therefore operate with Genset for 12 hours with huge operational cost. This work therefore seeks to technically and economically assess a reliable alternative power supply for Koforidua Polytechnic. The building used in this assessment is the engineering block, which has five (5) floors with a total energy consumption of 227.520kWh/day for lights and fans. Homer software for micro grid and distributed generation power system design and optimization (NREL Homer) was used to do the optimization and sensitivity analysis with daily average electric demand of 9.48kW and peak power of 26.7kW with July, August and December having the highest mean values. The designed Photovoltaic (PV) system consists of 70kW monocrystalline PV modules of 250 Wp at a system voltage of 12V with 111 batteries and 17kW converter. The levelized Net Cost to install a renewable energy system (PV) divided by its expected time energy output of electricity from the optimized system at an annual real interest rate of ten (10%) percent is GHȻ2.38/kW. For the PV system designed to reach “Grid Parity”, the levelized cost of energy is estimated to be GHȻ2.03/kW with an annual real interest rate of six (6%) percent.

Design the Balance of System (BOS) for Photovoltaic Application at CERE Building for Low Load Application: An Application of HOMER Pro

The reliable renewable energy systems will effective when the optimal output can be achieved. This paper presents a design of the BOS system at the CERE building for low load application. The entire system is being optimized by HOMER Pro software represented the effectiveness system. The HOMER Pro produced the optimal and economic hybrid system configuration. The result indicated the capacity of the PV array is 0.6 kW, 4 units of 1 kWh lead-acid battery and 0.3 kW of inverter was selected to complete the system. The impact of the ambient temperature also has been analysed. The total electrical energy production reduced with considering temperature coefficient. An optimization produced productive configuration over the system lifetime.