Energy Generation System Research Articles

A non-isolated converter of switching current stress in DC-DC converter for integrating PV and battery storage system

ABSTRACT High-gain DC-DC converters have seen significant adoption in renewable energy systems like Photovoltaic (PV), Fuel Cells (FC), and other systems. However, their effectiveness is increasingly tied to the availability of renewable resources. As Renewable Energy Sources (RES) typically generate electricity at low voltage levels, integrating high-gain DC-DC converters with RES is crucial for optimal performance. This paper introduces an innovative DC-DC converter design that achieves high gain and is specifically able to integrate smoothly with RES like PV systems and battery storage. The innovation of the proposed converter lies in its integration of conventional boost and buck-boost converters, enabling a high voltage gain while minimizing output voltage ripple and reducing switch current stress. Additionally, its unidirectional power transfer port allows efficient energy flow from solar PV or battery sources to the load, making it highly adaptable for managing fluctuating energy sources, a feature that distinguishes it from current modern converters. Its design simplifies architecture by combining traditional converter types, reducing the number of components, which leads to cost savings, lower weight, and improved reliability. Additionally, the design minimizes output voltage ripple and reduces switching current stress, enhancing the converter’s durability under variable operating conditions. The converter’s performance is evaluated through simulation and experimental studies, demonstrating a 96.3% efficiency and 5.5 times of voltage gain. The converter’s feasibility and effectiveness are validated under dynamic scenarios with varying solar irradiation, making it an ideal solution for clean energy generation systems, including hybrid energy generation setups. The proposed converter topology offers an auspicious solution for high-gain DC-DC conversion in renewable energy systems.

Integrated PV energy generation system with high-gain converter and CHHO-FLC-based MPPT for grid integration

Integrated PV energy generation system with high-gain converter and CHHO-FLC-based MPPT for grid integration

Design and simulation of a photovoltaic plant for maximum use of the solar resource in the Toluviejo municipality of Colombia

Currently, there are various technologies for constructing photovoltaic plants including monofacial and bifacial photovoltaic panels, centralized and string-type inverters, and fixed mounting structures with light followers, to build electrical energy generation systems. This work reviewed the advantages and disadvantages between these technologies, and the implementation of a photovoltaic plant in Toluviejo, Colombia was proposed. To justify and confirm the design, simulations were carried out with the PVsyst software, resulting in the bifacial panels, centralized inverters, and structures with light followers, the most effective solution, and with the highest production for the proposed photovoltaic power generation plant.

ENERGY MANAGEMENT IN HYBRID PV-WIND-BATTERY STORAGE-BASED MICROGRID USING DROOP CONTROL TECHNIQUE

The paper presents an efficient energy management system designed for a small-scale hybrid microgrid incorporating wind, solar, and battery-based energy generation systems using the droop control technique. The heart of the proposed system is the energy management system, which is responsible for maintaining power balance within the microgrid. The EMS continuously monitors variations in renewable energy generation and load demand and adjusts the operation of the energy conversion systems and battery storage to ensure optimal performance and reliability. The primary objective of the energy management system is to maintain power balance within the microgrid, even in the face of fluctuations in renewable energy generation and load demand. This involves dynamically adjusting the operation of the renewable energy sources and battery storage system to match the instantaneous power requirements of the microgrid. Overall, the paper presents a comprehensive approach to designing and implementing an efficient energy management system for a small-scale hybrid wind-solar-battery-based microgrid to extract maximum profit from electricity generation. By integrating renewable energy sources with energy storage and advanced control algorithms, the proposed system aims to enhance the reliability, stability, and sustainability of the microgrid's power supply.

Modeling and Simulation of an Integrated Synchronous Generator Connected to an Infinite Bus through a Transmission Line in Bond Graph

Most electrical energy generation systems are based on synchronous generators; as a result, their analysis always provides interesting findings, especially if an approach different to those traditionally studied is used. Therefore, an approach involving the modeling and simulation of a synchronous generator connected to an infinite bus through a transmission line in a bond graph is proposed. The behavior of the synchronous generator is analyzed in four case studies of the transmission line: (1) a symmetrical transmission line, where the resistance and inductance of the three phases (a,b,c) are equal, which determine resistances and inductances in coordinates (d,q,0) as individual decoupled elements; (2) a symmetrical transmission line for the resistances and for non-symmetrical inductances in coordinates (a,b,c) that result in resistances that are individual decoupled elements and in a field of inductances in coordinates (d,q,0); (3) a non-symmetrical transmission line for resistances and for symmetrical inductances in coordinates (a,b,c) that produce a field of resistances and inductances as individual elements decoupled in coordinates (d,q,0); and (4) a non-symmetrical transmission line for resistances and inductances in coordinates (a,b,c) that determine resistances and inductance fields in coordinates (d,q,0). A junction structure based on a bond graph model that allows for obtaining the mathematical model of this electrical system is proposed. Due to the characteristics of a bond graph, model reduction can be carried out directly and easily. Therefore, reduced bond graph models for the four transmission line case studies are proposed, where the transmission line is seen as if it were inside the synchronous generator. In order to demonstrate that the models obtained are correct, simulation results using the 20-Sim software are shown. The simulation results determine that for a symmetrical transmission line, currents in the generator in the d and q axes are −25.87 A and 0.1168 A, while in the case of a non-symmetrical transmission line, these currents are −26.14 A and 0.0211 A, showing that for these current magnitudes, the generator is little affected due to the parameters of the generator and the line. However, for a high degree of non-symmetry of the resistances in phases a, b and c, it causes the generator to reach an unstable condition, which is shown in the last simulation of the paper.

Decommissioning of a fuel oil-fired thermoelectric power plant in Brazil - Economic feasibility under certain and risk conditions

The strategic analysis for the decommissioning of thermoelectric plants is seen as a trend for the coming years. The search for renewable alternatives should stimulate investment in other energy sources, reducing the number of thermoelectric plants in the energy generation system. However, few studies have dealt with the decommissioning of oil-fired thermoelectric plants. In this work, the methodology was applied under deterministic and stochastic conditions using methods of net present value (NPV), internal rate of return (IRR), discounted payback, capital asset pricing model (CAPM) and weighted average cost of capital (WACC). The results showed that the deterministic NPV was positive, ranging from R$101.30 million (pessimistic scenario) to R$109.73 million (optimistic scenario). The IRR was higher than the WACC of 10.55 %, ranging from 13.50 % to 13.68 % per year. For the Monte Carlo simulation, NPV was observed with 100 % certainty of viability and the probabilities of occurrence allowed more analysis of the risks involved than those obtained by deterministic methods. this study contributes to future decommissioning projects in Brazil, considering the scenario of stimulating renewable sources and the energy transition, helping managers make decisions about their projects. In addition, it helps guide public policies that can optimize the decommissioning process and strengthen the national energy sector.

A nanofluidic chemoelectrical generator with enhanced energy harvesting by ion-electron Coulomb drag

A sufficiently high current output of nano energy harvesting devices is highly desired in practical applications, while still a challenge. Theoretical evidence has demonstrated that Coulomb drag based on the ion-electron coupling interaction, can amplify current in nanofluidic energy generation systems, resulting in enhanced energy harvesting. However, experimental validation of this concept is still lacking. Here we develop a nanofluidic chemoelectrical generator (NCEG) consisting of a carbon nanotube membrane (CNTM) sandwiched between metal electrodes, in which spontaneous redox reactions between the metal and oxygen in electrolyte solution enable the movement of ions within the carbon nanotubes. Through Coulomb drag effect between moving ions in these nanotubes and electrons within the CNTM, an amplificated current of 1.2 mA cm−2 is generated, which is 16 times higher than that collected without a CNTM. Meanwhile, one single NCEG unit can produce a high voltage of ~0.8 V and exhibit a linear scalable performance up to tens of volts. Different from the other Coulomb drag systems that need additional energy input, the NCEG with enhanced energy harvesting realizes the ion-electron coupling by its own redox reactions potential, which provides a possibility to drive multiple electronic devices for practical applications.

Combining energy generation and radiant systems: Challenges and possibilities for plus energy buildings

Radiant heating and cooling (RHC) systems are being more widely adopted considering the well-known technical advantages: increased thermal comfort, space saving, and reduced energy use. Since the building sector is currently one of the largest consumers of fossil fuels, many directives and regulations have been enacted to address the intense concern about energy use for space conditioning.Even though radiant systems are considered as an energy efficient technology for building heating and cooling, more effort is needed to fulfil the zero energy requirements outlined by recent standards and directives. Renewable Energy Sources (RES) are an effective solution to avoid using finite fossil fuels and related geopolitical issues enhanced by the recent world conflicts. Despite being primarily intermittent and subject to economic and regional constraints, RES offer suitable temperature levels to supply low temperature heating and high temperature cooling operation, a major advantage of RHC system.Although a limited number of studies directly report energy savings or CO2 emission reduction as the main outcomes of the research related to this combination, valuable insights have been obtained for the present review. Primary energy can decrease between 40% and 80% with different integration of RHC, photovoltaic, heat pumps and district heating. TABS can lead to load shifting up to 100%, allowing an increased self −consumption of renewable energy.This paper provides evidence on whether coupling radiant systems with renewables is a promising strategy for achieving nearly-zero annual energy balances in building stocks. It investigates recent trends, limitations and potential to support decarbonization goals.

Optimal cost predictive BMS considering greywater recycling, responsive HVAC, and energy storage

A crucial aspect of a sustainable city is ensuring that energy and water supplies can adequately meet urban demand. With the scarcity of natural resources and growing electricity and water demand, it becomes increasingly important for consumers to manage their resource usage more efficiently. This paper proposes a novel perspective of demand-side management coordination strategy for a building's water-energy nexus to enhance the resilience and efficiency of the overall electricity-water-heating system. The model is formulated to optimally coordinates the onsite greywater recycling system, heating, ventilation, air conditioning (HVAC) loads, and distributed energy generation systems with a bidirectional grid connection in a residential building. All subsystems are controlled by a model predictive controller (MPC) receiving real-time time of use (ToU) pricing from electricity and water utilities. The presented mixed integer linear programming model is verified to meet the customers' demands while reducing the operational costs. Results are compared with benchmark systems lacking the water recycling or energy storage system showing 8.3 % operational cost reduction while reducing potable water consumption by 21.5 %. The effect of increased MPC control horizon is also studied showing reduction in cost with increased horizon. Detailed analysis of the proposed framework computational burden and effect of prediction errors is performed to prove the MPC adaptability and robustness. Testing under increased room size and different user preferences further validate the efficacy of the proposed scheme in reducing the operational costs.

Integrated batch production planning and scheduling with machine-learning based production capacity region considering wind energy system

Continued greenhouse gas emission has led to increased global warming. Towards the goal of carbon emissions reduction and environmental sustainability, replacing high-polluting fossil fuel by clean energy has become a top priority in the decision-making of the current chemical industry. This work presents an optimization framework to address the integration of batch chemical production planning and scheduling considering energy consumption, which is a vital operational problem in chemical production. Assisting the linkage between planning layer and scheduling layer, a novel linear support vector machine based production capacity region calculation method is proposed to identify feasible regions of the scheduling layer. Uncertain factors in both the production system and the energy system are considered, including demand volatility of chemical products, energy supply fluctuations and time-varying energy market prices. To evaluate each strategy and the proposed model, simulation experiments are performed in three representative case studies. The results reveal that the integrated model considering energy consumption shows superior performance in different energy configurations, with or without wind energy generation and battery storage systems.

Green mediated sol-gel synthesis of MxCu1-xO (M = La,Ce x = 0.02–0.06) as an efficient catalyst for electrocatalytic oxygen evolution reaction

The imperative for advancing contemporary human society lies in the essential requirement to create energy generation systems that are sustainable, environmentally friendly, and exceptionally efficient. The development of efficient electrocatalysts, that are environmentally benign, economically viable and easily available, for alkaline oxygen evolution reaction is a significant research area in this regard. The present study focuses on a green mediated sol–gel auto-combustion process for the synthesis of lanthanum and cerium doped copper oxide nanoparticles with excellent electrocatalytic activity. Citric acid and polyols enriched lemon juice serves as the medium for the synthesis of various metal doped copper oxide nanoparticles. The extensive electrochemical studies using these catalysts reveals that, among the various doped samples, 5% lanthanum and 5% cerium doped catalysts exhibited the best performance in oxygen evolution reaction. Doping was found to enhance electrical conductivity and create oxygen vacancies, which enhanced the electrocatalytic activity of the catalysts. Specifically, the 5% lanthanum-doped copper oxide showed an overpotential of 340 mV, while the cerium-doped material exhibited an overpotential of 337 mV at a current density of 10 mA cm−2 in 1 M KOH. Moreover, the lanthanum-doped sample displayed a Tafel slope of 49 mV dec−1, whereas the cerium-doped sample had a Tafel slope of 60 mV dec−1 with better durability. Additionally, the chronopotentiometric studies revels the stability and long-term performance of LCO5 and CCO5, maintaining consistent potential of 1.58 V throughout 5 h at a current density of 10 mA cm−2. This study is conclusive evidence that the incorporation of rare earth elements improves the conductivity and overpotential of pristine copper oxide nanoparticles, making them highly effective in the oxygen evolution reactions.

Automated monitoring of natural parameters of renewable energy production systems

The paper discusses the urgent issues of the need to automate the monitoring of natural parameters of renewable energy production systems. Monitoring involves the collec- tion and analysis of various parameters of the natural environment that affect the efficiency and environmental friendliness of systems powered by renewable energy. Based on analytical materials and practical work related to techno-economic and ecological studies concerning the assessment of water reserves in indi- vidual wells, the study focused on the development of technologies and technical means for monitoring. It was found that, in practice, hydrogeological research on groundwaters use outdated methods and technical means for measuring and storing data. A local automated system for monitoring well parameters was developed and constructed. It ensures the operation of the hydrothermal heat pump system at the experimental site of the Institute of Renewable Energy of the National Academy of Sciences of Ukraine. This system was tested in our research. The benefits of this study are revealing the need to create an intelligent monitoring system with the possibility of automated decision-making regarding the management of renewable energy generation systems, depending on changes in the am- bient parameters. A network automated system for monitoring natural parameters was developed, consisting of several wireless sensor subsystems that communicate with each other via wireless connection and transmit information to the gateway. The gateway, in turn, is connected to the computer with a graphical interface for interaction with the system. The results of work indicate that the proposed structures for automated water monitoring are simple and easy to implement. Consequently, the study revealed that one of the prospects is the development of automated monitoring systems with intelligent features, capable of making optimal individual decisions regard- ing the management of renewable energy generation systems under variable environmental parameters. As a result, the data obtained from this study have significant scientific and practical implications for advancing the design methodology of geothermal heat pump wells, focusing on long-term forecasts and assessments of their ecological and economic efficiency.

Regulation of extracellular electron transfer by sustained existence of Fe²⁺/Fe³⁺ redox couples on iron oxide-functionalized woody biochar anode surfaces in bioelectrochemical systems

Sluggish extracellular electron transfer between the exoelectrogens and anode interface limits the application of bioelectrochemical systems (BECs) for energy generation. In this study, an innovative anode coated with oxidized biochar and co-functionalized with iron nanoparticles (FBC/Fe2O3) was developed to enhance microbial reactions through tuned physicochemical and electrical properties. The designed anode features a highly porous, heterogeneous structure with a large accessible surface area of 10.141 m²/g, promoting better habitation and metabolism of exoelectrogens. The synergistic effect of iron nanoparticles and oxidized functional groups increased the hydrophilicity of the anode surface, augmenting its affinity for bacterial outer membrane c-cysts and facilitating microbial adhesion at a density of 3.106 × 10⁹ CFU/cm². The iron moieties on the FBC/Fe2O3 electrode surface act as electron mediators, utilizing Fe²⁺/Fe³⁺ redox couples, as evidenced by X-ray photoelectron spectroscopy (XPS) data. This enhancement improved extracellular electron transfer (EET) between bacterial cells and the anode surface, resulting in a faster and bifurcated EET process through both direct transfer via outer membrane c-cysts and mediated transfer via the redox couples of Fe moieties. The assembled double-chamber microbial fuel cell (DC-MFC) with the FBC/Fe2O3 anode achieved a maximum power density of 528.75 mW/m² and a chemical oxygen demand (COD) removal efficiency of 47.5 % within 24 h of operation.

Switch Capacitor–Based High Step‐Up Three‐Port DC–DC Converter for Fuel Cell/Battery Integration

ABSTRACTAddressing issues of low input voltage in new energy generation systems such as fuel cells, a high step‐up three‐port DC–DC converter for fuel cell/battery hybrid power supply system is proposed. The proposed converter is evolved from Boost three‐port converter, and switch capacitor structure and diode capacitor voltage doubling unit are employed to achieve high voltage gain and low voltage stress. The three ports are connected to fuel cell, battery and load respectively, among which the flow of energy is realized. The steady state performance of this converter in various operating states and design of parameter are presented. Primary competitive advantages compared to similar converters include high voltage gain, continuous input current and its feature of common ground. Moreover, control strategy and compensators under three operating modes are designed to achieve stable output voltage and battery protection. Finally, a 100 W experimental prototype with 15 V input voltage and 24 V battery voltage is established to verify the stable and dynamic performance of the proposed converter.

Optimal design of hybrid green energy powered reduced switch converter based shunt active power filter using horse herd algorithm

Renewable energy sources are playing a leading role in today's world. However, integrating these sources into the distribution network through power electronic devices can lead to power quality (PQ) challenges. This work addresses PQ issues by utilizing a shunt active power filter in combination with an Energy Storage System (ESS), a Wind Energy Generation System (WEGS), and a Solar Energy System. While most previous research has relied on complex methods like the synchronous reference frame (SRF) and active-reactive power (pq) approaches, this work proposes a simplified approach by using a neural network (NN) for generating reference signals, along with the design of a five-level reduced switch voltage source converter. The gain values of the proportional-integral controller (PIC), as well as the parameters for the shunt filter, boost, and buck-boost converters in the WEGS and ESS, are optimally selected using the horse herd optimization algorithm. Additionally, the weights and biases for the neural network (NN) are also determined using this method. The proposed system aims to achieve three key objectives: (1) stabilizing the voltage across the DC bus capacitor; (2) reducing total harmonic distortion (THD) and improving the power factor; and (3) ensuring superior performance under varying demand and PV irradiation conditions. The system's effectiveness is evaluated through three different testing scenarios, with results compared against those obtained using the genetic algorithm, biogeography-based optimization (BBO), as well as conventional SRF and pq methods with PIC. The results clearly demonstrate that the proposed method achieves THD values of 3.69%, 3.76%, and 4.0%, which are lower than those of the other techniques and well within IEEE standards. The method was developed using MATLAB/Simulink version 2022b.

Investigating the Structural and Power Performance of a 15 MW Class Wind Energy Generation System under Experimental Wind and Marine Loading

The global transition to renewables in response to climate change has largely been supported by the expansion of wind power capacity and improvements in turbine technology. This is being made possible mainly due to improvements in the design of highly efficient turbines exceeding a 10 MW rated power. Apart from power efficiency, wind turbines must withstand the mechanical stress caused by wind–hydro conditions. Such comprehensive structural analysis has rarely been performed previously, especially for large-scale wind turbines under real environmental conditions. The present work analyzes the energy production and structural performance of an NREL-IEA 15 MW wind turbine using measured wind and hydro data. First of all, an optimum operating range is determined in terms of the wind speed and blade pitch angle to maximize the power coefficient. Then, at this optimum range, a detailed breakdown of the forces and moments acting on different components of the wind turbine is presented. It was found that wind speeds of 9 to 12 m/s are best suited for this wind turbine, as the power coefficient is at its maximum and the mechanical loads on all components are at a minimum. The loads are at a minimum due to the optimized blade pitch angle. The bending force on a monopile foundation (fixed on the seabed) is found to be at a maximum and corresponds to nearly 2000 kN. The maximum blade force is nearly 700 kN, whereas on the tower it is almost 250 kN. The maximum force on the tower occurs at a point which is found to be undersea, whereas above-sea, the maximum force on the tower is nearly 20% less than the undersea maximum force. Finally, seasonal and annual energy production is also estimated using locally measured wind conditions.

Nonlinear Enhanced Control for Wind Energy Generation System-Based Permanent Magnet Synchronous Generator

This paper proposes a Nonlinear Backstepping Approach (NBA) to improve the control performance of a Permanent Magnet Synchronous Generator (PMSG)-based Wind Energy Generation System (WEGS) under parameter uncertainties and short circuits with fluctuations in the grid voltage. Both the rectifier and the three-phase inverter are controlled using the NBA scheme; this method ensures Maximum Power Point Tracking (MPPT), which is a very appealing control objective with unpredictable scenarios of wind speed, and regulates the active and reactive power flows to the electrical network under varying wind speeds. Also, an inverter was employed to control voltage of the DC bus and the powers. The regulator’s stability is achieving using the Lyapunov approach. Simulation results with Matlab/Simulink confirm the efficiency of the presented scheme. The comparative analysis of the NBA with conventional Vector Controllers (VCs), under parameter deviations and for low voltage drop conditions, demonstrates the efficiency of the studied method.

Toward sustainable energy resource: Integrated concentrated photovoltaic and membrane distillation systems for fresh water and electricity production

This study introduces and evaluates a novel Concentrated Photovoltaic (CPV)-assisted Direct Contact Membrane Distillation (DCMD) system, examining its efficiency and energy output under varying operational conditions. A Computational Fluid Dynamics (CFD) model, validated with experimental data, assesses the system's performance at different concentration ratios ranging from 1x to 10x and 25x to 100x, flow patterns (counterflow and parallel flow) at different Reynolds numbers (30–1200). This study investigates the seasonal performance of the CPV-DCMD system, providing valuable insights into its reliability and sustainability throughout the year. Results show increased mass flux and electric power with higher concentration ratios, especially at lower Reynolds numbers. In the counter-flow arrangement, the mass flux increases notably under specific conditions, while seasonal analysis reveals peak flux during summer and autumn afternoons. Electric power output follows a consistent trend across seasons, with high output observed during noon hours. The study demonstrates the system's energy efficiency, with notable energy gain compared to consumption across diverse operational conditions. Overall, the findings provide insights into optimizing the performance of CPV-assisted DCMD systems for sustainable energy generation and water desalination applications.

A new hybrid fixed and adaptive gains control algorithm to reduce power losses on LLCL filter-based renewable energy conversion systems with systematic parametrization using Grey Wolf optimizer

Currently, there is a transition in the energy matrix around the world, where traditional sources of energy generation are continually being replaced by energy generation systems based on renewable sources to mitigate the climate crisis. In this bias, this work presents the mathematical modeling of an LLCL filter, used to connect power generation systems based on renewable energy sources to the electrical grid, and presents a novel hybrid fixed-and adaptive gains control strategy for current injection into the grid using this system. The developed hybrid controller is composed of a proportional–integral controller and a direct robust adaptive controller. The first term of the controller guarantees the reference current, while the second term of the controller is used for disturbance rejection. Furthermore, a systematic procedure for the controller’s parametrization based on Grey Wolf Optimizer is also provided. The control of the current injected into the grid is carried out considering the LLCL filter without passive damping resistors in the filter structure to avoid power losses due to the passive filter elements. Additionally, the LLCL filter model considers minimal parasitic resistances to evaluate the controller’s performance and optimize it for the application of interest, aiming to maximize the system performance by ensuring a short transient regime due to the fast closed-loop system response. Simulation results indicate high performance of this optimized control strategy with small tracking error even considering grid impedance variations.

Machine learning discovery of cost-efficient dry cooler designs for concentrated solar power plants

Concentrated solar power (CSP) is one of the few sustainable energy technologies that offers day-to-night energy storage. Recent development of the supercritical carbon dioxide (sCO2) Brayton cycle has made CSP a potentially cost-competitive energy source. However, as CSP plants are most efficient in desert regions, where there is high solar irradiance and low land cost, careful design of a dry cooling system is crucial to make CSP practical. In this work, we present a machine learning system to optimize the factory design and configuration of a dry cooling system for an sCO2 Brayton cycle CSP plant. For this, we develop a physics-based simulation of the cooling properties of an air-cooled heat exchanger. The simulator is able to construct a dry cooling system satisfying a wide variety of power cycle requirements (e.g., 10–100 MW) for any surface air temperature. Using this simulator, we leverage recent results in high-dimensional Bayesian optimization to optimize dry cooler designs that minimize lifetime cost for a given location, reducing this cost by 67% compared to recently proposed designs. Our simulation and optimization framework can increase the development pace of economically-viable sustainable energy generation systems.