Renewable Power Generation Systems Research Articles

Design of low‐stress ultrahigh‐gain dc–dc converter with coupled inductor

AbstractThe dc–dc converter plays a vital role in renewable energy power generation systems. To enhance the boost range and supply stable output voltage for the power grid, This paper propose an improved low‐stress ultrahigh‐gain dc–dc converter. First, a voltage multiplier cell is designed stemming from a three‐winding coupled inductor and a switched capacitor (SC), which can obtain ultrahigh voltage gain. In the improved voltage multiplier cell, the number of semiconductor devices is reduced, resulting in a decrease in capacitor voltage stress. Moreover, a passive clamp circuit uses the new SC, which can suppress oscillation peak voltage and absorb the leakage energy of the coupled winding. Furthermore, we deduce the operating mode of the proposed converter . Compared with other advanced topologies, the proposed topology outperforms boosting capacity, component stress, and efficiency. To stabilize the output voltage, the converter is closed‐loop controlled. Finally, experiments on the 180 W prototype have demonstrated the reliability and effectiveness of the proposed topology.

A Series Impedance Reshaping Control Method Considering PLL Dynamics for Grid-Connected Inverters Under Weak Grid Conditions

Grid-connected inverters are the key part in renewable energy power generation systems. Usually, phase-locked loop (PLL) is adopted in grid-connected inverters to achieve synchronization. However, prior-art works have revealed that the negative resistance behavior in the low-frequency band caused by PLLs may lead to system instability under weak grids. In this paper, first, a comprehensive small-signal output impedance modeling of the LCL-filtered single-phase grid-connected inverter is derived for stability analysis, where the digital control delays and PLL dynamics have been taken into account. Then, a simple but effective virtual series based impedance reshaping method is proposed. With that, the inverter system can operate stably even under a very weak grid (e.g., short-circuit ratio (SCR) is as low as 1.2). Compared with the traditional grid impedance compensation by virtually increasing grid resistance or reducing the grid inductance, the proposed method does not require grid impedance estimation and is robust against system parameter variations. Thus, its feasibility is improved. Finally, experimental tests are carried out on a single-phase 5-kW prototype, validating the effectiveness of the proposed scheme.

How do seasonal and technical factors affect generation efficiency of photovoltaic power plants?

Regions with limited space for constructing renewable power generation systems need to maximize electricity generation by optimizing the operational efficiency of existing plants and selecting an optimal location for the new construction of PV power plants with favorable weather conditions and surrounding environment. Utilizing monthly input and output data, including four inputs (solar irradiation, temperature, number of modules, and photovoltaic (PV) array rated capacity) and one output (electricity generation) from utility-scale PV power plants, meta-frontier data envelopment analysis was employed in this study to identify factors contributing to power generation inefficiency. Additionally, a Monte Carlo experiment analyzed the impact of solar irradiation uncertainty on power generation efficiency. The findings revealed that the average power generation inefficiency during the study period was 0.445, primarily attributable to seasonal and technical factors. Since these factors are difficult to control once a power plant is in operation, it is important to select an optimal site for power plants by considering meteorological and geographical data. Moreover, the results indicated a significant gap between observed and simulated values of power generation efficiency, arising from variations in weather conditions, power plant site area, and the data used in the research. Employing PV modules with higher electricity output levels can boost the DC/AC ratio, thereby increasing power generation, enhancing efficiency, and contributing to a stable power supply, thus reducing daily and seasonal fluctuations in power generation.

A smart parametrisation for robust adaptive PI controller applied on renewable energy power generation systems under weak and uttermost weak grid conditions

The increasing penetration of renewable energy systems into the global energy matrix is a necessity for sustainable development. The benefits impact the well-being of humanity and the environment directly. However, these power generation systems demand reliable controllers to regulate the current injection into the electrical grid. Therefore, this paper presents a smart parametrisation for a robust adaptive proportional integral controller applied to grid-injected current control of a voltage inverter source with an LCL filter. Controller parameter optimisation and the initialisation of their gains are performed using the particle swarm optimisation algorithm. Three cost functions are assessed on controller parametrisation, considering the current tracking error minimisation and control action limitations: integral of absolute error (IAE) + integral of absolute control action (IAU), integral of square error (ISE) + IAU, and integral of the time-weighted absolute error (ITAE) + IAU. A framework for performance analysis and an in-depth discussion are presented, providing a systematic decision-support methodology for controller configuration. The function determined as the best one is implemented experimentally and compared with a designer’s experience-based robust adaptive proportional integral controller using a hardware-in-the-loop test bench, where the improvements in controller performance are corroborated, contributing to the enhancement of energy quality in renewable energy systems. In addition, the controller’s robustness is evaluated on a weak grid and an uttermost weak grid, where it presents high robustness and global stability.

Techno-economic analysis of hybrid renewable power generation system under different climatic zones in India

Techno-economic analysis of hybrid renewable power generation system under different climatic zones in India

Assessment of renewable power generation applied in homestay hotels: Energy and cost-benefit considering dynamic occupancy rates and reservation prices

Increasing the revenue from hotel operations and decreasing the stress on utility grids from hotel energy consumption are two priorities for the modern tourism industry. Dynamic occupancy rate and hotel reservation prices influence their operations revenue, while occupancy rate also impacts real hotel energy consumption. Renewable power generation as an effective measure can benefit hotels not only by decreasing electricity purchases but also increasing some extra income from selling electricity generated from renewable sources. This study investigated the effects of renewable power generation on energy and the cost-benefit performance of hotel operation prices under different occupancy rates and reservation prices. A two-stage energy and cost-benefit performance assessment and a novel comprehensive cost-benefit assessment model were developed to examine these research issues. The impact of the renewable power generation system (i.e., a photovoltaic-battery system installed on the building rooftop) was considered on the hotel energy and cost-benefit performance. It was found that the novel cost-benefit assessment model accurately quantified the overall hotel profit by calculating its energy consumption cost with the PV-battery system under different occupancy rates and reservation prices. Three typical homestay hotels located in Sanya were tested and assessed. The results showed that PV-battery systems effectively decreased the amount of electricity purchased by hotels. Besides, the renewable energy penetration was above 57.98% in various cases. The overall hotel profit increased by a maximum of 31.4% since renewable power generation was used under different occupancy rates and hotel reservation prices.

Simulation of Small-Scale Solar Power Generation System in The Central Java Region: A Case Study of the Cilacap Area

The limitations of conventional non-renewable energy resources raise concerns about sustainability and energy supply security in the future. One of the worrying factors is the carbon dioxide emissions that can affect living organisms' health. Renewable energy sources, such as solar, wind, and hydropower, emerge as solutions capable of minimizing environmental impacts and reducing dependence on limited resources. Therefore, this research will simulate and design a small-scale renewable energy power generation system, particularly solar energy, in the Cilacap region, Central Java. The main components involved in this research include PV arrays, IGBT diodes, and universal bridges, supported by supporting elements such as displays, scopes, resistors, capacitors, inductors, and bus selectors. The technical data used as input are specific to the area. The simulation results show that the direct power generated by one modelled PV array is 221.7 W per hour. This research contributes to optimising small-scale solar power generation systems in the designated area, considering relevant components and parameters to enhance efficiency and sustainability.

Transient synchronization stability of the island 100 % renewable power generation system connected to Zhangbei MTDC network

This paper examines the transient synchronization stability (TSS) of an island 100 % renewable power generation (RPG) system that is connected to the Zhangbei multi-terminal direct current (MTDC) system. A large-signal model of the system is derived, based on which an analytical criterion for evaluating the TSS of the system is proposed. From the proposed TSS criterion, the current injection of the RPG, the current injection of the MMC, the parameter settings of the PLL, and the fault ground resistance and distance are identified and examined as four key factors affecting the system TSS. In addition, analysis in the paper highlights the importance considering the reactive current generated by the RPG during the fault, because excessive reactive current may causes the instability of the island 100 % RPG system. To demonstrate and evaluate the proposed TSS criterion and the analytical conclusions made, study cases to examine the TSS of the island 100 % RPG system connected to the Zhangbei MTDC are presented in the paper.

A predictive tool for power system operators to ensure frequency stability for power grids with renewable energy integration

The increased penetration levels of renewable energy resources (RESs) transform the power generation schema into one that is more susceptible to changes due to weather conditions, complicated load profiles, and reduced inertia levels. One of the main challenges that power grids can encounter under varying and low system inertia (SI) is poor frequency response (FR). Therefore, this paper proposes a novel online tool for assessing, predicting, and enhancing the frequency stability (FS) of power systems with renewable power generation and energy storage systems (ESS). Firstly, the tool provides accurate tracking of the SI in real-time settings using recursive least square identification and Kalman filtering to provide accurate and computationally efficient results. Secondly, the tool estimates the FR of the whole system in a virtual environment for different contingencies and inertia levels. The accuracy of the FR is improved by classifying the frequency response models (FRMs) based on the SI levels. Lastly, the proposed tool computes the optimal additional estimated reserve power (ERP) required from PV and battery energy storage systems (BESS) to provide inertial and primary frequency support to the power grid at the onset of a contingency. In addition, a reserve power allocation and load-shedding strategies are proposed and implemented to dynamically adjust the reserve power of PV power plants. This dynamic control of the PV power plant reserve capacity guarantees the availability of adequate reserves for addressing unforeseen systems contingencies. Moreover, dedicated FR controllers for PV and BESS are employed to emulate the synchronous machine’s inertial response (IR) and primary frequency control (PFC). The performance of the proposed tool and the FR controllers are tested and validated on a generic power grid and the IEEE 39 bus system using MATLAB Simulink and the OPAL-RT real-time simulation software.

AMCC-Based Power Management Scheme With Full Ancillary Services Support for a Wind–Solar Renewable Power Generation System

This paper introduces a power management scheme (PMS) for an integrated wind-solar renewable power generation system (RPGS). The PMS takes advantage of time of use electricity pricing mechanism to manage the net power exchange between the grid and the RPGS. A battery energy storage (BES) is utilized for enabling the system price arbitrage functionality. Meanwhile, the system control is performed through a novel application of the adaptive kernel width maximum correntropy criterion (AMCC) strategy. Apart from utilizing the electricity price volatility to maximize returns, the RPGS is also equipped to offer ancillary services support to the utility grid in the form of, (i) grid reactive current injection considering system constraints and (ii) grid power quality conditioning through local compensation of load reactive power, harmonics and unbalance. Moreover, for reduced system losses and minimized ripples in the grid currents amidst variations in grid voltages, a self-adjustable DC voltage reference technique is accommodated in the control strategy. An RPGS, employing a solar photovoltaic array and a doubly-fed induction generator for wind power generation, is utilized to experimentally demonstrate the effective operation of the overall control strategy.

Thermodynamic modelling and optimisation of a green hydrogen-blended syngas-fueled integrated PV-SOFC system

Developing an effective energy transition roadmap is crucial in the face of global commitments to achieve net zero emissions. While renewable power generation systems are expanding, challenges such as curtailments and grid constraints can lead to energy loss. To address this, surplus electricity can be converted into green hydrogen, serving as a key component in the energy transition. This research explores the use of renewable solar energy for powering a proton exchange membrane electrolyser to produce green hydrogen, while a downdraft gasifier fed by municipal solid waste generates hydrogen-enriched syngas. The blended fuel is then used to feed a Solid Oxide Fuel Cell (SOFC) system. The study investigates the impact of hydrogen content on the performance of the fuel cell-based power plant from thermodynamics and exergoeconomic perspectives. Multiobjective optimisation using a genetic algorithm identifies optimal operating conditions for the system. Results show that blending hydrogen with syngas increases combined heat and power efficiency by up to 3%, but also raises remarkably the unit product cost and reduces carbon dioxide emissions. Therefore, the optimal values for hydrogen content, current density, temperatures, and other parameters are determined. These findings contribute to the design and operation of an efficient and sustainable energy generation system.

Sustainability assessment of renewable power generation systems for scale enactment in off-grid communities

Sustainable Energy for All (SE4ALL), a United Nations initiative, recognizes the significance of renewable energy systems (RES) in meeting the energy needs of off-grid communities. In Pakistan, the rural population faces challenges in accessing reliable electricity, necessitating the exploration of alternative electrification methods. While previous studies have focused on single-user systems, no single RES fully meets all sustainability criteria. Moreover, the impacts of scaled RES differ significantly from those of single systems, encompassing technological, environmental, social, and economic aspects. This study assessed the sustainability of scaled RES for electrifying off-grid communities using Multi-Criteria Decision Analysis (MCDA) based on the Analytical Hierarchy Process (AHP). The assessment framework considered social, technical, environmental, and economic factors as key dimensions of sustainability. Pairwise comparison matrices were employed to determine priority vectors and weighted averages of indicators for fourteen sub-criteria. The results revealed that solar PV (29.82%) emerged as the most sustainable RES for scaled electrification in selected off-grid regions, followed by solar-thermal (26.79%), wind (23.86%), and biomass energy (19.53%). Each alternative has strengths in different categories, with solar-PV excelling in the environmental (42.30%), biomass in the social (36.18%), solar-thermal in the technical (41.53%), and wind energy in the economic category (39.40%). These findings provide valuable insights for implementers and policymakers seeking sustainable electrification solutions for off-grid communities. They emphasize the importance of aligning RES with the unique needs and goals and advocates for the widespread adoption of solar PV systems as a reliable source of electrification foroff-gridareas.

Optimum Design of an Electric Vehicle Charging Station Using a Renewable Power Generation System in South Korea

In the context of global warming and fossil fuel depletion, electric vehicles (EVs) have become increasingly popular for reducing both carbon emissions and fossil fuel consumption. However, as the demand for EV charging power rises along with the expansion of EVs, conventional power plants require more fuel, and carbon emissions increase. This suggests that the goal of promoting EV adoption to mitigate climate change and reduce reliance on fossil fuels may face significant challenges. Therefore, there is a need to adopt renewable energy generation for EV charging stations to maximize the effectiveness of EV distribution in an eco-friendly way. This paper aims to propose an optimal renewable energy generation system for an EV charging station, with a specific focus on the use of an actual load profile for the station, the consideration of carbon emissions and economic evaluation, and the study of a specific case location in Korea. As a case study, an EV charging station in Korea was selected, and its renewable energy fractions (REF) of 0%, 25%, 50%, 75%, and 100% were considered for comparison of carbon emissions and economic evaluation with the help of HOMER software. In addition, the system with 25% REF was analyzed to find the best operating strategy considering the climate characteristics of the case site. The results show that the system configuration of PV/ESS is the most economical among all the REF cases, including PV, WT, and ESS, due to the meteorological characteristics of the site, and that the system with REF below 25% is the most optimal in economic terms and carbon emissions.

Development and optimization of non-geothermal and geothermal-based electricity generation systems in regard to their environmental performance

In the third millennium, developing nations face the most pressing challenges involving climate change, fossil fuel scarcity, ozone depletion, global warming, and the production of greenhouse gases. To mitigate these challenges, renewable energy-driven power generation systems are of paramount importance. Present paper aims at proposal of two novel configurations for clean electricity generation with high-efficiency. The first system (standard system) is composed of an OFWH-assisted steam Rankine cycle and a gas turbine cycle which is driven solely by biomass energy. On the other hand, the second system (hybrid system) uses biomass and geothermal energy to drive the system, where the geothermal energy heats the water entering the OFWH and augments the power generation. Detailed analyses and comparisons between two systems are conducted using thermodynamics and exergoenvironmental methods. After completing the parametric analysis, a Pareto front is obtained for highest efficiency and lowest exergoenvironmental index (EEI). A notable finding of the parametric study is that the hybrid system is less energy efficient than the standard system, however it has higher exergetic efficiency and lower negative impacts on environment. Furthermore, increasing the pressure ratio of the air compressor leads to a consistently increasing EEI, while output electricity and exergy and energy efficiencies show an increasing-decreasing trend. Based on the bi-objective optimization, the gasifier with 3569 kW is the most exergy destructive component of the system in the base case and optimal case. Finally, the optimum values are obtained as 0.4734 and 42.63% for the EEI and exergy efficiency, respectively.

An optimal initialisation for robust model reference adaptive PI controller for grid-tied power systems under unbalanced grid conditions

This paper presents an Optimal Robust Model Reference Adaptive Proportional–Integral controller for grid-tied power systems, which is automatically parametrised using a Genetic Algorithm. The task of choosing the adaptation rate and the controller’s initial gains set is now performed in a computational and automatic way, saving design time and ensuring satisfactory transient regimes.The use of a Genetic Algorithm for complete parametrisation of robust adaptive controllers applied to renewable energy power generation systems with LCL filter is first here explored. Five cost functions are considered in the optimisation process. A comparison of simulation results applying the optimised controller in a grid-tied Voltage Source Inverter with LCL filter points out the benefits and drawbacks of using each cost function. A framework for performance analysis and an in-depth discussion are provided. The function determined as the best one, which is integral of absolute error, is used in the controller implemented experimentally, ensuring suitable tracking of grid current references and rejection of grid voltage harmonics, even under unbalanced grid voltage conditions. An experimental comparison in a three-phase 6.75 kW power converter with the non-optimised controller is also provided, where the optimised controller obtains a reduction in the overshoot in all transient regimes and smaller tracking error, resulting in a reduction in the mean error of 14.31% and 60.30% in α and β coordinates, respectively. In addition, the optimised controller reduces total harmonic content, improving energy quality. This parametrisation procedure can be immediately extended to the control of any other power converter systems.

Advanced Fault-Detection Technique for DC-Link Aluminum Electrolytic Capacitors Based on a Random Forest Classifier

In recent years, significant technological advances have emerged in renewable power generation systems (RPGS), making them more economical and competitive. On the other hand, for the RPGS to achieve the highest level of performance possible, it is important to ensure the healthy operation of their main building blocks. Power electronic converters (PEC), which are one of the main building blocks of RPGS, have some vulnerable components, such as capacitors, which are responsible for more than a quarter of the failures in these converters. Therefore, it is of paramount importance that the design of fault diagnosis techniques (FDT) assess the capacitor’s state of health so that it is possible to implement predictive and preventive maintenance plans in order to reduce unexpected stoppage of these systems. One of the most commonly used capacitors in power converters is the aluminum electrolytic capacitor (AEC) whose aging manifests itself through an increase in its equivalent series resistance (ESR). Several advanced intelligent techniques have been proposed for assessing AEC health status, many of which require the use of a current sensor in the capacitor branch. However, the introduction of a current sensor in the capacitor branch imposes practical restrictions; in addition, it introduces unwanted resistive and inductive effects. This paper presents an FDT based on the random forest classifier (RFC), which triggers an alert mechanism when the DC-link AEC reaches its ESR threshold value. The great advantage of the proposed solution is that it is non-invasive; therefore, it is not necessary to introduce any sensor inside the converter. The validation of the proposed FDT will be carried out using several computer simulations carried out in Matlab/Simulink.

Optimal energy management strategy for distributed renewable energy power generation system based on “three-flow” theory

Aiming at the off-grid application of distributed renewable energy, this study proposes a combined hydrogen, heating and power system based on solar energy, which mainly includes alkaline water electrolysis, metal-hydride hydrogen storage and proton exchange membrane fuel cells. To achieve the best combination of electricity, heat, and hydrogen, four energy management strategies based on mass, energy, and information flow are proposed. Taking an ecological community in Ningbo as the application scenario, the system performance under four control strategies in typical summer and winter days is studied, and the best control strategies in summer and winter are given, respectively. Electricity-led and high-led strategies are recommended for summer and winter, and both strategies can achieve a real-time supply of electric power, heating power, and hydrogen. After a day of operation, the two strategies have surpluses of 0 and 221.5 kW h of electricity, 5706 and 102.16 MJ of heat, and 57 and 17.82 kg of hydrogen, respectively.

Passivity Fractional-Order Sliding-Mode Control of Grid-Connected Converter With LCL Filter

Grid-connected converter with LCL-filter (LCL-GCC) plays an important role in renewable power generation systems. However, existing control techniques face several challenges in practice (e.g., difficulty in parameter design, slow dynamic response, and poor robustness under slowly time-varying filter parameter, dead-time of power devices and external disturbances). To solve these difficulties, a passivity-based fractional-order sliding-mode control (PBC-FOSMC) hybrid controller, which combines the merits of PBC and FOSMC, is proposed, where the inputs of the passive controller are the outputs of the FOSMC controller. First, a passive current controller is designed based on the Euler-Lagrange (EL) model established by damping injection according to the passivity-based control (PBC) theory, which can make the system automatically converge to meet the energy dissipation law. Secondly, a FOSMC controller is designed to further enhance the system robustness to counter disturbances and compensate the reference current accuracy of PBC. The introduced fractional order can successfully suppress the undesired chattering due to the switching behaviors in conventional SMC. Thirdly, the hybrid PBC-FOSMC controller is derived and system stability is analyzed. Finally, experimental results under 10-kW prototype validate the excellent performance of the proposed method in terms of robustness, dynamic performance, strong perturbation rejection ability, etc., and the desired control targets are achieved.

A Novel Modulation Strategy for Split-Inductor Active NPC Inverter With Loss Distribution Balancing and Thermal Stress Reduction

Neutral point clamped inverter (NPC) features low harmonics, high efficiency, and low voltage stress, et al. NPC is widely applied in renewable energy power generation systems, such as wind turbine power and photovoltaic. However, due to unbalanced power losses, NPC suffers inherent thermal unbalance among inner and outer power switches. A split-inductor active neutral point clamped inverter (SI-ANPC) was initially proposed to improve the operating reliability, providing the structural basis for balanced loss distributions. With this purpose, a novel modulation strategy with balanced loss distribution for SI-ANPC is proposed in this paper. The modulation strategy is analyzed under the unity and non-unity power factors. In specially, two redundant zero-state paths are fully used. Under the unity power factor, the power switches operate at the switching frequency or maintain the conduction state complementarily. Considering the phase angle in the non-unity power factor situation, the working patterns of power switches are rearranged to reduce the loss difference. The thermal stress is decreased on both occasions. Finally, loss calculation results, experimental waveforms, and thermal images of the inner and outer switches are presented to confirm the effectiveness of the proposed modulation strategy.

Analysis and Suppression Strategy of Synchronous Frequency Resonance for Grid-Connected Converters With Power-Synchronous Control Method

The power-synchronization control (PSC) method of grid-connected converters, which is based on the active power orientation, is a promising solution for high-penetration renewable power generation systems. Unfortunately, synchronous frequency resonance (SFR) is inevitably found in PSC-controlled converters, especially when connected to inductive networks, which seriously damages the stability of the system. The relatively small equivalent resistance of the inductive network is regarded as the main cause of SFR, and a virtual resistor (VR) is usually employed to dampen this kind of oscillation. However, another important reason for SFR is the non-minimum phase effect of the loop gains, which is discussed in this paper. With considering the dynamics of the grid equivalent inductance, the small-signal model of PSC-controlled converter is established. By this, the mechanism of SFR and the non-minimum phase effect are revealed. Furthermore, a conjugate poles elimination control method based on auxiliary branches introduced into the power control loops is proposed to suppress SFR, which can also broaden the control bandwidth compared with VR method. Finally, the theoretical analysis is verified by simulations and hardware-in-loop experimental results.