Intermittent Renewable Sources Research Articles

Domesticating energy flexibility. Learning from great britain’s 2022–2023 demand flexibility service

Demand-response is essential for balancing electricity grids with increasing proportions of intermittent renewable sources of generation. Harnessing the potential for demand-response in domestic settings could deliver widespread benefits for electricity systems and householders. This study applies domestication theory to a major national domestic electricity demand-response programme in Great Britain, exploring how participants integrate demand-response sessions into their everyday routines. The study uses empirical data from twenty-five participants who completed diaries reflecting on their experience of taking part in thirteen demand-response sessions scheduled over a five-month period in winter 2022–23. The study identifies and analyses five pathways for domesticating demand-response, making recommendations to support system-actors in boosting and sustaining the adoption of demand-response. The study concludes that designing electricity demand-response programmes, as a staple of secure low-carbon energy systems, will need to take full account of users’ non-financial motivations, previous experiences of demand-response, and access to enabling technology.

Investigating bubble-induced overpotential, current non-uniformity, and bubble distribution in flow-based water electrolyzers: A numerical study

The transition towards a sustainable energy landscape necessitates efficient and scalable technologies for renewable energy storage. Water electrolysis, a process that converts electrical energy into chemical energy stored in hydrogen, holds immense potential for integration with intermittent renewable sources. However, the performance and efficiency of water electrolyzers are impeded by the complex multiphase flow dynamics involving bubble nucleation, growth, and transport within the electrochemical cell. This study employs state-of-the-art three-dimensional multiphase flow simulations to unravel the intricate interplay between bubbles and the electrochemical processes in a parallel-electrodes flow-based electrolyzer (PE-FBE). By accurately capturing bubble-electrolyte interfaces, the simulations quantify the detrimental effects of bubbles on overpotentials, current density distribution, and bubble distribution. Crucially, the impact of critical parameters, including flow rate, bubble nucleation size, surfactant addition, and applied current, on these performance metrics is systematically investigated. The findings reveal strategies to mitigate bubble-induced losses, enhance current uniformity, and improve hydrogen purity, paving the way for optimized electrolyzer designs and efficient renewable energy storage.

Robust hybrid control strategy for active power management in Kabertene wind farm within Algeria’s PIAT grid

The paper introduces a hybrid control strategy for optimised active power management in Algeria's Kabertene wind farm, crucial for the pole insalah-adrar-timimoune (PIAT) grid's stability. This strategy merges simultaneous interconnection and damping assignment (SIDA) passivity theory, passivity-based control (PBC), and multivariable proportional-integral-derivative (PID) controllers. This combined approach ensures frequency and voltage stability within the PIAT grid, which encompasses various elements like wind farms, solar plants, gas turbines, and dynamic impedance (Z), current (I), and active power (P) (D-ZIP), load model. By tailoring controllers for doubly fed induction generators (DFIGs) using SIDA-PBC principles and optimising internal parameters, the strategy achieves precise control of active power output. Additionally, particle swarm optimisation (PSO) refines power scheduling, which is especially beneficial for intermittent renewable sources like DFIGs. This comprehensive strategy offers numerous advantages: improved network stability, minimized voltage deviations, reduced frequency fluctuations, and enhanced integration of renewable energy sources. The paper emphasises practical implementation considerations, providing valuable guidance for efficient Kabertene wind farm operation and integration. This research contributes significantly to fostering cleaner and more reliable energy systems, facilitating the PIAT grid's transition towards sustainable energy generation.

Optimally tuned cascaded FOPI-FOPIDN with improved PSO for load frequency control in interconnected power systems with RES

In the operation and control of power systems, load frequency control (LFC) plays a critical role in ensuring the stability and reliability of interconnected power systems. Modern power systems with significant penetration of highly variable and intermittent renewable sources present new challenges that make traditional control strategies ineffective. To address these new challenges, this paper proposes a novel LFC strategy that employs a cascaded fractional-order proportional integral-fractional-order proportional integral derivative with a derivative filter (FOPI-FOPIDN) as a controller. The parameters of the FOPI-FOPIDN are optimised using a variant of the particle swarm optimization (PSO) in the literature called ADIWACO. The effectiveness and scalability of the proposed strategy are validated by extensive simulations conducted on two- and three-area test systems and performance comparisons with recent LFC control strategies in the literature. The performance metrics used for the evaluation are ITAE values, deviations in the power flows in the tie-lines, and deviations in the frequencies of the control areas with the power systems subjected to diverse load and RES generation disturbances in several experimental scenarios. Governor dead band, communication time delay, and generation rate constraints are considered in one of the scenarios for more realistic evaluation. Again, the controller’s robustness to uncertain model parameters is validated by varying the parameters of the three-area test system by ± 50%. The simulation results obtained confirm the controller’s robustness and its superiority over the comparison LFC strategies in terms of the above performance metrics.

Modified Tilt-integral active disturbance rejection controller with inertia emulated direct current link for frequency control of marine microgrid

The increasing integration of intermittent renewable sources (RSs) poses a dynamic frequency stability challenge for modern marine vessel microgrids. To address this issue, this paper proposes a novel control approach, specifically targeting frequency and tie-line power stabilization in a diverse source marine microgrid (MμG) with two intertied areas featuring renewable (wind-wave) sources. The suggested approach introduces a modified tilt-integral active disturbance rejection (TI-ADRC) controller designed to ensure effective damping of power frequency oscillations. As the control scheme depends on the optimal setting of the proposed controller, a recently developed marine predator technique (MPT) has been adopted. The performance of the proposed controller is compared with other recent controllers viz. PID, tilt-integral derivative (TID), two-degree-of-freedom (2DOF)-PID, fuzzy-PI, and ADRC to validate its superiority. To further enhance the system dynamics, a precise modeling of inertia emulated direct current (IEPDC) tie link is incorporated in microgrid system. The impact assessments, considering time delays with pre/post IEPDC link, demonstrate a substantial 57.79% and 81.53% reduction in peak frequency overshoot compared to DC link (conventional model) and AC link, respectively. The analysis of the eigen plot confirms the stability of the control system. Sensitivity assessments of the controller against ± 30% parametric variations and load fluctuations are conducted, affirming its robustness. Finally, the result from OPAL-RT confirm the practicality of the proposed method. It is asserted that the suggested controller is reliable and functions well in n the presence of diverse disruptions and parametric variations.

Heat absorption/release efficiency betterment of phase change material inside a shell-and-tube latent heat storage system under six different conditions of tube and fins

Researchers are exploring innovative solutions for thermal energy storage to address the challenges posed by intermittent renewable sources, enhance energy efficiency, and contribute to the global shift towards cleaner and more sustainable energy practices. In the pursuit of an optimal system to improve the heat release/absorption efficiency of phase change materials (PCMs), a unique shell and tube latent heat storage system with four rectangular fins was designed. The melting and solidification behaviors of the material in this device were examined by manipulating the tube's position within the shell and fins around the tube. Six different cases were considered such as case A (tube in the center of the shell), case B (tube at the top of the shell), case C (tube at the bottom of the shell), case D (tube in the center of the shell with fins on its sides), case E (tube at the top of the shell with fins located in its bottom section), and case F (tube at the bottom of the shell with fins located in its top section). Cases D and E were the best options for absorbing and releasing heat in the shortest time. However, it should be noted that case F was faster during the melting process and dropped behind in the final stages. The authors proposed that if achieving a balanced result without incurring additional costs is essential, case D is a suitable option since it offers reasonable performance in melting and solidification processes. However, suppose researchers and developers of energy storage systems are seeking higher performances where heat absorption and release occur much more rapidly. In that case, it is suggested to construct one of the cases, E or F, and implement a rotational mechanism to enable access to the other case. Based on the outcomes, cases D and F needed 6235 s and 7552 s, respectively, to fully melt. While all cases even required more than 3 h to solidify 80 % of the PCM. The complete melting speed of Case F is 21.12 % faster than that of Case D. Additionally, the time required for 50 % solidification is 14.79 % faster for Case E compared to Case D. During 3 h, this system could absorb 1172 kJ of energy (cases D and F) and release 893 kJ of energy (cases D and E).

Renewable hydrogen production through electrolysis: An analysis of the cost gap for its economic competitiveness in Italy

With global policies targeting greenhouse gas emission reduction, renewable hydrogen produced by water electrolysis powered with renewable electricity appears a promising alternative to fossil fuels. However, still high capital costs, reliance on intermittent renewable electricity sources, and high electricity cost hinder the economic viability of electrolyzers. This work develops a comprehensive analysis for assessing the need of an incentive to make renewable hydrogen economically viable, identifying different archetypes of electrolysis plant representative of a wide range of applications. A techno-economic optimization model is set up that minimize the average hydrogen production cost and compute the cost gap that makes hydrogen economically competitive with the fossil alternative, defining the optimal size and operation of the plant components while satisfying the hydrogen demand. The model is applied to the Italian case study. Sensitivity analyses investigate the impact of economy of scales, renewable electricity availability and introduction of the emission trading system. Cost gaps ranging between 8.1 €/kg and 29.9 €/kg highlights the need of an incentive to allow the deployment of this technology, thus meeting the hydrogen penetration targets.

Magnetic field based finite element method for magneto-static problems with discontinuous electric potential distributions

We introduce two finite element formulations to approximate magneto-static problems with discontinuous electric potential based respectively on the electrical scalar potential and the magnetic field. This work is motivated by our interest in Liquid Metal Batteries (LMBs), a promising technology for storing intermittent renewable sources of energy in large scale energy storage devices. LMBs consist of three liquid layers stably stratified and immiscible, with a light liquid metal on top (negative electrode), a molten salt in the middle (electrolyte) and a heavier liquid metal on bottom (positive electrode). Energy is stored in electrical potential differences that can be modeled as jumps at each electrode-electrolyte interface. This paper focuses on introducing new finite element methods for computing current and potential distributions, which account for internal voltage jumps in liquid metal batteries. Two different formulations that use as primary unknowns the electrical potential and magnetic field, respectively, are presented. We validate them using various manufactured test cases, and discuss their applications for simulating the current distribution during the discharge phase in a liquid metal battery.

Development of the Squaramide Scaffold for High Potential and Multielectron Catholytes for Use in Redox Flow Batteries.

Nonaqueous organic redox flow batteries (N-ORFBs) are a promising technology for grid-scale storage of energy generated from intermittent renewable sources. Their primary benefit over traditional aqueous RFBs is the wide electrochemical stability window of organic solvents, but the design of catholyte materials, which can exploit the upper range of this window, has proven challenging. We report herein a new class of N-ORFB catholytes in the form of squaric acid quinoxaline (SQX) and squaric acid amide (SQA) materials. Mechanistic investigation of decomposition in battery-relevant conditions via NMR, HRMS, and electrochemical methods enabled a rational design approach to optimizing these scaffolds. Three lead compounds were developed: a highly stable one-electron SQX material with an oxidation potential of 0.51 V vs Fc/Fc+ that maintained 99% of peak capacity after 102 cycles (51 h) when incorporated into a 1.58 V flow battery; a high-potential one-electron SQA material with an oxidation potential of 0.81 V vs Fc/Fc+ that demonstrated negligible loss of redox active material as measured by pre- and postcycling CV peak currents when incorporated in a 1.63 V flow battery for 110 cycles over 29 h; and a proof-of-concept two-electron SQA catholyte material with oxidation potentials of 0.48 and 0.85 V vs Fc/Fc+ that demonstrated a capacity fade of just 0.56% per hour during static H-cell cycling. These findings expand the previously reported space of high-potential catholyte materials and showcase the power of mechanistically informed synthetic design for N-ORFB materials development.

Development of an Energy Planning Model Using Temporal Production Simulation and Enhanced NSGA-III

This paper presents an innovative model of Energy Planning Model which allows navigating the complexities of modern energy systems. Our model utilizes a combination of Temporal Production Simulation and an Enhanced Non-Dominated Sorting Genetic Algorithm III to address the challenge associated with fluctuating energy demands and renewable sources integration. The model represents a significant advancement in energy planning due to its capacity to simulate energy production and consumption dynamics over time. The unique feature of the model is based on Temporal Production Simulation, meaning that the model is capable of accounting for hourly, daily, and seasonal fluctuations in energy supply and demand. Such temporal sensitivity is crucial for optimization in systems with high percentages of intermittent renewable sources, as existing planning solutions largely ignore such fluctuations. Another component of the model is the Enhanced NSGA-III algorithm that is uniquely tailored for the nature of multi-objective energy planning where one must balance their cost, environmental performance, and reliability. We have developed improvements to NSGAIII to enhance its efficiency when navigating the complex decision space associated with energy planning to reach faster convergence and to explore more optimal solutions. Methodologically, we use a combination of in-depth problem definition approach, advanced simulation, and algorithmic adjustments. We have validated our model against existing models and testing it in various scenarios to illustrate its superior ability to reach optimal energy plans based on efficiency, sustainability, and reliability under various conditions. Overall, through its unique incorporation of the Temporal Production Simulation and an improved optimization algorithm, the Energy Planning Model provides novel insights and practical decision support for policymakers and energy planners developed to reach the optimal sustainable solutions required for the high penetration of renewables.

The effects of reducing renewable power intermittency through portfolio diversification

Intermittency of renewable power sources is a growing concern for grid reliability in the United States and it has not been properly addressed by public policy for very long. One simple way to mitigate this problem is to diversify the renewable energy portfolio. This work studies the case of Texas, a state that not only is the largest wind power producer in the US, but that also has faced considerable diversification in its renewable energy portfolio in the past ten years. A dispatch model is proposed to simulate how thermal generators respond to changes in the intermittency of renewable sources. Additionally, since higher renewable output usually means higher intermittency and vice-versa, a mean–variance analysis is used to study this trade-off. Results indicate that although intermittency decreases the reliability of the grid, reducing it can have adverse effects as increasing the dispatch of polluting power sources and decreasing the revenues of thermal generators, what can decrease important investment in dispatchable power sources in the long-term. Also, results show that the subsidy design adopted by the federal government is an obstacle to portfolio diversification.

Neural network predictive control in renewable systems (HKT-PV) for delivered power smoothing

The reduction of power fluctuations from intermittent renewable sources is one of the most pressing challenges today. Recent research has shown that prediction and control mechanisms, when combined with energy storage systems, significantly contribute to improving these techniques. However, substantial research gaps still exist regarding the optimization of energy storage system operability. This article introduces an innovative power smoothing method based on neural network predictive control, in conjunction with the exponential moving average method. The proposed approach encompasses the ability to substantially reduce energy fluctuations, optimize battery state of charge, and mitigate ramp rates, thereby preventing deep discharges that shorten battery lifespan. Furthermore, the control system's primary objective is to optimize energy exchange with the grid, surpassing the performance offered by other conventional power smoothing methods. The control system excels in optimizing energy exchange within the network, surpassing conventional methods. Extensive testing on the University of Cuenca microgrid reveals a consistently more stable and higher battery charge compared to conventional methods. Numerical results for underscore the method's effectiveness with a fluctuation suppression rate of 30.78 % compared to 34.85 % (low pass filter) and 36.22 % (ramp rate) methods respectively. The enhanced voltage profiles at the common coupling point ensure the delivery of high-quality and stable power.

On Green Hydrogen Generation Technologies: A Bibliometric Review

Green hydrogen, produced by water electrolysis with renewable energy, plays a crucial role in the revolution towards energy sustainability, and it is considered a key source of clean energy and efficient storage. Its ability to address the intermittency of renewable sources and its potential to decarbonize sectors that are difficult to electrify make it a strategic component in climate change mitigation. By using a method based on a bibliometric review of scientific publications, this paper represents a significant contribution to the emerging field of research on green hydrogen and provides a detailed review of electrolyzer technologies, identifying key areas for future research and technology development. The results reflect the immaturity of a technology which advances with different technical advancements, waiting to find the optimal technical solution that allows for its massive implementation as a source of green hydrogen generation. According to the results found in this article, alkaline (ALK) and proton exchange membrane (PEM) electrolyzers seem to be the ones that interest the scientific community the most. Similarly, in terms of regional analysis, Europe is clearly committed to green hydrogen, in view of the analysis of its scientific results on materials and electrolyzer capacity forecasts for 2030.

Evaluation and deployment of a unified MPPT controller for hybrid Luo converter in combined PV and wind energy systems

This work emphasizes the development and examination of a Hybrid Luo Converter integrated with a unified Maximum Power Point Tracking (MPPT) for both grid and independent hybrid systems. The primary objectives of this hybrid system are to efficiently harness power from intermittent and variable renewable sources while elevating low-voltage energy inputs to utility-grade levels. Unlike previous studies employing specific MPPT algorithms for solar and wind sources, this work aims to simplify the control system by utilizing a unified MPPT controller. This research also introduces a novel approach involving dual-lift hybrid Luo converters to create hybrid systems, operating exclusively or concurrently based on the availability of renewable resources. To maximize power generation from all renewable sources, a unified MPPT algorithm is developed. The hybrid system, incorporates 500 W wind and 560 W PV systems, the innovative Luo converter, and the unified MPPT controller. A comprehensive comparative analysis is presented, comparing the hybrid system's performance with that of traditional control algorithms, such as the Perturb & Observe, and Radial Basis Function Network controllers. The successful prototype of the converter validates the practicality of the proposed approach.

Climate policy with electricity trade

Trade reduces the effectiveness of climate policies such as carbon pricing when domestic products are replaced by more carbon-intensive imports. We investigate the impact of unilateral carbon pricing on electricity generation in a country open to trade through interconnection lines. We characterize the energy mix with intermittent renewable sources of energy (wind or solar power). Electricity trade limits the penetration of renewables due to trade-induced competition. A carbon border adjustment mechanism (CBAM) removes this limit by increasing the cost of imported power, or by deterring imports. The CBAM must be complemented by a subsidy on renewables to increase renewable generation above domestic consumption. The interconnection line is then used to export power rather than importing it when renewables are producing. We also examine network pricing and investment into interconnection capacity. A higher carbon price increases interconnection investment which further reduces the effectiveness of carbon pricing. In contrast, when renewable electricity is exported, a higher subsidy on renewables reduces further carbon emissions by expanding interconnection capacity.

Implementation of Fluidized Bed Concept to Improve Heat Transfer in Ecological Adsorption Cooling and Desalination Systems

Sustainable development policy focuses on reducing the carbon footprint generated by the global industry and energy sector. Replacing conventional energy sources with environmentally friendly ones requires advanced research to increase energy efficiency and reduce the instability and intermittence of renewable sources. Moreover, adsorption chillers are an opportunity to introduce net-zero emission technologies to the refrigeration, air-conditioning, and desalination industries. Adsorption devices could be popularized if a method of effective heat transfer in the volume of the adsorption bed is developed. The innovative concept of introducing fluidized beds into the adsorption system can achieve the most promising results in improving energy efficiency. To confirm the adopted assumption, heat transfer coefficient calculations for the packed and fluidized bed were carried out in this paper based on experimental tests and literature data. The empirical research aims to extend the fundamental knowledge in the implementation of fluidization under low-pressure conditions, characteristic of the adsorption systems’ working cycle. Experiments were conducted on a unique test stand equipped with the Intensified Heat Transfer Adsorption Bed (IHTAB) reactor prototype. Five adsorption bed samples were analyzed. The reference sample consisted only of silica gel, and the subsequent ones contained aluminum or carbon nanotubes with 5 and 10% additions. In the case of samples with admixtures, the fluidized state increased the heat transfer coefficient on average from approx. 36.9 W/m2 K to approx. 245.4 W/m2 K.

Optimal Tuning of PID Controllers for LFC in Renewable Energy Source Integrated Power Systems Using an Improved PSO

The constant rise in energy demand and concerns about climate change have led to increased penetration of renewable energy sources (RES). Maintaining active power balance between generation and demand in power systems with significant penetration of these highly variable and intermittent renewable sources requires an efficient load frequency control (LFC) strategy. One such strategy that has gained the attention of researchers is optimal tuning of PID controllers of LFC using metaheuristic method. This paper presents a PSO variant for optimal tuning of PID controllers for load frequency control of power system integrated with renewable energy resources. The proposed PID tuning technique is tested on a two-area power system commonly used in the literature. Seven scenarios have been used to validate the effectiveness of the proposed Load Frequency Control. For more realistic evaluation, governor dead band and communication time delays have been incorporated in the test system in one of the scenarios. Simulation results obtained when compared with those of three well-known PID-tuning metaheuristic algorithms produced shorter settling time and smaller frequency and tie line power deviations.

Optimization of a solar irradiation forecasting tool based on artificial intelligence

In current electric markets, where many stakeholders can take part, power network operators need accurate predictions of the energy generated by intermittent renewable sources in order to control the whole system. Therefore, the capacity to accurately forecast solar irradiance is key when it comes to the large-scale integration of solar energy generators in the traditional network. One of the challenges, however, consists of providing accurate very short-term predictions (minutes ahead) due to the variability of solar irradiance caused by different meteorological phenomena. This study addresses this need for very short-term forecasts through the development of an irradiance prediction scheme for 10 minutes ahead. The irradiance prediction algorithm is based on a parallel combination of two different layer recurrent networks and has been trained with a two-year historical database of solar irradiance. The accuracy of the proposed tool has been validated through forecasting a whole year using data that is not in the database used in the training step. This tool was then used to forecast the irradiance in two Spanish locations with different weather conditions to analyse whether the accuracy changes. The accuracy between predicted and actual values demonstrates that this tool outperforms similar forecasters.

Balancing Energy and Material Efficiency in Green Hydrogen Production via Water Electrolysis

Green hydrogen is increasingly regarded as a pivotal solution in achieving “net zero by 2050” in carbon neutrality across various sectors and industries. Ambitious decarbonisation roadmaps largely depend on the successful deployment of electrolysis technologies. Among these, Proton Exchange Membrane Electrolysis (PEMEL) stands out for its efficiency, compact design, and adaptability to intermittent renewable power sources. PEMEL is gradually being commercialised, and considerable uncertainty remains regarding its future environmental performance at a plant level. Therefore, future PEMEL cells should be life cycle engineered with a focus on improving materials efficiency by investigating enhanced electrochemical catalysts, membranes, and electrodes for an improved membrane electrode assembly (MEA). In this study, we simulate a 10MW PEMEL plant, identify key operational parameters and evaluate future MEA development scenarios to assess their impact on energy consumption, material utilisation, and system durability. Our findings shed light on the potential trade-offs between energy and material efficiency, providing valuable insights to mitigate environmental hotspots. By focusing on these trade-offs, this work contributes significantly to the ongoing efforts to improve the environmental and operational performance of PEMEL plants.

The missing pieces in the catalytic cycle of [FeFe] hydrogenases.

Hydrogen could provide a suitable means for storing energy from intermittent renewable sources for later use on demand. However, many challenges remain regarding the activity, specificity, stability and sustainability of current hydrogen production and consumption methods. The lack of efficient catalysts based on abundant and sustainable elements lies at the heart of this problem. Nature's solution led to the evolution of hydrogenase enzymes capable of reversible hydrogen conversion at high rates using iron- and nickel-based active sites. Through a detailed understanding of these enzymes, we can learn how to mimic them to engineer a new generation of highly active synthetic catalysts. Incredible progress has been made in our understanding of biological hydrogen activation over the last few years. In particular, detailed studies of the [FeFe] hydrogenase class have provided substantial insight into a sophisticated, optimised, molecular catalyst, the active site H-cluster. In this short perspective, we will summarise recent findings and highlight the missing pieces needed to complete the puzzle.