Efficient Use Of Renewable Energy Research Articles

Reinforcement Learning-Enhanced Adaptive Scheduling of Battery Energy Storage Systems in Energy Markets

Battery Energy Storage Systems (BESSs) play a vital role in modern power grids by optimally dispatching energy according to the price signal. This paper proposes a reinforcement learning-based model that optimizes BESS scheduling with the proposed Q-learning algorithm combined with an epsilon-greedy strategy. The proposed epsilon-greedy strategy-based Q-learning algorithm can efficiently manage energy dispatching under uncertain price signals and multi-day operations without retraining. Simulations are conducted under different scenarios, considering electricity price fluctuations and battery aging conditions. Results show that the proposed algorithm demonstrates enhanced economic returns and adaptability compared to traditional methods, providing a practical solution for intelligent BESS scheduling that supports grid stability and the efficient use of renewable energy.

Methods for improving microbial electrolysis cell for swine wastewater treatment

Microbial electrolytic cell combined with anaerobic digestion faces challenges such as unstable clean energy supply and inefficient cathode performance. The integration of low-cost, durable electrodes with renewable energy can enhance the microbial electrolytic cell sustainability. In this study, a metal-organic framework-modified electrode and intermittent renewable energy sources were used in the microbial electrolytic cell to treat swine wastewater. Additionally, hydrothermal carbon composite metal-organic framework were tested to reduce cathode costs and improve biocompatibility. Results showed that with 18 h of daily power from a hybrid wind-solar system, the metal-organic framework-modified cathode achieved the highest cumulative methane production of 305.11 mL/g-chemical oxygen demand and the highest net energy recovery. Increased microbial activity during the power-on period enhanced methane output and energy efficiency, making this energy supply method ideal for microbial electrolytic cells. This approach ensures efficient use of renewable energy, improving the economic feasibility of microbial electrolytic cells for wastewater treatment. The metal-organic framework-modified cathode also promoted biofilm growth, with an average thickness of 37.6 μm and enhanced microbial activity, likely due to its lower resistance and rapid current response.

A Study the optimisation of smart grid power flow

Optimal Power Flow (OPF) is a fundamental concept in the management and operation of modern electrical power systems, particularly within the context of smart grids. As the demand for electricity continues to grow and the energy landscape evolves towards greater sustainability, the need for efficient, reliable, and adaptive power systems has become more critical than ever. The primary objective of OPF is to determine the most efficient way to operate the power system while satisfying various technical and operational constraints. This involves the optimization of several variables, including generator outputs, voltage levels, and power flows, to minimize costs, reduce losses, and enhance system reliability. Smart grids can enhance their resilience to disturbances, support the efficient use of renewable energy, and provide reliable electricity to consumers.

Charging Strategies for Electric Vehicles from Renewable Hybrid Systems

Objective: The aim of this study is to analyze charging strategies for electric vehicles (EVs) in a hybrid system connected to the conventional electricity grid, to optimize the use of renewable energies. Theoretical Framework: This paper presents the concepts of hybrid systems, photovoltaic power generation, and electric vehicle energy demand. It emphasizes the importance of integrating renewable energy into the transportation sector to reduce greenhouse gas emissions and promote sustainability. Method: The research was based on obtaining load curves and photovoltaic generation in different climatic conditions. The energy available for charging electric vehicles was calculated, considering the limitations of the hybrid system. Different charging power configurations were studied. Results and Discussion: The results demonstrate the feasibility of recharging EVs with renewable energy and highlight the operational flexibility provided by storage systems. Different climate scenarios affect energy availability for charging, highlighting the importance of adaptive strategies. Research Implications: This research contributes to developing sustainable strategies in the transportation sector by providing insights into integrating electric vehicles and renewable energy. Practical implications include reducing carbon emissions and decreasing dependence on fossil fuels. Originality/Value: This study stands out for its specific analysis of EV charging strategies in a hybrid context, providing new approaches for the efficient use of renewable energy in transportation. The integration of storage systems and adaptation to climatic conditions are innovative aspects that add value to the research.

Assessment of hydrogen-induced material degradation using electromagnetic testing technology

The production, transport and use of green hydrogen are key issues for the efficient use of renewable energies. Hydrogen is able to compensate for both temporal and spatial fluctuations that naturally occur in the production and consumption of renewable energies, regardless of weather conditions, and thus can act as an efficient energy storage medium. The use of existing gas pipelines in a dynamically operated pipeline network offers particular potential for the transport of green hydrogen with regard to sustainability, resource conservation and economic efficiency. In this context, dynamic means that pressure fluctuations are permissible to a certain extent in the operation of gas pipelines. However, a hydrogen-induced degradation of the mechanical material properties can lead to brittle fracture and manifest itself in sudden material failure. Such failure must be excluded in safetyrelevant infrastructures. Hence, it would be beneficial to detect fatigued or degraded areas in the material at an early stage, especially in the context of possible increased crack growth rates associated with hydrogen embrittlement. In addition to fatigue data, which are crucial in the calculation and design of gas pipelines, non-destructive inspections are particularly important in subsequent operation to monitor the current condition of the pipelines. Non-destructive testing focuses primarily on defects such as cracks that have already developed or on visible corrosion attack. The fatigue condition, i.e., the probability of crack initiation and crack propagation is hard to evaluate. However, this can be addressed by an electromagnetic test method capable of evaluating the current state of the material. In the presented paper, an electromagnetic test method is presented, which is able to detect and evaluate hydrogen-induced material degradation. In subsequent stages, such a method can then be used as an electromagnetic monitoring system in fatigue tests, thus providing new potential for condition assessment.

Adaptive energy management strategy for optimal integration of wind/PV system with hybrid gravity/battery energy storage using forecast models

Hybrid energy systems, including hybrid power generation and hybrid energy storage, have attracted considerable attention as eco-friendly solutions to meet the increasing global energy demands while minimizing environmental impacts. The economic viability and resilience of hybrid energy system solutions depend on careful consideration of economic and reliability factors during the design phase. This paper explores the optimization and design of a wind turbine (WT)/photovoltaic (PV) system coupled with a hybrid energy storage system combining mechanical gravity energy storage (GES) and an electrochemical battery system. An adaptive energy management strategy linked to an optimization process has been proposed for the optimal integration of the WT/PV system with the hybrid Gravity/Battery storage system. Forecast models have been employed to predict solar and wind generation. Simulation models are developed for each component of the multi-source power plant to predict energy flow behavior based on real-world industrial load demand scenarios. The renewables contribution to 100 % reliability is approximately 18 % for photovoltaic and 92 % for wind turbine, primarily attributed to the great wind energy potential of the selected site. The optimal cost of energy is 0.28 €/kWh for a reliability of 100 %, which reduces to 0.03€/kWh when reliability level is decreased to 20 %. The incorporation of forecast models into the study and the hybridization of storage options improve the design accuracy and optimal operation of the multi-source power system leading to reliable and efficient use of renewable energy.

Multi-Faceted Analysis of Phase-Change Composite Intended for Autonomous Buildings.

This paper presents the long-term, holistic results of research into an innovative heat accumulator based on an organic phase-change material in the form of a mixture of aliphatic alkanes, molecular silica sieves, carbon recyclate and epoxy and cement matrices. The research included chemical testing of vacuum soaking of molecular silica sieves with a liquid phase-change material. The results proved an improvement in the heat storage efficiency of the heat accumulators due to the addition of carbon recyclate by 28%, while increasing the heat storage time by 134 min, and a reduction in PCM leakage due to the use of molecular silica sieves. In addition to its cognitive scientific value, another research objective of the work achieved was to obtain response functions in the form of approximating polynomials. They provide a useful, validated and verified tool to predict the physical and chemical characteristics of heat accumulators with different contents of individual components. As part of the ongoing research, technical problems related to leak-proofing assurance and matrix selection for organic phase-change materials were also solved. The solution presented is in line with the issues of efficient use of renewable energy, low-carbon and energy-efficient circular economy.

Would You Like to Trade Your Energy? A Comparative Survey Experiment on Energy Trading Platforms

As energy markets become more decentralised, energy trading platforms are emerging as useful tools to facilitate the coordination of energy consumption and generation, encouraging a more efficient use of renewable energy by residential producers and consumers. By exploring three different European countries, we study the effectiveness of both monetary and non-monetary incentives in fostering energy trade via trading platforms. We use an incentivized survey experiment to evaluate the drivers of consumers’ and prosumers’ willingness to participate in an energy trading platform. We find that the monetary incentive is not necessarily the main reason why people would choose to trade their energy, but other dimensions, such as environmental concerns and independence from the national grid, play an important role.

The Need for Dynamic Process Simulation: A Review of Offshore Power‐to‐X Systems

AbstractThe integration of offshore wind energy into Power‐to‐X (PtX) process chains offers opportunities for the efficient use of renewable energy. This article analyzes different PtX process chain configurations and their adaptation to the offshore environment. However, direct coupling of PtX platforms with fluctuating electrical energy poses major challenges. Dynamic process simulation is presented for analysis of different plant configurations and operating strategies. The article emphasizes the need for interdisciplinary research to consider technological as well as economic and environmental aspects.

(Keynote) Metallaelectro-Catalyzed Bond Activations

Oxidative C–H activation has emerged as an increasingly powerful tool in molecular syntheses.[ 1] Despite major progress towards atom and step economy, these transformations largely rely on precious metal catalysts and stoichiometric amounts of toxic metal oxidants, compromising the overall sustainability of the C–H activation strategy. In contrast, employing electrooxidation in lieu of reactive chemical oxidants prevents undesired waste formation through oxidant economyand offers efficient use of renewable energies from sustainable sources for chemical bond formation.[2] Inexpensive Earth-abundant 3d metal[3] cobaltaelectrocatalysis set the stage for molecular syntheses at a unique level of resource economy.[4] Our studies towards metallaelectrocatalytic C–H and C–C activation will be discussed, with a topical focus on sustainable base metals.[5] References [1] a) L. Ackermann, Acc. Chem. Res. 2014, 47, 281–295; b) C. S. Yeung, V. M. Dong, Chem. Rev. 2011, 111, 1215–1292.[2] a) P. Gandeepan, L. H. Finger, T. H. Meyer, L. Ackermann, Chem. Soc. Rev. 2020, 49, 4254–4272; b) LA, Acc chem Rex 2020, C. Ma, P Fang, T.-S. Mei, ACS Catal. 2018, 7179–7189.[3] P. Gandeepan, T. Müller, D. Zell, G. Cera, S. Warratz, L. Ackermann, Chem. Rev. 2019, 111, 2192–2452.[4] Y. Qiu, M. Stangier, T. H. Meyer, J. C. A. Oliveira, L. Ackermann, Angew. Chem. Int. Ed. 2018, 57, 14179–14183; b) Y. Qiu, W.-J. Kong, J. Struwe, N. Sauermann, T. Rogge, A. Scheremetjew, L. Ackermann, Angew. Chem. Int. Ed. 2018, 57, 5828–5832.[5] a) R. Mei, N. Sauermann, J. C. A. Oliveira, L. Ackermann, J. Am. Chem. Soc. 2018, 140, 7913–7921;N. Sauermann, T. H. Meyer, C. Tian, L. Ackermann, J. Am. Chem. Soc. 2017, 139, 18452–18455. Figure 1

Operation Performance Analysis of a Novel Renewable Energy‐Driven Multienergy Supply System Based on Wind, Photovoltaic, Concentrating Solar Power, Proton Exchange Membrane Electrolyzers, and Proton Exchange Membrane Fuel Cell

In pursuing clean energy systems and carbon neutrality, the efficient use of renewable energy is key. This research introduces a novel wind–solar–hydrogen multienergy supply (WSH‐MES) system, powered by renewables, designed to stabilize power output through regulated concentrating solar power (CSP) and proton exchange membrane electrolyzers (PEMEs). An active regulation strategy for thermal and hydrogen storage is developed to counterbalance the volatility of wind and photovoltaic power. Key results reveal that the WSH‐MES system surpasses WP–PV and WP–PV–CSP systems in reliability, reducing power supply loss probability to 2.81%. This improvement is largely due to the controlled CSP and PEME, which effectively mitigates the stochastic fluctuations in wind and solar power generation, thereby ensuring more stable and reliable power output. Moreover, the system achieves an 80.97% primary renewable energy rate and a 0.12 power discard rate. In conclusion, this research comprehensively examines the operational characteristics of the WSH‐MES system, elucidates the practical advantages of the WSH‐MES system in terms of reliability, renewable energy utilization, and adaptability under various conditions. The results offer valuable insights into the design and operation of multienergy supply systems, potentially fostering the large‐scale implementation of renewable energy systems and leading toward a sustainable energy future.

Coordinated planning of integrated electricity–heat–gas energy system considering renewable energy consumption

AbstractDevelopment and utilization of renewable energy is an effective way to deal with global warming. In this context, integrated electricity–heat–gas energy system (IEHGES) provides a new way for the efficient use of renewable energy. Existing IEHGES planning methods focus on the improvement of cost and energy efficiency, while not designing a capacity configuration scheme for high renewable energy penetration scenarios. Here, a coordinated planning method for IEHGES considering renewable energy consumption is proposed. Firstly, electricity/gas/heat storage, electric boiler and power to gas are co‐configured to realize heat‐electricity decoupling operation of combined heat and power, providing flexible and controllable electricity supply for the system. Then, coordinated planning method of IEHGES is proposed which takes into account the coordination of multi‐energy and the coordination between optimal planning and optimal operation. The spare capacity factors are included in the planning and cost of environmental penalty and renewable energy generation subsidy are included in operation cost. In view of the uncertainties, complementary characteristics between electricity, gas and heat supply systems in IEHGES are combined with k‐means to obtain optimal schemes of coordinated planning. Finally, the correctness and validity of the proposed method are verified by three indexes in a case study.

Revisiting the impact of renewable energy on carbon emission in 130 countries—The mediating effect of resource rental rents and human capital

More efficient use of renewable energy to reduce carbon emission requires a more comprehensive understanding of the impact of renewable energy on carbon emissions. To this end, this work investigates the linear and nonlinear relationship between renewable energy consumption and carbon emissions in 130 countries from the new perspective of resource capital factors (total natural resources rents) and human capital (human capital index). The results are given that from a global perspective, the increase in the proportion of renewable energy consumption can accelerate the reduction of per capita carbon emissions before reaching a particular threshold value of total natural resources rents. When a specific natural threshold value is reached, the increase in the proportion of renewable energy consumption will reduce the rate of per capita carbon emissions. Another interesting finding is that the greater the human factor, the lower the reduction rate of per capita carbon dioxide emissions. To explain the above phenomenon, all countries are divided into four different income levels for further heterogeneity research. When the threshold variables are different, the impact on carbon emissions in various income countries is heterogeneous, which is further analyzed in the article. Furthermore, a meaningful discovery shows that whether the threshold variable is natural or human factor, low-income countries benefit the most from the carbon reduction effect brought by the increase in the proportion of renewable energy consumption, followed by lower-middle income and upper-middle income countries, and the lowest is higher-income countries.

Transient supply-demand matching and numerical parametric study of solar absorption thermal battery for space cooling

Efficient use of renewable energy, e.g., solar energy, is an important pathway towards net-zero energy buildings and carbon neutrality. However, renewable energy is difficult to be fully utilized due to its instability and intermittency. Thermal energy storage technologies applied in buildings can bridge the gap between renewable energy sources and heating/cooling demands. This study employs a solar absorption thermal battery (SATB) in a building for space cooling. The annual dynamic performance of the SATB is investigated and compared in four representative cities by simulation using an experimentally validated model, considering transient supply–demand matching. Besides, parametric studies are conducted for the SATB designed with different solar collector sizes and solution charges. Results indicate that the SATB achieves satisfactory cooling met ratios (MRs) in different climates when 0.49 m2 solar collector is equipped for each square meter of the serviced room. The highest cooling MR of 0.95 is obtained in Singapore, with an energy storage efficiency (ESE) of 0.66 for the ATB unit, a system ESE (solar-to-cooling) of 0.24, and an energy storage density (ESD) of 125.8 kWh/m3. The maximum ESEs of the ATB unit and the SATB system are 0.71 and 0.30, respectively. The highest ESD of 157.1 kWh/m3 is achieved by the SATB system, which is much higher than the sensible and latent thermal batteries for space cooling. This paper demonstrates a transient supply–demand matching operation scheme of the SATB system in different climates with excellent annual performance, which can facilitate the promotion and development of ATB technology.

A new version of membrane search algorithm for hybrid renewable energy systems dynamic scheduling

It is a consensus that hydropower should be clean and renewable. The economic emission dynamic scheduling of hydro hybrid combined heat and power (Hydro-CHP) systems allows for further reduction of greenhouse gas emissions from the power sector. A new version of our Membrane Search Algorithm, denoted as IMSA, is proposed to solve the complex dynamic scheduling problems of CHP and hydro-thermal systems with spatio-temporal coupling, which can obtain competitive solutions. Furthermore, based on IMSA, we construct a multi-objective algorithm, called the Multi-objective Improved Membrane Search Algorithm (MOIMSA), which can solve the complex economic emission dynamic scheduling problem of CHP systems with ramp limits, and provide a solution set with relatively less emissions. Finally, a solution to the dynamic scheduling problem of the Hydro-CHP system is proposed. IMSA obtains the maximum power output of the hydro unit, and MOIMSA is used to search for the Pareto front of the economic emission of CHP. Compared with the unimproved MOMSA, the compromise solution provided by MOIMSA is better. Experiments show that this study contributes to the efficient use of renewable energy and the reduction of emissions.

Realtime And Centralized Solar Panel Online Monitoring System Design Using Thingspeak

Indonesia is a country with a tropical climate and has a high intensity of solar irradiation. Seeing this situation, Indonesia is the right region to implement the installation of new and renewable energy such as PLTS. In the use of solar panels, the magnitude of the output power is determined by several environmental conditions, such as the intensity of sunlight, temperature, and the direction in which sunlight comes. To prevent damage and deterioration in the performance of solar panels, research is needed for a more accurate and efficient use of renewable energy. The study was a solar panel system with a Wemos D1 microcontroller that monitored online using Thing speak with the help of INA 219 and LDR sensors. Online monitoring system by recording data on current, voltage, and light intensity in real time and centralized. The system will store and record measurement data every 15 seconds in the form of JSON, XML, CSV file extensions. Error on the voltage sensor of 1.7% for and 3.2% for the current sensor. average panel voltage value of 12.77 V, average panel current value of 0.43 A and 2410 lux for light intensity at interval testing from 07:00 a.m.to 16:00p.m.

A planning scheme for energy storage power station based on multi-spatial scale model

With the continuous development of renewable energy, it has become important to make efficient use of renewable energy. However, the uncertainty and randomness of renewable energy can cause instability in the operation of power systems and can lead to the problem of abandoning PV power and wind power. To reduce the waste of renewable energy and increase the use of renewable energy, this paper proposes a provincial-city–county spatial scale energy storage configuration model based on the power supply and load situation of the power grid in recent years, which can better adapt to different scenarios. The objective function has been redesigned to take into account the differences in investment returns in different regions, with the objective of minimizing costs, making full use of energy storage devices to reduce the abandonment of renewable energy, achieving efficient use of renewable energy and ensuring system power balance. The proposed model further takes into account the difference in dispatching capacity of different regions and effectively reduces the occurrence of load cutting according to regional characteristics. Finally, the reasonableness of the model is verified by simulation with power grid data for a typical day in spring and a typical day in autumn in a region of China.

Review on Smart Charging of Electric Vehicles via Market-Based Incentives, Grid-Friendly and Grid-Compatible Measures

Smart charging of electric vehicles is a promising concept for solving the current challenges faced by connecting mobility and electricity within the context of the ongoing sustainable energy transition. It allows cost savings for the expansion and operation of the power grid and a more efficient use of renewable energies. However, wide implementation of smart charging requires further work on technical and regulatory issues and further development of standards, especially an end-to-end consistency of the control signals. A fully automated process, as well as customisable services and flexible tariffs, would also facilitate wider market penetration. The novelty of this paper is the consensus of German pilot projects funded within the German programme “Elektro-Mobil” on the communication channel between all stakeholders for the use cases of smart charging based on market price incentives. Within this consensus, the projects have illustrated how specific standards can facilitate the communication between smart charging stakeholders, become a reality in the pilot projects and should be applied to further use cases in the low-voltage network. This consensus results in a white paper. On this basis, the adjustment of the standards can be made to ensure the consistency of the control signals from the beginning of the control process up to the end. In an advanced Edition, solutions for the prioritisation and orchestration of the different control signals could be designed.

A comprehensive evaluation of wind-PV-salt cavern-hydrogen energy storage and utilization system: A case study in Qianjiang salt cavern, China

With global energy consumption increasing year by year, the industrial sectors of the world’s countries have never been more urgent in achieving carbon reduction. Renewable energy plays a crucial role in the industrial decarbonization process. As the most mature renewable energy technology, wind and photovoltaic power generation have made significant progress in recent years. However, the intermittent characteristics hinder the efficient use of renewable energy. Existing research provides sufficient support for the flexible scheduling of large-scale renewable energy. Hence, this paper proposes a combined energy system composed of wind power-photovoltaic-energy storage salt cavern with hydrogen as the energy scheduling carrier. The system mainly realizes energy conversion through electrolytic water equipment and fuel cells. Then, Qianjiang City, Hubei Province, is taken as the analysis object, and the working conditions of each component in the system are optimized with the help of an improved particle swarm optimization algorithm. According to the results, the system’s contribution to the energy system is discussed, and the system's economy and carbon reduction effect is studied. The analysis proves that the improved particle swarm optimization algorithm has a stronger solving ability. The combined energy system can effectively improve the economy and renewable energy utilization rate, meet the regional electricity demand, and significantly reduce carbon emissions. The economic analysis of the system shows that the operation and maintenance cost of hydrogen storage salt caverns accounts for the largest proportion of the total cost, about 60 %. Compared with several existing large-scale energy storage technologies, it is found that the energy efficiency of the whole system is only about 40 % due to the limitation of technology maturity. Nevertheless, the flexibility of the hydrogen storage system layout is relatively high. The required underground space volume is only equivalent to 1/6 and 1/2 of pumped storage and compressed air storage with the same scheduling capacity. The system will provide a theoretical support for the optimization of energy pattern and layout.

Towards carbon Neutrality: Prediction of wave energy based on improved GRU in Maritime transportation

Efficient use of renewable energy is one of the critical measures to achieve carbon neutrality. Countries have introduced policies to put carbon neutrality on the agenda to achieve relatively zero emissions of greenhouse gases and to cope with the crisis brought about by global warming. This work analyzes the wave energy with high energy density and wide distribution based on understanding of various renewable energy sources. This study provides a wave energy prediction model for energy harvesting. At the same time, the Gated Recurrent Unit network (GRU), Bayesian optimization algorithm, and attention mechanism are introduced to improve the model’s performance. Bayesian optimization methods are used to optimize hyperparameters throughout the model training, and attention mechanisms are used to assign different weights to features to increase the prediction accuracy. Finally, the 1-hour and 6-hour forecasts are made using the data from China's NJI and BSG observatories, and the system performance is analyzed. The results show that, compared with mainstream prediction algorithms, GRU based on Bayesian optimization and attention mechanism has the highest prediction accuracy, with the lowest MAE of 0.3686 and 0.8204, and the highest R2 of 0.9127 and 0.6436, respectively. Therefore, the prediction model proposed here can provide support and reference for the navigation of ships powered by wave energy.