Efficient Use Of Renewable Energy Research Articles

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.

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.

Optimization strategy for power sharing and low-carbon operation of multi-microgrid IES based on asymmetric nash bargaining

Promoting the efficient use of renewable energy and realizing the low-carbon operation of the integrated energy system has become an important direction for the reform of the integrated energy system. In this paper, we firstly construct a microgrid model containing electricity, heat and gas multi-energy synergy, consider the optimal operation mechanism of carbon trading with reward and punishment ladder, and improve the model of CHP units by adding carbon capture system and power-to-gas facility to reduce carbon emissions. Then, a cooperative operation model of multi-microgrid electric energy sharing is established, which is then decomposed into the subproblem of maximizing the benefits of microgrid alliances and the subproblem of distributing cooperative benefits, and the alternating direction multiplier method is selected for distributed solution, so as to effectively protect the privacy of each subject. In the cooperative benefit distribution subproblem, a method is proposed to quantify the contribution size of each participating entity by a nonlinear energy mapping function, and each microgrid negotiates with each other by the size of its electric energy contribution in the cooperation as the bargaining power to achieve a fair distribution of cooperative benefits. Finally, the simulation results verify the effectiveness of the proposed method. The results show that the benefits of the microgrid alliance are maximized by the proposed multi-microgrid power sharing method; moreover, the cooperative benefits of the microgrid alliance are equitably distributed based on the magnitude of the energy contribution of each microgrid; in terms of carbon emissions, the results demonstrate that the carbon capture joint power-to-gas system, as well as the energy sharing method among microgrids, can effectively reduce the carbon emissions during the microgrid operation.

Selection and Optimization of Hybrid Power Systems in Remote Areas of China

Providing electricity to remote areas is one of the most important measures to improve the living conditions of local inhabitants. Clean and reliable ways of electricity generation to meet the electricity demands of residents in remote areas of China are considered proceeding from resource, technical and economic factors. To minimize the total net present cost (NPC) and levelized cost of energy (COE), a hybrid power system comprising a diesel power plant (DPP), a solar photovoltaic plant (SPPP), a wind power plant (WPP), and a pumped storage power plant (PSPP) has been designed by using the HOMER software to meet the electricity demands of residents in Xiaoqindao Township (Chandao County, China). The system includes a 150 kW DPP 1, a 140 kW DPP 2, a 529 kW SPPP, a 50 kW WPP, a 200 kW PSPP (with the upper reservoir volume equal to 10000 m3 and head equal to 98 m), and a 201 kW inverter. The renewable sources account for 91.6% of the hybrid power system total electricity output. Along with meeting the electricity demands of residents, the hybrid system efficiently reduces the pollutant emissions caused by electricity consumption, which is important for efficient use of renewable energy in remote areas.

Multistage Economic Scheduling Model of Micro-Energy Grids Considering Flexible Capacity Allocation

Micro-energy grids integrating multiple energy sources can realize the efficient use of renewable energy and accelerate the process of energy transition. However, due to the uncertainty of renewable energy, the stability and security of system operations should be taken into account with respect to multi-energy coupling economic operations. Thus, it is essential to make flexible capacity allocations in advance of the actual scheduling of production in the micro-energy grid. With this motivation, this paper constructs a three-stage scheduling model corresponding to the running stage of the spot market. Specifically, the capacity of flexible, active devices is configured in the day-ahead stage; then, the intraday economic operation dispatching scheme is provided according to the capacity configuration. Based on the day-ahead and intraday optimization results, the system power balance is realized through the dispatching process using the reserve capacity of flexible active devices for deviations generated in the real-time stage of renewable energy. For the uncertainty of renewable energy output, the clustering method is applied to realize the clustering analysis of renewable energy output scenarios. In addition, the conditional value at risk (CVaR) theory is introduced to modify the three-stage stochastic optimization model, and the risk values caused by uncertainty are quantitatively evaluated. Finally, we simulate a practical case to verify the effectiveness of the proposed model. The results show that day-ahead flexible capacity allocation enhances the autonomy of the micro-energy grid system, ensures a certain degree of system operational security, and reduces balancing costs in the real-time stage. The higher the risk aversion factor, the more operational costs the system operator pays to avoid the risk. In addition, if the carbon penalty coefficient is higher, the overall carbon emission level of the micro-energy grid will decrease, but it will gradually converge to a minimal level. This paper guides the development of micro-energy grids and has important constructional significance for the construction of multi-energy collaborative mechanisms.

Simulation of Two-Phase Flow and Syngas Generation in Biomass Gasifier Based on Two-Fluid Model

The efficient use of renewable energy is receiving more and more attention in the context of “carbon neutrality” and “carbon peaking”. For a long time, biomass has been used less efficiently as a renewable energy source, but with the development of fluidized biomass gasification technology, it can play an increasing role in industrial production. A fluidized bed biomass gasifier has a strong nonstationary process due to its complex energy–mass exchange, and analysis of its complex reaction process and products has relied on experiments for a long time. This paper uses a Euler–Euler two-fluid model to establish a three-dimensional CFD model of the fluidized bed biomass gasifier, on which factors affecting syngas generation are analyzed. The simulation shows that increasing the initial bed temperature can effectively improve syngas production, while increasing the air equivalent is not beneficial for syngas production.

Embodied carbon, embodied energy and renewable energy: a review of environmental product declarations

Environmental product declarations (EPD) to EN 15804 provide information about the embodied carbon dioxide of construction products – their life cycle greenhouse gas emissions – alongside reporting the use of renewable and non-renewable primary energy and secondary fuels, among the other environmental indicators. As the number of EPD to EN 15804 increases, they become a useful data resource to consider these impacts. In moving towards a reduction in the embodied carbon of products, it is necessary to use renewable energy resources efficiently to allow the transition to net zero; this is because of the increasing demands on renewable energy to decarbonise industry, transport and domestic energy consumption and the limited capacity to expand renewable generation. This paper reviews published EPD data for structural and reinforcing steels, cement, bricks and structural timber products, and considers, for the cradle to gate ‘product’ life cycle stage, exploring the relationship of embodied carbon with embodied energy (total energy used), the balance of renewable and non-renewable energy, and the efficient use of energy. It is found, for bricks and timber, that EPD show products that use a greater percentage of renewable energy have higher embodied energy, suggesting a less efficient use of renewable energy for these products.

LoRa-RL: Deep Reinforcement Learning for Resource Management in Hybrid Energy LoRa Wireless Networks

LoRa wireless networks are considered as a key enabling technology for next generation internet of things (IoT) systems. New IoT deployments (e.g., smart city scenarios) can have thousands of devices per square kilometer leading to huge amount of power consumption to provide connectivity. In this paper, we investigate green LoRa wireless networks powered by a hybrid of the grid and renewable energy sources, which can benefit from harvested energy while dealing with the intermittent supply. This paper proposes resource management schemes of the limited number of channels and spreading factors (SFs) with the objective of improving the LoRa gateway energy efficiency. First, the problem of grid power consumption minimization while satisfying the system's quality of service demands is formulated. Specifically, both scenarios the uncorrelated and time-correlated channels are investigated. The optimal resource management problem is solved by decoupling the formulated problem into two sub-problems: channel and SF assignment problem and energy management problem. Since the optimal solution is obtained with high complexity, online resource management heuristic algorithms that minimize the grid energy consumption are proposed. Finally, taking into account the channel and energy correlation, adaptable resource management schemes based on Reinforcement Learning (RL), are developed. Simulations results show that the proposed resource management schemes offer efficient use of renewable energy in LoRa wireless networks.

Data Acquisition with LoraWAN IoT Technology to Monitor Bio-Inspired Wind Turbines in Rural Areas of Cundinamarca

Context: The energy crisis is a global problem. In Colombia, research aimed at the efficient use of renewable energies is being conducted. For example, in the case of bio-inspired wind generators, a monitoring system is required to observe the output variables (voltage and frequency). Method: LoRaWAN technologies are used to deploy the wireless link since the generators are separated from the base station. In addition, the Gateway coverage area is simulated with HTZ Communications software for future smart grid improvements. Results: The implemented system allows constant monitoring over a long period of time and stores its information in online, open-source databases, which allows remotely visualizing the status of the network, with a total of 3 samples per minute and a range of up to 3,47 km. Conclusions: The data acquisition system can be implemented for remote monitoring. Moreover, since it is a low power system, it can be utilized in non-interconnected areas, as well as for storing data for up to 6 months. However, for the characterization of a model of wind generators, it is advisable to modify the system so that the sampling time is lower.