Efficient Use Of Renewable Energy Research Articles

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.

Synergistic Evaluation between Decoupled Electrolysis for Water Splitting and Liquid-Organic Hydrogen Carrier (LOHC) Systems: A Simulation Study

The combination of two innovative processes for hydrogen production and storage is presented and evaluated. The first process, named Electrochemical thermally Activated Chemical (ETAC) cycle, involves the temporal decoupling of hydrogen production, while the second process involves the hydrogenation of an organic molecule (methylcyclohexane, MTH). The models for ETAC and MTH systems are implemented on Aspen Plus, assuming a cycle behavior computed with calculator blocks, and validated against experimental data. Simulation studies are performed, including parametric sensitivity analysis, to evaluate effects of applied load, temperature, and pressure. Finally, an energy analysis is performed to assess the efficiency of the overall system. The study revealed that integrating thermically both processes (ETAC + MTH) is advantageous as it leads to an overall increase of energy efficiency compared to commercially available solutions. In addition, this work addresses the issue of the limitations of these technologies and proposes a cost analysis, particularly for the ETAC System. This manuscript provides an innovative approach for Power-to-H2, addressing actual challenges towards an efficient use of renewable energy.

Battery technology and sustainable energy storage and conversion as a new energy resource replacing fossil fuels

One of the greatest challenges facing our world today is climate change, brought about by the emission of greenhouse gases into the atmosphere in large part due to the massive use of fossil fuels to satisfy our society's ever-increasing energy demands. The transition to clean energy resources requires the development of new, efficient, and sustainable technologies for energy conversion and storage. Several low carbon energy resources will contribute to tomorrow's energy supply landscape, including solar, wind, and tidal power, yet rechargeable batteries will likely remain the dominant technology for storing this energy and using it in an economic and efficient manner for decades to come. For instance, the gradual replacement of internal combustion engine vehicles powered by petroleum or diesel by electric vehicles and photovoltaic power charging stations is one way we can lessen our reliance on fossil fuels. Improving the performance of energy storage and conversion devices toward higher energy and power density, and greater efficiency, durability, and safety, hinges on the development of new materials and processes, specifically, on tuning the properties of the component materials by modulating their crystal structure and microstructure, and on optimizing materials processing and device assembly protocols. Today, there is a clear need for a dedicated publication platform to cover high-impact and multidisciplinary scientific contributions that will pave the way to the next generation of energy conversion and storage devices. We expect this journal to grow in the coming years, as part of the fourth industrial revolution featuring the efficient use of renewable energies, in addition to navigating a digital world and accelerated by the current pandemic. Battery Energy is co-published by Wiley and Xijing University, China. Battery Energy covers diverse scientific topics related to the development of high-performance energy conversion/storage devices, including the physical and chemical properties of component materials, and device-level electrochemical properties. Battery Energy is a high-quality, interdisciplinary, and rapid-publication journal aimed at disseminating scholarly work on a wide range of topics from different disciplines that share a focus on advanced energy materials, with an emphasis on batteries, energy storage and conversion more broadly, photocatalysis, electrocatalysis, photoelectrocatalysis, heterocatalysis, and so on. The journal features cutting-edge research covering many forms of electrochemical and photochemical energy, including battery processes, and spanning from conventional electrical energy to the type that catalyzes chemical and biological transformations. This journal is also interested in work that prompts new technologies and processes leading to the green production of battery materials. Upcoming issues of Battery Energy will be composed of research papers, review articles, editorials, and research highlights. We recommend contributors to read through the authors' guidelines (https://onlinelibrary.wiley.com/page/journal/27681696/homepage/author-guidelines). This journal adopts an open-access publishing model, and so all published articles are freely accessed through the Wiley Online Library. The editorial team of Battery Energy is composed of world-renowned scientists in the field of energy materials. The Editor-in-Chief is Prof. Yong-Mook Kang from Korea University, Republic of Korea, who has been tackling various important issues for battery technologies. Prof. Anmin Cao (Institute of Chemistry, Chinese Academy of Sciences, Beijing, China), Prof. Raphaële Clément (University of California, Santa Barbara, USA), Prof. Shu-Lei Chou (Wenzhou University, Wenzhou, China), Prof. Sang-Young Lee (Yonsei University, Seoul, Republic of Korea), Prof. Zongcheng Miao (Northwestern Polytechnical University, Xi'an, China) are all invested in the successful launch of the journal and in ensuring the publication of research works of the highest quality in Battery Energy. The editorial board is composed of prominent scientists from academia and industry, to consolidate the ties between fundamental understanding and large-scale implementation of energy devices within this journal. We firmly believe that our diverse insights and viewpoints will provide our authors and reviewers a smooth peer review and publication processes. Yong-Mook Kang (Editor-in-Chief) Korea University, Seoul, Republic of Korea. Anmin Cao (Associate Editor) Institute of Chemistry, Chinese Academy of Sciences, Beijing, China. Raphaële Clément (Associate Editor) University of California Santa Barbara, Santa Barbara, USA. Shu-Lei Chou (Associate Editor) Wenzhou University, Wenzhou, China. Sang-Young Lee (Associate Editor) Yonsei University, Seoul, Republic of Korea. Zongcheng Miao (Associate Editor) Northwestern Polytechnical University, Xi'an, China.

Prediction of Renewable Energy Consumption of European Union Using Artificial Neural Networks

The increasing demand for renewable energy sources attract attention of both researchers and governments. The countries support renewable energy and technologies developed for the efficient use of renewable energy. For this reason, the assessment and prediction of renewable energy consumption is vital for governments. Furthermore, associations put forward long-term and short-term targets for countries. Therefore, European Union (EU) members provide support schemes for promoting renewable energy consumption. In this study, renewable energy consumption in EU is predicted using artificial neural networks. The World Development indicators which are renewable electricity output, energy use generated from combustible renewables and waste, electricity production from oil, gas and coal sources, energy use generated from alternative and nuclear energy, electricity production from renewable sources excluding hydroelectric, energy imports, energy use, gross domestic product (GDP) and population are evaluated as independent variables using historical data from 1990 to 2015. The results indicate that artificial neural networks provides convenient results in energy demand forecasting as seen in similar studies of the literature.

Multi-objective optimization of passive energy efficiency measures for net-zero energy building in Morocco

The present study aims to assess the possibility of achieving net zero energy building in the Moroccan housing stock by combining architectural energy efficiency practices and renewable energies for hot water and electricity productions. The impacts of retrofitting an existing residential building to meet zero energy balance in the six Moroccan climatic zones have been investigated. The design features considered include building orientation, windows type and Window-to-Wall Ratio, wall and roof insulation and infiltration rate. A multi-objective optimization has been carried out in order to find the best solution which will allow a compromise between the building life cycle cost, energy saving and thermal comfort through the optimization of the aforementioned design parameters as passive energy efficiency measures. The obtained results show that the application of the multi-objective study conclusions combined with an efficient use of renewable energies makes it possible to achieve zero energy building throughout all Moroccan housing stock. More than 21% of energy saving can be achieved, 28% in heating load and 40% in cooling. Moreover, 45% of building energy load can be covered instantly by renewable energy systems in all Moroccan climatic zones. On the other hand, the comparison of levelized cost of energy shows that Tangier is the city with the greatest potential for wind energy system and other cities are expected to present a challenge since the areas for efficient on-site generation of photovoltaic and solar thermal collectors are limited.

Influencing Factors on Consumers’ Willingness to Share Energy Data on Online Energy Platforms

Climate change requires an adaptation of the energy system towards an efficient use of renewable energies. For efficient control and optimization of the energy system, energy consumption and production data at household level play an essential role. Sharing platforms can enable the bundling and controlling of energy data from individual households. However, there is often a lack of acceptance among potential users to share their own data on such platforms. Therefore, this paper investigates the willingness of consumers to share their personal energy data. In particular, several factors that influence this willingness are examined. Decisive for the willingness are incentives for consumers in return for sharing their energy data. These can be offered in personal added value or collective added value. This paper shows that the factors perceived behavioral control, personal attitude and subjective norm have an influence on the willingness of private users to share energy data if a personal benefit or a collective benefit is provided. The age of users and their privacy concerns affect the willingness to share only in case personal value is added. These findings are valuable for the development and operation of online energy platforms.

Research on Optimal Dispatch of Active Distribution Network with Distributed Energy Storage

In order to alleviate the energy crisis and improve environmental quality, the efficient use of renewable energy has become a development trend. In order to integrate various types of distributed generation (Distributed Generation, DG), to achieve large-scale renewable energy consumption, improve the utilization efficiency of distribution network resources, and improve the reliability and power quality of users, active distribution network technology has come into being, and it has attracted more and more attention from researchers. As an important part of the active distribution network, distributed energy storage has the advantages of centralized energy storage that can achieve independent control and “plug and play”, wide geographical distribution, flexibility and convenience. At the same time, because energy storage has power and the dual characteristics of load, using it to participate in the optimal dispatching of the distribution network, can effectively reduce the operating cost of the distribution network and to a certain extent realize the peak cut and valley filling of the power grid, and improve the power quality of the distribution network.

A request dispatching method for efficient use of renewable energy in fog computing environments

In the emerging era of Internet of Things (IoT), fog computing plays a critical role in serving delay-sensitive and location-aware applications. As a result, fog nodes are envisioned to be heavily deployed and form future distributed data centers. Powering fog nodes with green energy sources (such as solar and wind), not only helps in environmental and CO2 emission control but also paves the way towards a “sustainable IoT technology”. However, the downside of green energy is its variation and unpredictability, which needs to be engineered. In this paper, we use the Lyapunov optimization technique to derive algorithms for dynamic dispatching of the users’ requests among the nearby fog nodes and remote data centers. The proposed algorithms take into account the time constraints of the requests and maintain the system stability while efficiently utilize the available green energy sources. Exhaustive simulation results, based on solar radiation data supplied by the Australian Bureau of Meteorology, confirm the efficiency of the proposed algorithms. In particular, in terms of service time, the number of deadline misses and green energy utilization, the proposed algorithms outperform the state-of-the-art alternative up to 6%, 17% and 12%, respectively.

Renewable Energy Powered Plugged-In Hybrid Vehicle Charging System for Sustainable Transportation

Energy transformation by power electronic converters is not feasible without the efficient use of renewable energy. The article tries to extend the use of renewable energy to PHEV battery charging. In PHEV, the battery is one of the major sources of stored energy. The converter used for charging these batteries is of crucial concern. The paper addresses various challenges in designing a DC to DC converter for battery charging in DC bus. An optimized converter is designed to work with renewable energy sources to accomplish a high boost ratio, low input current ripple, low output voltage ripple, high power efficiency, and high power density. A combination of two interleaved boost converters is effectively used with the overlap time switching to achieve a high voltage boost ratio in forming the DC bus. Transformer isolation is used to increase reliability and boost ratio further. The secondary side employs a series-connected voltage doubler. The converter boosts an input voltage of 24 V to a range of 300–400 V. Simulation results have been obtained for a 300 W system. Simulation results are validated by a prototype implementation for a 250 W system. The converter is studied and analyzed for steady-state and transient state characteristics and the power efficiency obtained is 92.9%.

ДВУХКОНТУРНЫЙ НАКОПИТЕЛЬ ЭНЕРГИИ ДЛЯ ГИБРИДНЫХ ЭНЕРГЕТИЧЕСКИХ СИСТЕМ С ВОЗОБНОВЛЯЕМЫМИ ИСТОЧНИКАМИ ЭНЕРГИИ

Актуальность. Актуальной задачей технико-экономического развития северных и восточных регионов России является обеспечение надежного и эффективного электроснабжения потребителей, территориально расположенных в отдаленных, труднодоступных районах. Перспективным способом решения данной проблемы является применение гибридных энергетических систем с возобновляемыми источниками энергии. Характерной особенностью режимов гибридных систем, особенно с высоким уровнем замещения топлива, является наличие пульсаций в зарядно-разрядных токах аккумуляторных батарей, используемых в качестве накопителей энергии. Эксплуатация аккумуляторных батарей в режиме импульсных токов приводит к быстрой деградации их характеристик и сокращению срока службы, что обуславливает снижение надежности системы электроснабжения и увеличение себестоимости генерируемой электроэнергии. Существенным недостатком гибридных систем, построенных по известным стандартным схемам, является неэффективное использование потенциала первичной возобновляемой энергии, что особенно критично для энергетических систем, территориально расположенных в районах с суровыми климатическими условиями. В статье предложены технические решения, позволяющие устранить обозначенные проблемы. Цель: поиск и разработка технических решений, обеспечивающих повышение надежности и эффективности гибридных энергетических систем с высоким уровнем замещения топлива. Методы: математическое и компьютерное моделирование с использованием программной среды MatLab/Simulink. Результаты. Предложен новый способ построения и алгоритм управления режимами гибридных энергетических систем, обеспечивающих повышение их надежности и энергетической эффективности. Представлены результаты моделирования рабочих режимов гибридной электростанции с высоким уровнем замещения топлива, которые доказывают, что предложенный способ построения и алгоритм управления режимами обеспечивают надежное и эффективное управление балансом мощности гибридной энергетической системы во всех возможных эксплуатационных режимах. Применение двухконтурного накопителя энергии с предложенным алгоритмом управления обеспечивает снижение интенсивности отказов гибридной энергетической системы на 5,7 %, увеличение эксплуатационного ресурса аккумуляторных батарей на 50 %, повышение эффективности использования энергии возобновляемых источников на 28 % в сравнении со стандартными способами построения гибридных электростанций.

Wind Turbine Data Collection using IoT

Renewable energy resources have gained an important place in human life. It is a fact that the amount of non-renewable energy resources is decreasing rapidly, at the same time, the need for renewable energy resources increases. The history of humanity teaches us to use the resources prudently and efficiently. This can happen only with well planning and devising ways to realize the same. Even in the case of efficient use of renewable energy, the data analysis has greater value, since better the analysis, better the efficient and effective use. This paper is an outcome of making the data analysis of a wind turbine by collecting and communicating the data to the cloud server. These details can be accessed locally with the use of an LCD module, and remotely with the web browser or through a mobile app.

CO2-Preis jetzt – sozialverträglich und verursachergerecht

Abstract The urgency of effective climate action measures and the practical experience in the context of the existing European Emissions Trading Scheme (ETS) are striking arguments for the introduction of uniform prices on CO₂ emissions: as a minimum price in the ETS and as a reform of existing tax rates on fossil fuels (CO₂ tax) for heating and transport (Non-ETS). In order for CO₂ pricing not to become a mere instrument of rising government revenues, the options currently under consideration are the counter-financing of existing taxes and levies that reduces electricity prices or a per capita refund (climate bonus) for households. Both result initially in very similar distributional effects: the lower the household income, the higher the initial financial relief. Compared to the counter-financing of the EEG levy, climate bonuses are expected to have stronger rebound effects and the reduction of bureaucracy and promotion of the efficient use of renewable energy in heating and transport (sector coupling) would be waived. Thus a counter-financing, in particular the EEG levy in order to lower electricity costs, is a priority. In order to adequately address social hardships, only few socio-political accompanying measures would be needed that are largely independent of the pricing mechanism.

(Invited) Advances and Issues in Developing Salt-Concentrated Battery Electrolytes

With a worldwide trend towards the efficient use of renewable energies and the rapid expansion of the electric vehicle market, the importance of rechargeable battery technologies, particularly lithium ion batteries, has steadily increased. In the past few years, a major breakthrough in electrolyte materials was achieved by simply increasing the salt concentration in suitable salt/solvent combinations, offering technical superiority in numerous figures of merit over alternative materials. This long-awaited extremely simple yet effective strategy can overcome most of the remaining hurdles limiting the present lithium ion batteries without sacrificing manufacturing efficiency, and hence, its impact is now widely felt in the scientific community, withserious potential for industrial development. I will try to provide timely and objective information that will be valuable for designing better realistic batteries, including a multi-angle analysis of their advantages and disadvantages together with future perspectives. Emphasis is placed on the pathways to address the remaining technical and scientific issues rather than re-highlighting the many technical advantages.

Ternary Low-Temperature Molten Salt Electrolyte for Sodium Ion Batteries

To meet the increasing demand of electricity (which is forecasted to double by 2050)1 and to mitigate the climate crisis associated with using fossil fuels, renewable and clean energy sources are becoming the ultimate choices to generate electricity. Electrochemical energy storage devices such as batteries play an important role in the efficient use of renewable energy, providing an efficient and sustainable way to store energy.1,2 Beyond-lithium rechargeable batteries based on earth-abundant elements, namely sodium ion batteries (SIBs), are believed to be the alternatives for large-scale storage. Nevertheless, the commercial applications of SIBs are restricted by absence of reliable and low-cost electrolyte favouring low-temperature, high-efficiency, and reversible metal deposition/stripping. Interestingly, the newly reported molten salts containing several metal halides act as a low-cost electrolyte, which exhibits high electrical conductivity and quick electrode kinetics, and produce even better performances than ionic liquid electrolytes.3,4 Nonetheless, the conventional molten salt electrolytes normally operate at a relatively high temperature (over 260 ), which is significantly inconvenient for outdoor operation. Actually, reducing the operation temperature is not only beneficial to improving cycle life by restraining temperature-related degradation (i.e. undesired side reactions), but also profitable to using lower cost cell materials and reduce the cost of batteries fabrication. This paper reports our development of a low-temperature inorganic molten salt electrolytes with good electrochemical performances.5 The metal chloride eutectic mixture is used as electrolyte, whose melting points are dependent on its precursors and composition, so the relationship of mole ratio of metal chlorides and electrolyte’s melting points are investigated in our work. The influences of additives in chloride-based eutectic mixture are also studied, to decrease the melting point of the electrolyte. Herein, the electrochemical properties of this electrolyte are investigated in battery cells using Na metal as anode and metal fluoride cathode respectively. The battery charge /discharge behaviour and electrochemical impedance spectra (EIS) is tested using GAMRY potentiostat. Materials characterization techniques including X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM),X-ray spectroscopy (XPS) and Raman spectroscopy are used to characterise the electrode materials and to understand the effect of electrolyte on the electrode materials.

Design of Mechanically Robust Polymer Membranes for Non-Aqueous Flow Battery

Large scale grid storage is imperative for an efficient use of renewable energies. While aqueous redox flow batteries (RFBs) such as a vanadium-based aqueous RFB are relatively mature technologies for a grid storage, non-aqueous RFBs present an attractive alternative strategy for potentially providing much higher energy density. One of the key enablers for non-aqueous RFBs is mechanically robust and highly ion-conductive membranes. In aqueous RFBs, membranes can achieve high proton or anion conductivity due to water mediating their ion conduction, thus there are various high performance membranes for aqueous RFBs. On the other hand, for membranes in non-aqueous RFBs, achieving high ion conductivity while maintaining mechanical and chemical stability is a major challenge. The design principle for such membranes is poorly understood due to the complexity of the system. Our membranes are developed for a non-aqueous RFB with an alkali alloy anode technology that has the potential to achieve high energy density, high safety, low cost and long cycle life. This presentation will discuss the fundamental design principle in polymer membranes for non-aqueous RFBs and our recent efforts on the development of novel plasticized polymer membranes that simultaneously provide high conductivity and tailored mechanical modulus. In this study, mechanically robust crosslinked poly(ethylene oxide) membranes were synthesized and doped with sodium triflate and tetraglyme. The relationships between ion conductivity (reached up to 10-4-10-3 S/cm at r.t.), salt/gel content, glass transition temperature (Tg) and mechanical properties are investigated. The synthesized membranes are mechanically robust with storage modulus maintaining at ~1 MPa from -20 °C to 180 °C even saturated with tetraglyme. Furthermore, mechanically tailored novel single-ion conducting polymer electrolytes (SICPEs); block and graft copolymers of poly[(4-styrenesulfonyl) (trifluromethane-sulfonyl)imide] (poly(STF)) and poly[1-[3-(methacryloyloxy)-propylsulfonyl]-1-(trifluoromethanesulfonyl)imide] (poly(MPA)), were investigated. The SICPEs were synthesized by covalently attaching anionic moieties to the polymer backbones that only allows specific cations, such as lithium or sodium ions, to move freely and provide ionic conductivity (i.e. the transference number is close to 1) which is imperative for RFBs. These novel SCPE membranes include a membrane with a flexible polymer backbone to afford mechanical robustness and stretchability, and poly(STF) or poly(MPA) as side chains to provide single-ion conductivity. The effect of monomer type, degree of polymerization of the side chain, and different cations are also studied. The obtained polymer membrane showed 100% elongation and around 10-4 S/cm single-ion conductivity (no salt) at 30 °C after being doped with propylene carbonate. This work is funded by Dr. Imre Gyuk, Office of Electricity Delivery and Reliability, Department of Energy and the Laboratory Directed Research and Development Program of Oak Ridge National Laboratory, managed by UT-Battelle, LLC.

Optimization model of a combined wind–PV–thermal dispatching system under carbon emissions trading in China

The objective of the traditional dispatching optimization model is to find the most economical scheduling mode, while ignoring the efficient use of renewable energy. To properly arrange thermal power generation and renewable energy power generation, this paper constructs an optimization model of the combined wind–photovoltaic (PV)–thermal dispatching system under a carbon emissions trading (CET) mechanism. The contribution of this paper is twofold. First, a dispatching optimization model is proposed, which not only considers the total cost but also takes into account the impact of the renewable energy spillage rate on the dispatching system. As a factor affecting renewable energy consumption, a carbon emissions trading mechanism has also been introduced into the dispatching system. The second contribution is to develop a model for predicting the output of renewable energy generation. Then, the optimization model is applied to the auxiliary power dispatching system of the Tianzhong ±800 kV UHV DC transmission channel in Xinjiang. The results indicate that under a carbon emissions trading mechanism, thermal power generation will be limited by the carbon emissions cost, thereby reducing the total cost of the system. Optimizing the spillage rate increases the share of renewable energy in the dispatching system, resulting in a 3.5% reduction in the actual spillage rate. The proposed model alleviates the serious problem of electricity being abandoned in the existing scheduling mode and helps to realize economical low-carbon dispatching of the power system.