Spatial optimization of biomass power plant site using fuzzy analytic network process

Electricity has a significant role in the sustainable development of societies. Traditional methods of generating electricity face several challenges. The ever-increasing demand for electricity generation on the one hand, and the lack of adequate resources for fossil fuels on the other, has led to the use of renewable energy. Biomass is a renewable energy supply that can be used in electricity generation for a sustainable environment. This study aims to introduce a multi-criteria decision-making framework which integrates a geographical information system with a fuzzy analytic network process together with weighted linear combination to optimize the location of a biomass power plant in Guilan Province, Iran. For this purpose, the environmental and socioeconomic factors were identified, and the main contributing criteria were selected. The results showed that about 27.73 and 41.06% of the region has high or moderate suitability, respectively, for constructing a biomass power plant. In addition, a sensitivity analysis was performed to investigate the robustness of the outcomes of decision making by changing the weighting of the criteria. Results indicated that the ranking of alternative locations is independent of the weights chosen.     

Optimal site selection for solar power plants using multi-criteria evaluation: A case study from the Ayranci region in Karaman,Turkey

Currently, coal, oil and natural gas are mainly used for energy in most countries. These sources, called fossil fuels, are not renewable. Fossil fuels are limited, and their reserves are steadily decreasing. This situation causes the prices to rise constantly. On the contrary, renewable energy is clean, economical and unlimited. Turkey has a very high potential for renewable energy, and the Turkish government has made significant reforms for solar energy investments over the last decade. Site selection for solar power plants is a critical issue for large investments because of quality of terrain, local weathering factors, proximity to high transmission capacity lines, agricultural facilities and environmental conservation issues. Multi-criteria evaluation is a tool that allows one to choose the best criterion among multiple and offer a structure with a wide range of applications. In this paper, the ideal locations for solar power plant were selected using the geographic information system and analytic hierarchy process which is one of the multi-criteria evaluation methods. The resulting land suitability was grouped into three categories: low suitable, suitable and best suitable using an equal interval classification method. Consequently, 15,550 ha or 6.23% of the evaluated region was determined as the best suited areas for solar power plants.     

Bottlenecks and Countermeasures of High-Penetration Renewable Energy Development in China

China has become the world’s largest producer and consumer of energy, and ranks first in its wind and solar power installation capacity. However, serious wind and solar curtailment in China has significantly hindered the development and utilization of renewable energy. To address problems in the consumption of renewable energy, this paper analyzes four key factors affecting the capacity of power generated from renewable energy sources: power balance, power regulation performance, transmission capacity, and load level. Focusing on these bottlenecks, we propose seven solutions: centralized and distributed development of renewable energy, improving the peak-load regulation flexibility of thermal power, increasing the proportion of gas turbines and pumped-hydropower storage, construction of transmission channels and a flexible smart grid developing demand response and virtual power plants, adopting new energy active support and energy storage, and establishing appropriate policies and market mechanisms. The Chinese Government and energy authorities have issued a series of policies and measures, and in the past three years, China has had remarkable achievements in the adoption of renewable energy. The rate of idle wind capacity decreased from 17% in 2016 to 7% in 2018, and that of solar decreased from 10% in 2016 to 3% in 2018.     

Optimizing Decision-Making of A Smart Prosumer Microgrid Using Simulation

Distributed renewable energy sources offer significant alternatives for Qatar and the Arab Gulf region’s future fuel supply and demand. Microgrids are essential for providing dependable power in difficult-to-reach areas while incorporating significant amounts of renewable energy sources. In energy-efficient data centers, distributed generation can be used to meet the facility’s overall power needs. This study primarily focuses on the best energy management practices for a smart microgrid in Qatar while taking demand-side load management into account. This article looked into a university microgrid in Qatar that primarily aimed to get all of its energy from the grid. While diesel generators are categorized as a dispatchable distributed generation with energy storage added to handle solar radiation from the sun and high grid power operating costs in the suggested scenario, wind turbines and solar Photovoltaic (PV) are classified as non-dispatchable distributed generators. The resulting linear math issues are assessed and displayed in MATLAB optimization software using a mixed-integer linear programming (MILP) strategy. According to the simulation results, the suggested energy management strategy reduced the university microgrid’s grid power costs by 38.8%, making it an affordable solution which is somehow greater than the prior case scenario’s 23% savings. The installed solar system capacity’s effects on the economy, society, and finances were also assessed, and it became clear that the best option for the smart microgrid was determined that would be 325 kW of solar PV, 25 kW of wind turbine, and 600 kW of diesel generators, respectively. Given the current situation, university administrators are urged to participate in distributed generators and adopt cutting-edge designs for energy storage technologies due to the significant environmental and financial benefits.     

Sustainable multi-period electricity planning for Iskandar Malaysia

This paper presents the current situation and projected planning of the electricity generation sector for Iskandar Malaysia by implementing a model to optimise the cost, utilise the usage of available renewable energy sources, and achieve carbon dioxide reduction targets. This Mixed Integer Linear Programming model was developed with the main objective of minimising the total cost of electricity generation, taking into consideration energy demand, reserve margin, electricity generation, peak and base generation, resource availability, and CO₂ emission. Data for the year 2013 were forecasted until 2025 to illustrate the analysis for this study, and are represented via four scenarios. This optimal model is capable of balancing types of fuel and switching coal plants to natural gas power plants. It also enhances the use of renewable energy (RE) to meet CO₂ emission targets. The model is further integrated with several other considerations related to energy systems, such as suitability of power plants as peak or base plants, RE resource availability, intermittency of solar power, losses during transmission, fuel selection for biomass, decision to retrofit existing coal power plant to NG power plant, and construction lead time of power plants. The results for this study determined that the optimal scenario is Scenario 3 (CS3). This research proves that Iskandar Malaysia can reduce CO₂ emission by 2025 via utilisation of RE. This model is generic and can be applied to any case study, which would be useful for assisting government policy-making.     

Optimal operation of a distributed energy generation system for a sustainable palm oil-based eco-community

The palm oil industry potentially can be environmentally sustainable through utilizing the vast availability of biomass residues from palm oil mills as renewable energy sources. This work addresses the optimal operation of a combined bioenergy and solar PV distributed energy generation system to meet the electricity and heat demands of an eco-community comprising a palm oil mill and its surrounding residential community. A multiperiod mixed-integer linear programming planning and scheduling model is formulated on an hourly basis that optimally selects the power generation mix from among available biomass, biogas, and solar energy resources with consideration for energy storage and load shifting. A multiscenario approach is employed that considers scenarios in the form of many possible weather conditions and various energy profiles under varying mill operation modes and residential electricity consumption. The proposed approach is demonstrated on a realistic case study for a palm oil mill in the Iskandar Malaysia economic development region. The computational results indicate that biomass-based resource is the preferred renewable energy to be implemented due to the high cost associated with solar PV. As well, load shifting and energy storage can be feasibly deployed for demand peak shaving particularly for solar PV systems.     

Line-focusing concentrating solar collector-based power plants: a review

Concentrated solar power (CSP) plant is an emerging technology among different renewable energy sources. Parabolic trough collector (PTC)-based CSP plant, using synthetic or organic oil as a heat-transfer fluid, is the most advanced technology. About 87 % of the operational capacities of CSP plants worldwide are based on PTC technology. Direct steam-generating linear Fresnel reflector (LFR) systems have been developed as a cost-effective alternative to PTC systems. Line-focusing concentrating solar collectors (PTC and LFR), with single-axis tracking, are simple in design and easy to operate. Prior to the detailed design of a CSP plant, it is necessary to finalize type of the solar field, type of the power-generating cycle, overall plant configuration, sizing of the solar field and the power block, etc. The optimal design of a CSP plant minimizes the levelized cost of energy for a given site. In this paper, a detailed review of important design parameters which affect the design of line-focusing concentrating solar collector-based power plants is presented. This includes parameters for solar collector field design, receiver, heat-transfer fluid, thermal energy storage, power-generating cycle, sizing and configuration of the plant, etc. This review may provide a reference for designing CSP plants. Future research directions are also identified.     

Impact of renewable energy on rural electrification in Malaysia: a review

Malaysia is rich in renewable energy (RE) resources. Hybrid systems of these resources can contribute strongly to the electrification and sustainable development of rural areas that do not have access to electricity grids. The integration of the generation of hybrid renewable power in remote and rural areas supplies the required power demand and mitigates emissions. Thus, this study reviews the latest literature (theses, journals articles, and conference proceedings) on the need for electricity in remote rural communities, on hybrid RE systems, on environmental impact, and on economic regulation in Malaysia. Power in this country is mainly generated by fossil fuels that emit high concentrations of greenhouse gases. Thus, RE is a potential alternative for to electrify rural areas, to meet current and future energy demands, and to mitigate emissions. Moreover, Malaysia has pledged to reduce its carbon-emission intensity by a maximum of 40 % (2005 level) by the year 2020. Therefore, the implementation of RE technologies in this country is significantly aided by RE projects, research and development activities, technologies, energy policies, and future direction. This review concludes that solar, wind, hydro, and biomass energy, as well as a hybrid of these, can effectively electrify rural areas.     

Significance of demand response in light of current pilot projects in China and devising a problem solution for future advancements

The electric power sector significantly contributes to China's economic growth. However, rapid industrialization and urbanization have led to energy shortage problems. More than 70% of customers' demand is fulfilled by fossil fuel sources that threaten the environment. The rapid increase in demand and the need for decarbonization has forced China to work on demand-side management (DSM) to fulfill the power needs of the country. DSM is receiving much importance in China over the past few years. However, it is still in the early phases of development in comparison to other developed countries. At first, this paper points out the need for demand response, which is an aspect of the DSM, for maintaining power system stability and integrating variable renewable energy resources such as wind (on-shore and off-shore) and solar (photovoltaic and concentrated solar power). Then, it assesses China's power sector reforms and changes in demand response policies over the period to promote demand response programs. It also reviews the current demand response pilot projects in China, identifies technical and policy barriers in implementing these projects and proposes recommendations to make it successful across the whole country.     

Green energy?

The UK gets nearly all its energy from the fossil fuels (coal, oil, gas etc.) and nuclear power, approximately 15% being consumed in the form of electricity. It is now well known that the burning of fossil fuels is accompanied by atmospheric pollution in the form of acid rain, ozone depletion and the greenhouse effect. Renewable energy sources, e.g. wind, solar, tidal, wave, hydroelectric and geothermal power do not at present contribute significantly to the UK energy supply and are also accompanied by adverse effects on the environment. The best hope for meeting future energy needs may lie in containing energy consumption, increased generation efficiency and an expanded nuclear power programme. The author discusses the problems of acid rain and the greenhouse effect and describes several forms of renewable energy: wind energy, solar energy, tidal power, wave power, hydroelectricity, biomass geothermal power and nuclear power     

Application of fuzzy VIKOR and environmental impact analysis for material selection of an automotive component

Material selection is a complex process, since the process includes many criteria, determination of criteria weight and the most important factor is that the selection of appropriate criterion. The last factor indicates that the criterion must be selected in a manner, such that the selection based upon the known material parameters and the requirements of the application. Therefore the material selection can be done using MCDM (Multi Criterion Decision Making) methods. Since the inputs provided by the decision maker in linguistic manner, there is a possible chance of getting incomplete problems. So in order to overcome the problem, the inputs could be provided as fuzzy numbers. Since fuzzy set represents the uncertainty in human perceptions. In this paper, VIKOR (VlseKriterijumska Optimizacija I Kompromisno Resenje in Serbian, means Multicriteria Optimisation and Compromise Solution) has been used a MCDM tool for the selection of alternate material for instrument panel used in electric car and in order to evaluate this selection process in fuzzy environment, fuzzy based VIKOR is used. In addition to the fuzzy VIKOR method, the environmental impacts are also considered and compared for the four materials. The results achieved in both the assessment, showed that Polypropylene could be an alternate material for the instrument panel. The objective of this study is to develop a rational method to select the best material for an application based upon known material parameters and the requirements of the application.     

我国太阳能光伏产业现状及未来展望

太阳能光伏发电是可再生能源利用的重要形式,也是我国目前重点发展的、为数不多的具有全球竞争力的战略性新兴产业之一。本文详细分析了太阳能光伏产业国内外发展现状及未来趋势,分析了我国太阳能光伏产业现状和存在的问题,对光伏产业的健康发展提出了若干建议并对光伏产业的未来发展进行了展望。     

基于太阳能热化学的分布式供能系统热力学性能及碳排放分析

分布式供能系统临近用户,具有灵活消纳可再生能源的优势。集成太阳能与清洁燃料互补的分布式供能系统,旨在实现太阳能与燃料的高效互补利用。提出了基于太阳能热化学的分布式供能系统,该系统集成了太阳能热化学转化与分布式冷热电联供系统,将太阳能与甲醇以热化学的形式进行源头互补,把太阳能转化为合成气燃料化学能,进而通过内燃机发电机组和余热回收单元输出冷、热、电产品,以满足用户的负荷需求。通过数值计算的方法,对所集成的系统开展了热力学性能及CO₂排放性能分析,研究了设计工况及变工况下运行性能,结果表明所集成的太阳能与燃料热化学互补供能系统具有显著的节能减排优势。     

Sustainable Supplier Selection Model in Supply Chains During the COVID-19 Pandemic

As global supply chains become more developed and complicated, supplier quality has become increasingly influential on the competitiveness of businesses during the Covid-19 pandemic. Consequently, supplier selection is an increasingly important process for any business around the globe. Choosing a supplier is a complex decision that can result in lower procurement costs and increased profits without increasing the cost or lowering the quality of the product. However, these decision-making problems can be complicated in cases with multiple potential suppliers. Vietnam's textile and garment industry, for example, has made rapid progress in recent years but is still facing great difficulties as the supply of raw materials and machinery depends heavily on foreign countries. Therefore, it is extremely important for textile and garment manufacturing companies in Vietnam to implement an effective supplier evaluation and selection process. While multicriteria decision-making models are frequently employed to assist with supplier evaluation and selection problems, few of these models consider the problem under the condition of a fuzzy decision-making environment. The aim of this paper is to create a hybrid MCDM model using the Fuzzy Analytical Hierarchy Process (FAHP) model and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to assist the supplier selection process in the garment industry in a fuzzy decision-making environment. In this study, the FAHP method is used to evaluate the performance and the weight of each criterion. TOPSIS is then used to rank all potential suppliers. The proposed model is then applied to a real-world case study to demonstrate both the process of calculation as well as its real-world applicability. The results from the case study provide empirical evidence that the model is feasible. The proposed approach can also be used in combination with other MCDM models to better support decision makers and can be modified to be applied in similar supplier selection processes for different industries.     

Intelligent energy management control for independent microgrid

This work presents a new adaptive scheme for energy management in an independent microgrid. The proposed energy management system has been developed to manage the utilization of power among the hybrid resources and energy storage system in order to supply the load requirement based on multi-agent system (MAS) concept and predicted renewable powers and load powers. Auto regressive moving average models have been developed for predicting the wind speed, atmospheric temperature, irradiation, and connected loads. The structure proposed in this paper includes renewable sources as primary source and storage system as secondary source. A wind generator and solar PV array system together acts as primary source, which supplies power to the local load most of the time in this energy management strategy. When they fail to meet the load demand, the secondary source present in the system will assist the primary source and help to attain the goal of satisfying load demand without interruption. If the primary source and secondary source together are not able to meet the load demand then load shedding will be executed according to the priority set. Thus the developed MAS algorithm co-ordinates the hybrid system components and achieves energy management among renewable energy sources, storage units, and load under varying environmental conditions and varying loads. STATCOM based compensation has been implemented to balance the reactive power demand and to mitigate the voltage fluctuations and harmonics on the AC bus. The proposed microgrid has been simulated with MAS concept in Matlab/Simulink environment. The results presented in this paper show cases the effectiveness of the proposed energy management controller.     

风光储联合发电运行技术研究

随着能源需求的日益增长和新能源的快速发展,利用风能、太阳能的发电技术已经逐步成熟,且在电网中的渗透率也在不断提高。为弥补风能、太阳能发电所带来的功率不稳定、电能质量低等问题,有必要对风能、太阳能、储能联合发电进行深入研究。文中依据简单平抑方法、考虑一定约束的平抑方法、考虑功率预测与人工智能的平抑方法对储能的平抑控制策略进行了归纳总结。在储能平抑风光波动的研究中滤波算法是最为常见的方法,加入一定的约束会使平抑效果更佳,储能平抑配合精准的预测使整个系统更加平滑。多储能技术混合可以发挥各储能技术优越性。加入储能装置的风光储互补系统可以有效降低原风光互补系统对电网的不利影响。可以在更高程度上平滑风光发电系统的输出特性,增加电网对可再生能源的吸收接纳程度,取得良好的经济和社会效益。     

Cellulose‐Based Nanomaterials for Energy Applications

Cellulose is the most abundant natural polymer on earth, providing a sustainable green resource that is renewable, degradable, biocompatible, and cost effective. Recently, nanocellulose‐based mesoporous structures, flexible thin films, fibers, and networks are increasingly developed and used in photovoltaic devices, energy storage systems, mechanical energy harvesters, and catalysts components, showing tremendous materials science value and application potential in many energy‐related fields. In this Review, the most recent advancements of processing, integration, and application of cellulose nanomaterials in the areas of solar energy harvesting, energy storage, and mechanical energy harvesting are reviewed. For solar energy harvesting, promising applications of cellulose‐based nanostructures for both solar cells and photoelectrochemical electrodes development are reviewed, and their morphology‐related merits are discussed. For energy storage, the discussion is primarily focused on the applications of cellulose‐based nanomaterials in lithium‐ion batteries, including electrodes (e.g., active materials, binders, and structural support), electrolytes, and separators. Applications of cellulose nanomaterials in supercapacitors are also reviewed briefly. For mechanical energy harvesting, the most recent technology evolution in cellulose‐based triboelectric nanogenerators is reviewed, from fundamental property tuning to practical implementations. At last, the future research potential and opportunities of cellulose nanomaterials as a new energy material are discussed.     

Comparative analysis of energy resources

This paper examines the problems encountered by a growing demand for energy consumption and a dwindling reserve of conventional energy sources Development of alternative clean energy sources should be vigorously pursued in order to improve or maintain the quality of life. The search for new energy sources has indicated the need for developing approaches to evaluate feasibility and competitiveness of the alternative sources. Frequently mentioned as alternative energy sources are wind power, water power, tidal power, coal, fission energy with or without breeders, geothermal energy, ocean thermal energy conversion, low temperature solar energy, solar power through photosynthesis and solar electric: generation. Factors considered in comparing these energy sources are given. An illustration based on United States energy consumption rates and available energy resources provide revealing information about future directions in energy production.

Requirements for economic comparative models are discussed and an example is given.     

Regenerative Energie aus Solarstrahlung und aus dem atmosphärischem Temperaturgefälle

We discuss several methods to extract renewable energies for thermal power plants from solar radiation and from the atmospheric temperature gradient. Emphasis is on the thermodynamical aspect. We recommend for all methods: construction on the slope of a mountain, working substance air; in particular for a solar power plant: mounting of the turbine on top; and in particular for a power plant basing on the atmospheric temperature gradient: isothermic compression by a compressor mounted on top and isothermic expansion by a turbine mounted on bottom.     

Maintenance policy selection in manufacturing firms using the fuzzy MCDM approach

In manufacturing firms, there is a critical need for proper maintenance of manufacturing facilities. The maintenance process enhances customer satisfaction and reliability of the products, and increases the profit of the manufacturer. Therefore, a proper maintenance policy selection is a critical issue for manufacturers, as an inefficient maintenance policy affects not only the direct cost of the firm but also the other aspects. In the present study, maintenance policy selection at the level of the firm rather than the equipment level is shown, and for selection various criteria have been identified. The presented work not only provides the best alternatives but also provides an alternative ranking, which facilitates decision-makers in choosing alternatives according to their constraints. These selection criteria are different in nature, as some give a crisp value, whereas others are defined in linguistic terms. To select the appropriate maintenance policy, a distance-based fuzzy multicriteria decision-making (MCDM) approach has been employed. The proposed method provides the means for integrating the economic figure of merit with the strategic performance variables. The MCDM approach is efficient in incorporating data, in the form of linguistic variables, triangular fuzzy numbers, and crisp numbers, into the evaluation process of maintenance policy alternatives. A comprehensive example illustrates the application of the distance-based fuzzy MCDM approach.