Implementing factory demand response via onsite renewable energy: a design-of-experiment approach

This paper proposes the implementation of demand response (DR) programmes in large manufacturing facilities featuring distributed wind and solar energy. Manufacturing facilities are high consumers of electric power. For this reason, these facilities usually pay exorbitant utility bills, which could be as much as $10–20 million per year. A high consumption of electricity also means that upstream fossil-fuelled power plants must release thousands of metric tonnes of carbon annually during the generation of electricity. DR contracts offer a lower utility rate in return for a load reduction during contingent events (i.e. peak hours). This paper covers the modelling and implementation of an interruptible/curtailable DR programme participated by a manufacturer that possesses onsite renewable generation units. These complementary energy resources allow the manufacturer to meet the curtailment requirements without causing any major electricity shortage that adversely affects the normal production schedule. We developed a stochastic programming model to determine the capacity of the wind turbine and solar panels that maximise the DR programme savings. The optimal solutions are derived based on central composite design methodology.     

Flow shop scheduling with grid-integrated onsite wind power using stochastic MILP

Over the last decade, manufacturing companies have identified renewable energy as a promising means to cope with time-varying energy prices and to reduce energy-related greenhouse gas emissions. As a result of this development, global installed capacity of wind power has expanded significantly. To make efficient use of onsite wind power generation facilities in manufacturing, production scheduling tools need to consider the uncertainty attached to wind power generation along with changes in the energy procurement cost and in the products’ environmental footprints. To this end, we propose a solution procedure that first generates a large number of wind power scenarios that characterise the variability in wind power over time. Subsequently, a two-stage stochastic optimisation procedure computes a production schedule and energy supply decisions for a flow shop system. In the first stage, a bi-objective mixed integer linear programme simultaneously minimises the total weighted flow time and the expected energy cost, based on the generated wind power scenarios. In the second stage, energy supply decisions are adjusted based on real-time wind power data. A numerical example is used to illustrate the ability of the developed decision support tool to handle the uncertainty attached to wind power generation and its effectiveness in realising energy-related objectives in manufacturing.     

风、光、油互补控制器的设计

本文设计开发的一款基于风、光、油互补的充电控制器,可以实现风能和光能转化为蓄电池电能,在无风、无光照的条件下,且蓄电池的能量不足,可以启动油机进行发电,并对蓄电池进行充电。从而实现对可再生能源的充分利用,在保障设备供电的前提下,最大限度的节省燃油。     

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     

我国中长期发电供应能力研究

结合我国能源资源储量、禀赋特点和能源发展相关政策,对我国中长期发电供应能力进行了全面的分析,包括燃煤发电、水电、核能发电、风力发电、太阳能发电、生物质能发电和天然气发电的供应能力。在此基础上,以社会总体成本最小为原则,对我国中长期电源结构调整进行了研究,同时研判了我国中长期电源发展布局。     

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.     

Technology assessment for clean energy technologies: The case of the Pacific Northwest

This study presents a technology assessment for clean power generation in the Pacific Northwest. Our goal is to incorporate clean production principles into the evaluation process for power alternatives. Two types of technologies are considered: one is for a renewable energy source (wind) and the other is for a traditional, fossil fuel based energy source (coal). The Analytical Hierarchy Process is used to assess the feasibility of both the wind energy and clean burning coal energy technologies. Criteria such as location, cost, feasibility, and availability are used for evaluations. For the wind energy, cost was determined to be the most important criterion when making a technology decision. For the SO₂ emissions technology, the regenerative process was determined to be the best technology to scrub SO₂ emissions from the air. Additionally, efforts towards renewable energy in Oregon should continue. Both federal and state governments offer tax credits that can help mitigate costs and facilitate the adoption of renewable energy options for power companies.     

Economic feasibility analysis of a solar energy and solid oxide fuel cell-based cogeneration system in Malaysia

The current study presents a concept of a cogeneration system integrated with solar energy and solid oxide fuel cell technology to supply electrical and thermal energy in Malaysia. To appraise the performance, the system is analysed with two case studies considering three modes of operation. For the case-1, typical per day average electricity and hot water demand for a single family have been considered to be 10.3 kWh and 235 l, respectively. For the case 2, electricity and hot water demand are considered for the 100 family members. Energy cost, payback period, future economic feasibility and the environmental impact of the system are analysed for both cases using an analytical approach. The overall system along with individual component efficiency has been evaluated, and the maximum efficiency of the overall system is found to be 48.64 % at the fuel cell operation mode. In the present study, the proposed system shows 42.4 % cost effectiveness at higher load. Energy costs for case-1 and case-2 have been found to be approximately $0.158 and $0.091 kWh^?1, respectively, at present. Energy costs are expected to be $0.112 and $0.045 kWh^?1 for the case-1 and case-2, respectively, considering future (i.e. for the year 2020) component cost.     

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。     

燃料电池分布式供能技术发展现状与展望

燃料电池作为一种清洁高效的发电方式,兼具效率高、排放低、安全无噪音等优点,是分布式供能领域的一项重要技术。燃料电池既可以利用传统煤炭、天然气,也可以融合可再生能源实现削峰填谷。在传统煤电领域,散煤的利用是环境污染的重要来源,通过直接碳燃料电池技术,有望解决散煤利用效率低下、污染严重的问题。联合天然气管网,基于燃料电池的微型热电联供系统可实现能源的梯级利用,相比传统的热电分供模式可大大提高能源利用效率。同时,电解池作为燃料电池的逆过程,可将可再生能源富余电力转化为化学能进行储存,实现"三弃"电力的有效转化,在可再生能源的分布式供应系统中具有广阔的发展前景。     

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.     

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.     

超临界二氧化碳循环发电技术应用

超临界二氧化碳循环可应用于火力发电、核能发电、太阳能热发电等多种发电技术领域,作为新型的动力循环系统替代目前广泛使用的汽轮发电机组或燃气轮机发电机组。在进入商业化应用之前,需要对超临界二氧化碳循环技术在各种应用场景下的优势及其潜在的社会和经济效益进行探讨。通过分析超临界二氧化碳循环的特点和优势,探索其与化石能源、核能、太阳能、生物质能、余热等各种热源相结合的可行性,提出多种发电系统方案,可为今后超临界二氧化碳循环的商业化应用提供参考。随着超临界二氧化碳循环技术不断成熟,设备成本进一步降低,其系统简化、结构紧凑、效率高等优势将更加突显。     

Dust sensor based on luminescent glazing for control of photovoltaic panels cleaning

The installation of photovoltaic panels in dusty areas affects their efficiency by the accumulation of dust on glazing surfaces. The cleaning of the dusty panels allows recovering the maximum efficiency. However, it increases the cost of operating and maintenance for photovoltaic installations, a compromise between the reduction in the annual cleaning cost and the improvement solar energy production is obtained with implementation of a dust sensor. By this study, for a first time a dust sensor is developed by using luminescent glazing material with embedded photocells on borders. The dust deposited on sensor is detected from photogenerated current from the photocell integrated on the edges of a luminescent glass plate of 10 × 10 cm² area. The optical and electrical characterization revealed that the generated photocurrent from the sensor output increases of 9 µA when dusts accumulation shading is widen by 10%. This new principal for dust sensors could be applied to monitor photovoltaic power plant installations for maximizing energy production from solar renewable source in dusty environment as like Saharan regions. In order to start the cleaning cycle of the photovoltaic modules, the signal generated by the dust sensor is amplified by a Darlington analog circuit which assures the relay control for operating of a direct current pump.     

An Integrated Approach Toward Renewable Energy Storage Using Rechargeable Ag@Ni0.67Co0.33S‐Based Hybrid Supercapacitors

Self‐powered charging systems in conjunction with renewable energy conversion and storage devices have attracted promising attention in recent years. In this work, a prolific approach to design a wind/solar‐powered rechargeable high‐energy density pouch‐type hybrid supercapacitor (HSC) is proposed. The pouch‐type HSC is fabricated by engineering nature‐inspired nanosliver (nano‐Ag) decorated Ni_0.67Co_0.33S forest‐like nanostructures on Ni foam (nano‐Ag@NCS FNs/Ni foam) as a battery‐type electrode and porous activated carbon as a capacitive‐type electrode. Initially, the core–shell‐like NCS FNs/Ni foam is prepared via a single‐step wet‐chemical method, followed by a light‐induced growth of nano‐Ag onto it for enhancing the conductivity of the composite. Utilizing the synergistic effects of forest‐like nano‐Ag@NCS FNs/Ni foam as a composite electrode, the fabricated device shows a maximum capacitance of 1104.14 mF cm^?2 at a current density of 5 mA cm^?2 and it stores superior energy and power densities of 0.36 mWh cm^?2 and 27.22 mW cm^?2, respectively along with good cycling stability, which are higher than most of previous reports. The high‐energy storage capability of HSCs is further connected to wind fans and solar cells to harvest renewable energy. The wind/solar charged HSCs can effectively operate various electronic devices for a long time, enlightening its potency for the development of sustainable energy systems.     

Highly Flexible and Efficient Solar Steam Generation Device

Solar steam generation with subsequent steam recondensation has been regarded as one of the most promising techniques to utilize the abundant solar energy and sea water or other unpurified water through water purification, desalination, and distillation. Although tremendous efforts have been dedicated to developing high‐efficiency solar steam generation devices, challenges remain in terms of the relatively low efficiency, complicated fabrications, high cost, and inability to scale up. Here, inspired by the water transpiration behavior of trees, the use of carbon nanotube (CNT)‐modified flexible wood membrane (F‐Wood/CNTs) is demonstrated as a flexible, portable, recyclable, and efficient solar steam generation device for low‐cost and scalable solar steam generation applications. Benefitting from the unique structural merits of the F‐Wood/CNTs membrane—a black CNT‐coated hair‐like surface with excellent light absorbability, wood matrix with low thermal conductivity, hierarchical micro‐ and nanochannels for water pumping and escaping, solar steam generation device based on the F‐Wood/CNTs membrane demonstrates a high efficiency of 81% at 10 kW cm^?2, representing one of the highest values ever‐reported. The nature‐inspired design concept in this study is straightforward and easily scalable, representing one of the most promising solutions for renewable and portable solar energy generation and other related phase‐change applications.     

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.     

蒸发冷却空调与风光互补发电结合使用的可行性分析

夏季,为给户外场所降温并节约电能使用,提出利用蒸发冷却空调与风光互补发电相结合的方式。本文分别介绍了这两项技术的发展现状、原理及特点,并通过风洞模拟自然界风力带动风车发电,再与光伏板进行互补发电实验,得出其互补发电功率为166.4W,能够带动一台额定功率为170W的蒸发式冷风扇平稳运转。这两项技术的有效结合是一种绿色、低碳、环保的降温和能源利用方式。     

能源互联网背景下的微电网能量管理分析

能源互联网背景下,可再生能源并网规模日益扩大。由于可再生能源发电功率具有很强的随机性,电力系统运行中出现了所谓“双侧随机问题”,影响安全稳定运行。如何对各种可再生能源进行经济有效的能量管理,是实现能源互联网的关键技术之一。为实现微电网运行的整体优化,对包含各种分布式电源的微电网,建立以综合发电成本最低、环境效益最好作为优化目标的多目标优化模型。利用遗传算法,进行能量管理的优化研究。以联网运行的含有多种分布式电源的微电网为算例进行仿真计算,仿真结果表明了优化模型及算法的有效性。