Efficient Energy Usage Research Articles

Nexus between energy consumption and carbon dioxide emission: evidence from 10 highest fossil fuel and 10 highest renewable energy-using economies.

The world, addressing to achieve rapid and drastic economic growth by relying on fossil fuel energy consumption, could increase already increasing level of carbon dioxide (CO2). Therefore, there is a growing consensus that environmental sustainability by using renewable energy is the only option to avoid environmental calamity. Therefore, according to the authors' best knowledge, this is the first work to look into the short and long-run nexus between economic growth, trade openness, renewable and fossil fuel energy consumption, along with gross capital formation, population growth, and life expectancy as additional variables in top 10 highest renewable energy-using (TRU) economies and top 10 highest fossil fuel-using (TFU) economies from 1991 to 2020, by employing advanced panel data econometric approach. After demonstrating cross-sectional dependency in panel data, the Westerlund cointegration test verifies the long-term link between the variables. A cross-sectional autoregressive distributed lag (CS-ARDL) econometric technique is used to show short- and long-run coefficient values. CS-ARDL estimates confirm that the economic growth, fossil fuel energy, trade openness, and gross capital formation increase carbon dioxide (CO2) emissions levels in the short run for TRU and FEU economies, except for gross capital formation for FEU economies. However, economic growth adds to CO2 emissions for only TRU economies, while fossil fuel energy consumption enhances CO2 emissions for both groups of economies in the long run. On the contrary, renewable energy reduces CO2 emissions in the short and long run, while human capital in only the short run. The inferences of this study present new intuitions and urge governments and policymakers to develop a reliable mechanism for investing capital to diversify the energy portfolio through the energy transition process to attain sustainable economic growth and promote awareness campaigns to draw the attention of human capital to environmentally friendly, clean, and green energy sources. Overall, the results recommended energy efficiency usage and ecological friendly innovative technologies to enhance and protect environmental quality.

A growth-boosting synergistic mechanism of Chromochloris zofingiensis under mixotrophy

The mixotrophic cultivation approach, consisting of heterotrophy and photoautotrophy, has been suggested as a promising strategy to reach a high growth rate and biomass productivity. However, the underlying growth-boosting mechanisms remain elusive. In this study, Chromochloris zofingiensis, a promising high-value-added astaxanthin producer, was selected to elucidate how mixotrophy benefits cellular growth. Results showed that mixotrophy yielded the highest biomass, which was significantly higher than the sum of photoautotrophic and heterotrophic cultivation, indicating a significant growth-boosting effect. The chlorophyll fluorescence and transcriptomics results confirmed that the highest biomass production under mixotrophy was attributed to a higher photosynthesis performance, decreased light damage and photorespiration, as well as significantly upregulated glucose metabolism compared to photoautotrophy. Compared to heterotrophy, mixotrophy consumed less glucose and had a lower glucose metabolic efficiency, but led to higher biomass yield. Taken together, we propose a synergistic growth-promoting mechanism between photosynthesis and glucose metabolism under mixotrophy, in which cells not only directly benefit from extra energy from exogenous organic carbon metabolism but also the reutilization of the byproduct CO2 for photosynthesis. In return, O2 evolved from photosynthesis was consumed by glucose metabolism as well. Furthermore, the coexistence of photosynthesis and glucose metabolism contributes to higher energy usage efficiency and biomass yield, correspondingly diminishing the waste and decreasing the damage. This study provides insights into the synergistic mechanism under mixotrophy and helps to better select growth strategies for commercially valuable algal species.

Enhanced blue-light excited cyan-emitting persistent luminescence of BaLu2Al2Ga2SiO12:Ce3+, Bi3+ phosphors for AC-LEDs via defect modulation

Alternating current light-emitting diodes (AC-LEDs) have received significant attention from both academia and industry due to their remarkable benefits of more compact volume, cheaper manufacturing cost, greater energy usage efficiency, and longer service life. One of the most significant challenges for AC-LEDs is the flicker effect, which is mainly caused by the unavoidable 5–20 ms dimming time. Aiming to reduce the flicker effect, we designed a series of excellent blue-light excited cyan-emitting persistent luminescence (PersL) phosphors BaLu2Al2Ga2SiO12:Ce3+, Bi3+ via defect engineering of co-doping Bi3+. Interestingly, we found that co-doping Bi3+ not only effectively enhanced the PersL intensity, but also regulated the PersL lifetime of this phosphors. As the Bi3+ co-doping concentration increases to 0.01, the τ80 value (the time when the PersL intensity decreases to 80% of the initial intensity) increases from 0.24 to 19.61 ms, which proves to be effective in compensating the flicker effect of AC-LEDs. A new method of generating white light emission during the dimming time through adding the blue-light excited cyan PersL phosphor to the original orange-red PersL phosphor was proposed and an AC-LED lamp with a decreased percent flicker of 48.15% was fabricated, which is significantly better than the other currently reported AC-LED devices based on PersL phosphors. These results demonstrate that BaLu2Al2Ga2SiO12:Ce3+, Bi3+ might be an attractive material for low-flicker AC-LEDs.

Construction 4.0 technologies and applications: a systematic literature review of trends and potential areas for development

PurposeBased on the systematic literature review, this paper aims to propose a framework of Construction 4.0 (C4.0) scenarios, identifying Industry 4.0 (I4.0) enabling technologies and their applications in the construction industry. The paper reviews C4.0 trends and potential areas for development.Design/methodology/approachIn this research, a systematic literature review (SLR) methodology has been applied, including bibliographic coupling analysis (BCA), co-citation network analysis of keywords, the content analysis with the visualisation of similarities (VOSviewer) software and aggregative thematic analysis (ATA). In total, 170 articles from the top 22 top construction journals in the Scopus database between 2013 and 2021 were analysed.FindingsSix C4.0 scenarios of applications were identified. Out of nine I4.0 technology domains, Industrial Internet of Things (IIoT), Cloud Computing, Big Data and Analytics had the most references in C4.0 research, while applications of augmented/virtual reality, vertical and horizontal integration and autonomous robotics yet provide ample avenues for the future applied research. The C4.0 application scenarios include efficient energy usage, prefabricated construction, sustainability, safety and environmental management, indoor occupant comfort and efficient asset utilisation.Originality/valueThis research contributes to the body of knowledge by offering a framework of C4.0 scenarios revealing the status quo of research published in the top construction journals into I4.0 technology applications in the sector. The framework evaluates current C4.0 research trends and gaps in relation to nine I4.0 technology domains as compared with more advanced industry sectors and informs academic community, practitioners and strategic policymakers with interest in C4.0 trends.

Containerized Microservices Orchestration and Provisioning in Cloud Computing: A Conceptual Framework and Future Perspectives

Cloud computing is a rapidly growing paradigm which has evolved from having a monolithic to microservices architecture. The importance of cloud data centers has expanded dramatically in the previous decade, and they are now regarded as the backbone of the modern economy. Cloud-based microservices architecture is incorporated by firms such as Netflix, Twitter, eBay, Amazon, Hailo, Groupon, and Zalando. Such cloud computing arrangements deal with the parallel deployment of data-intensive workloads in real time. Moreover, commonly utilized cloud services such as the web and email require continuous operation without interruption. For that purpose, cloud service providers must optimize resource management, efficient energy usage, and carbon footprint reduction. This study presents a conceptual framework to manage the high amount of microservice execution while reducing response time, energy consumption, and execution costs. The proposed framework suggests four key agent services: (1) intelligent partitioning: responsible for microservice classification; (2) dynamic allocation: used for pre-execution distribution of microservices among containers and then makes decisions for dynamic allocation of microservices at runtime; (3) resource optimization: in charge of shifting workloads and ensuring optimal resource use; (4) mutation actions: these are based on procedures that will mutate the microservices based on cloud data center workloads. The suggested framework was partially evaluated using a custom-built simulation environment, which demonstrated its efficiency and potential for implementation in a cloud computing context. The findings show that the engrossment of suggested services can lead to a reduced number of network calls, lower energy consumption, and relatively reduced carbon dioxide emissions.

KONYA TEKNİK ÜNİVERSİTESİ MÜHENDİSLİK VE DOĞA BİLİMLERİ FAKÜLTESİNE AİT BİNALAR İÇİN ENERJİ VERİMLİLİĞİNİ ARTIRMAYA YÖNELİK ÖRNEK BİR ÇALIŞMA

Dünyada ve ülkemizde artan enerji maliyetleri, fosil yakıtların tükeniyor olması, yenilenebilir enerji kaynaklarında da henüz istenen kurulu güç potansiyeline erişilememiş olması, enerjide dışa bağımlılık ve çevresel endişeler binalarda enerjinin verimli kullanımını zorunlu kılmıştır. Özellikle kamu kurum ve kuruluşlarından başlanmak üzere tüm yapılarda enerji tasarrufu yoluna gidilmesi, enerjinin verimli kullanılması ve hatta var olan enerjinin daha sonra kullanılmak üzere depolanması ülkemizin enerji verimliliği ve yönetimi konusunda üst sıralara ilerlemesine yardımcı olacaktır. Üniversitelerde enerjinin verimli kullanılması ile hem enerji maliyetlerinin üniversite bütçesi üzerindeki yükü hafifletilebilecek, hem de sürdürülebilir üniversite kriterleri için önemli bir adım atılabilecektir. Bu amaçla, bu çalışmada Konya Teknik Üniversitesi Mühendislik ve Doğa Bilimleri Fakültesi binasının (KTUN) enerji açısından mevcut durumu ortaya çıkarılmış ve enerji verimlilik potansiyeli incelenmiştir. Elde edilen sonuçlara göre, üniversitenin 2020-2021 yılı enerji tüketim değerinin sırasıyla 482 ve 502 Ton Eşdeğer Petrol (TEP) olduğu bununla birlikte yıllık CO2 salınımının 2020 yılında 135 toneşd.CO2 ve 2021 yılında 141 toneşd.CO2 olduğu belirlenmiştir. Bir başka deyişle bu rakamlar sırasıyla 1164 ton ve 1215 ton karbon ayak izine karşılık gelmektedir. Yapılan çalışmadan yola çıkılarak başta kamu kurum ve kuruluşlarında olmak üzere tüm yapılarda enerji mevzuatlarına göre enerji tasarrufu, enerji verimliliği ve yenilenebilir enerji kaynakları ile ilgili çalışmalara bir an önce başlanması ve gerekli önlemlerin alınması gerekmektedir.

ESTIMATED PARAMETERS IN THE SYSTEMS OF A SINGLE-AXIS ORIENTACIS OF A PHOTOELECTRIC MODULE

The development of "green" energy in Ukraine involves an increasingof the amount of electricity generated by photovoltaic modules (PMs). However, PMs have disadvantages associated with the inconsistency of electric generation in time due to the diurnal and annual motion of the Sun and to the shading of the modules. In order to maintain steady generation during the day and the year, there are two ways to minimize the impact of these factors.First one is to install an excess capacity which means higher cost of the solar plant and using an additional area.Second one isto apply a system of orientation PMs perpendicular to the sun's rays. 
 In the article three cases of solar panels installation are considered: usinga two-axistracking system, using aheight tracking system and anazimuth tracking system. There wasgiven the method and algorithms of calculation and analysis the parameters of theuniaxialand biaxial tracking system when installed in Kyiv.The algorithm involves calculation the coordinates of Sun in any moment of time for the considered location, pass-through and absorptive capacityof the protective glass, estimation the amount of the direct and diffuse solar radiation and their impact on the total radiation on the surface of the photoconverter. There was made an estimation of energy usage efficiency levels for the considered systemsusing the proposed algorithm.

Assessing the low-carbon city pilot policy on carbon emission from consumption and production in China: how underlying mechanism and spatial spillover effect?

The low-carbon city pilot (LCCP) policy is an important initiative for China to fulfill its international commitment to carbon emission reduction and achieve low-carbon transformation. In this context, this study investigated whether the LCCP policy of China has achieved carbon emission reduction from the production and consumption perspectives and how its underlying mechanism and spatial spillover effect. Using the panel dataset of 285 Chinese prefecture-level cities from 2003 to 2019, this study applied the staggered DID model to examine the effects and its underlying mechanism of the LCCP policy on carbon intensity (CI) and carbon emission per capita (CP). We also conducted heterogeneity and spatial spillover effect analyses using the textual quantification method and spatial DID. Our results show that the LCCP policy effectively reduced CI and CP, but these effects did not appear until the third year of implementation. The above conclusions passed a series of robustness and endogeneity tests. Reducing industrial emissions, improving technological innovation, and optimizing the efficiency of energy usage were three important mechanisms to reduce CI and CP, validating the effectiveness of the LCCP policy. Command-mandatory and voluntary LCCP policy tools achieved better results, and the LCCP policy exerted a significant emission reduction effect on second-tier pilot cities as compared to others. The carbon emission abatement of the LCCP policy has also demonstrated a spatial spillover impact on neighboring cities. This study focused on analyzing the mechanism paths and spatial spillover effects of the LCCP policy impact and provided an important decision-making reference in promoting the LCCP policy for not only China but also other developing countries. Specifically, low-carbon pilot experiences and typical cases should be refined, ways for accelerating the greening and cleaning of energy usage must be explored, and regional joint control and collaborative governance should be established to achieve China's low-carbon transformation.

Cooperative Recharge Scheme Based on a Hamiltonian Path in Mobile Wireless Rechargeable Sensor Networks

The energy problem and limited capacity of batteries have been fundamental constraints in many wireless sensor network (WSN) applications. For WSN, the wireless energy transmission technology based on magnetic resonance coupling is a promising energy transmission technology. To reduce the cost and energy consumption during charging in mobile wireless rechargeable sensor networks (MWRSNs), a cooperative mobile charging mechanism based on the Hamiltonian path is proposed in this paper. To improve the charging task interval, we study the use of a mobile charger (MC) as a mobile sink node to collect the data in this paper. Then, we used the sink and the charging sensors selected by the MC to construct the undirected complete graph. Finally, the Euclidean distance between nodes is used as the edge weight and a Hamiltonian loop is found by using the improved Clark–Wright (C-W) saving algorithm to solve the problem of charging a rechargeable sensor network. In addition to the energy usage efficiency (EUE) and the network lifetime, the average energy loss per unit time is considered as the evaluation index according to the impact of the MC on the energy consumption during charging. The simulation results show that the proposed scheme increases the average network lifetime, decreases the average energy loss per unit time, and improves the EUE.

Challenges for real-world applications of nonintrusive load monitoring and opportunities for machine learning approaches

The rapid increase of power consumption calls for efficient and effective energy usage and conservation strategies in buildings. One of the requirements of achieving such a goal is load monitoring of residential appliances. Among the available load monitoring frameworks, nonintrusive load monitoring (NILM) which is used to estimate the appliance-level power usage from the aggregated signals from smart meters, has the potential to be widely deployed. This paper presents an up-to-date review of NILM methods and the challenges existing in each step of NILM. Then this paper reviews two state-of-the-art machine learning based NILM methods including Hidden Markov Model and Deep Learning techniques. Finally, this paper discusses areas for future research and development of NILM in real-world applications, where machine learning approaches can play a more significant and even decisive role.

IoT-Orchestration based nanogrid energy management system and optimal time-aware scheduling for efficient energy usage in nanogrid

Internet of Things (IoT) has brought an immense revolution in diverse fields related to mission-critical systems including healthcare and navigation systems. We argue that the potential of IoT has not been fully exploited in the energy sector. There is a dire need to shift the traditional paradigm of mission-critical electric power architectures to IoT-enabled fully orchestrated architectures to enhance the overall performance. In this study, we present a novel IoT task orchestration architecture for efficient energy management of a nanogrid system that focuses on minimizing the use of non-renewable energy resources and maximizing the use of renewable energy resources. Since network orchestration deals with automating the interaction between multiple components involved to execute a particular service, therefore, scheduling the relevant processes within strict deadlines becomes the core pillar of the system's performance. The mission-critical systems with urgent task execution often suffer from missing task deadlines issues. To overcome this issue, we present a task scheduling algorithm that incorporates the optimized surplus time, and efficiently executes the energy management-related tasks contemplating to their types. The study utilizes sensors to obtain data from physical IoT devices, including photovoltaic (PV), Energy Storage System (ESS), and diesel generator (DG). The performance of the proposed model is evaluated using data set of nanogrid houses. The outcomes revealed that IoT-task orchestration has played a pivotal role in efficient energy management for nanogrid missioncritical systems. Furthermore, the comparison showed that the task starvation rate is reduced to 16% and 12% when compared with state-of-the-art scheduling algorithms.

Multi-objective optimal scheduling of microgrid with electric vehicles

With the increasing global attention to environmental protection, microgrids with efficient usage of renewable energy have been widely developed. Currently, the intermittent nature of renewable energy and the uncertainty of its demand affect the stable operation of a microgrid. Additionally, electric vehicles (EVs), as an impact load, could severely affect the safe dispatch of the microgrid. To solve these problems, a multi-objective optimization model was established based on the economy and the environmental protection of a microgrid including EVs. The linear weighting method based on two-person zero-sum game was used to coordinate the full consumption of renewable energy with the full bearing of load, and balance the two objectives better. Moreover, the adaptive simulated annealing particle swarm optimization algorithm (ASAPSO) was used to solve the multi-objective optimization model, and obtain the optimal solution in the unit. The simulation results showed that the multi-objective weight method could diminish the influence of uncertainty factors, promoting the full absorption of renewable energy and full load-bearing. Additionally, the orderly charging and discharging mode of EVs could reduce the operation cost and environmental protection cost of the microgrid. Therefore, the improved optimization algorithm was capable of improving the economy and environmental protection of the microgrid.

NRG4-U: a novel home energy management system for a unique loadprofile

ABSTRACT Home Energy Management Systems (HEMSs) are developed to facilitate residential energy management toward a more efficient way while enhancing the residents’ energy awareness. Within this paper, a novel non-intrusive, advisory and low-cost home eNeRGy management system FOR a Unique load profile (NRG4-U) is proposed to generate a target personalized load profile for each user to manage energy while preserving comfortable living conditions. The user is able to monitor all systems applications through a visualization dashboard. NRG4-U individual modules gradually generate a user-based profile including preferences, routines, and energy base load. Thermal and visual comfort are estimated through a fusion algorithm for better results. Occupancy and activity inference are estimated by auto-generating an energy base-load exploiting hidden Markov models without using any manual pre-processing task or ground truth. Personalized recommendations are sent to alert the users for energy saving actions while motivating them to adapt to more efficient energy usage. The main source of generating energy savings is the real time recommendations that inform the user about changing the operational states of appliances that may not be necessary at the given time, or may be functioning for excessive time. The suggested HEMS tool (NRG4-U) has been deployed in residential environments, while the experimental results demonstrate that it is a compelling tool for personalized load profile and energy awareness. Results demonstrate that using the NRG4-U HEMS can result in average monthly energy savings of 7%.

Secure Multi-Dimensional and Multi-Angle Electricity Data Aggregation Scheme for Fog Computing-Based Smart Metering System

Smart Meters (SMs) can regularly report their detailed real time electricity consumption data to utility company, which can improve the balance of electrical load and the efficiency of energy usage. However, the fine-grained electricity data reported by smart meters is easy to disclose the privacy of users. Therefore, data aggregation technology is often used to protect the privacy of users. Currently the existing data aggregation schemes cannot meet the requirement of further fine-grained analysis. In this paper, we propose a multi-dimensional and multi-angle electricity data aggregation scheme for fog computing-based smart metering system. In our proposed scheme, the smart meters use the super-incremental sequence matrix to structure and encrypt their obtained electricity consumption data; the fog nodes regularly collect and aggregate these ciphertexts of electricity consumption data by using the homomorphic Paillier cryptosystem; the control center decrypts the aggregated ciphertext to obtain multi-dimensional and multi-angle electricity data, which is accurate to the types of household appliances and their corresponding electricity angles (energy efficiency indexes). According to the security requirements, we analyze the security of our proposed scheme, which can achieve identity anonymity. Additionally, the experimental results show our scheme is efficient.

Appraisal of CO2 emission in Tunisia's industrial sector: a dynamic vector autoregression method.

The world is confronted with a slew of environmental issues, one of which is attenuating the detrimental impacts of carbon dioxide (CO2) emission-induced climate change. The ever-increasing use of energy is eroding natural resources to the point that our economic future may be jeopardized. The Tunisian economic growth indicates the excellent performance in the industrial sector as the minimum required input for these developments which necessitate additional energy consumption, resulting in increased CO2 emissions and environmental degradation. This study explores the role of energy efficiency, urbanization, economic growth, and natural gas energy usage in the industrial sector on the CO2 emissions of Tunisia. The research mainly employs the vector autoregressive model (VAR) to examine the factors driving the evolution of CO2 emissions through the industrial sector from 2000 to 2018. The findings assess that natural gas as an energy source and efficiency is crucial for reducing CO2 emissions. The study has shown the existence of the environmental Kuznets curve (EKC), which demonstrates that economic development in Tunisia has an inverted U-shape connection with CO2 emissions. The findings show that energy consumption and GDP have a considerable impact on CO2 emissions due to large-scale population changes and industrial structure alteration. In contrast, energy efficiency is a key factor in lowering CO2 emissions. Based on the study's results, the article will enable economic decision-makers and relevant authorities to develop an appropriate energy strategy for the industrial sector to safeguard environmental deterioration in the long term by lowering carbon emissions.

Global Prospects, Advance Technologies and Policies of Energy-Saving and Sustainable Building Systems: A Review

Automation, modernization, economic development and global progress depends on efficient extraction and utilization of energy. Power generation by burning fossil fuels makes various adverse impacts on the environment. Additionally, the worldwide fossil fuel reserve is limited and depleting very fast. Hence, efficient energy usage and savings are crucial to address the environmental issues to ensure sustainable development. Buildings, both commercial and residential, represent a major energy consumption sector. Approximately 40% of the total energy is reportedly consumed in the building sector. Worldwide building energy consumption, performance measuring systems and best practices, energy-saving techniques and policies are reviewed and summarized in this article. Underfloor air distribution, double-glazed windows, use of highly efficient electric motors and variable speed drives may play a great role in reducing building energy consumption. In the UK, the application of double-glazed windows in commercial buildings can save 39–53% energy. The proper maintenance of a building’s central heating system can save up to 11% energy. The automatic HVAC control system can reduce up to 20% of the building’s total heating load. Proper utilization of a VSD system in motor and building performance optimization by an ANOVA tool also proved instrumental in saving energy. Apart from this, the building codes of different countries also help to improve building performance by reducing energy consumption. This study will help building researchers and policymakers to make a framework for sustainable, green building.

Semisolid Materials Processing: A Sustainability Perspective

Sustainable development is increasing in importance with restrictions on emission and carbon footprint. Similarly, both energy and resources efficiency are required, and at the same time, cost-efficiency is required. The current paper is focusing on carbon footprint, energy usage and material use efficiency of semisolid metal casting. A detailed analysis is made on the RheoMetal process, which is benchmarked to conventional HPDC casting. The analysis includes the gating system and the importance of the use of primary or secondary material. It furthermore includes a discussion of process yield and benefits based on process capability.

Multi-Agent Real-Time Advanced Metering Infrastructure Based on Fog Computing

This effort to make the power grid more intelligent is tightly coupled with the deployment of advanced metering infrastructure (AMI) as an integral part of the future vision of smart grid. The goal of AMI is to provide necessary information for the consumers and utilities to accurately monitor and manage energy consumption and pricing in real time. Immediate benefits are enhanced transparency and efficiency of energy usage and the improvement of customer services. Although the road map toward successful AMI deployment is clearly defined, many challenges and issues are to be solved regarding the design of AMI. In this paper, a multi-agent AMI based on the fog-computing approach is presented. Architecture follows structural decomposition of AMI functionalities encapsulated in a form of local and area-specific service components that reside at the different tiers of hierarchically organized AMI deployment. Fog computing concepts provide the framework to effectively solve the problems of creating refined and scalable solutions capable of meeting the requirements of the AMI as a part of future smart grid. On the other hand, agent-based design enables concurrent execution of AMI operations across the distributed system architecture, in the same time improving performance of its execution and preserving the scalability of the AMI solution. The real-time performance of the proposed AMI solution, related to the periodic and on-demand acquisition of metering data from the connected electricity meters, was successfully verified during one year of pilot project operation. The detailed analysis of the performance of AMI operation regarding data collection, communication and data availability across the deployed pilot AMI, covering several transformer station areas with diverse grid topologies, is also presented.

PV Solar Energy Supply in Smart Cities

The application of solar energy and other renewable energy sources (wind, hydro, etc.) enables the connection of low-power electrical energy generation units to the grid. This new concept called distributed energy generation, provides opportunities to separate parts of existing distribution networks into smaller units, i.e., microgrids, which can be self-sufficient and sustainable for shorter or longer periods. In a smart grid environment, efficient usage of energy and better consumer energy supply is possible, especially in cases of failures in the main grid. This paper presents a method for the assessment of possible rooftop PV system power capacity in a smart city. Special attention will be paid to the generation units coming from renewable energy (solar) and the possibility of supplying existing loads. As a case study, the results of a hypothetical project on the possibility of PV solar energy application for the electricity supply in some cities in Serbia are presented.

An analysis of lighting design in a football stadium

Lighting is an essential element for human life. Based on the decree of the Minister of Health No.1405/Menkes/SK/XI/2002 Date: 19 November 2002 concerning the requirements and procedures for the implementation of healthy working environment. Indonesian National Standard 16-7062-2004 states that the quality of the inadequate lighting gives bad effects for visual function, the environment around the workplace, and psychological aspects that can be felt as fatigue, feeling less comfortable, less alertness until the effects of the most serious such as accident. The purpose of the study was to determine the intensity of the lighting, the spread of light, lighting design, type of lamp, light bulb conditions, efficiency of energy usage, and maintenance of the football stadium lights. This study employed a qualitative descriptive approach using the type of evaluation research. The subject of this research is Harapan Bangsa Football Stadium in Banda Aceh. Data analysis techniques are: data reduction, data display, and drawing conclusion. The findings of the research showed that the lighting intensity of Harapan Bangsa Football Stadium was 341 lux. Meaning that it was deficit of 458.8 lux of the standard set by PT Liga Indonesia (800 lux), deficit of 959 lux of the standard set by AFC (1.200 Lux), and deficit of 1659 of the standard set by FIFA 2000 Lux. Lighting in the Harapan Bangsa Football Stadium spread unevenly. The lighting intensity design of the stadium was 594 lux. The kind of light bulb used was mercury. The electric power needed to support all of lamps was 377. 200 Watt. The type of light bulb used was Philips trademark. Most of the light bulbs were broken and expired. The use of mercury lamps has not been efficient in energy use. The maintenance of the lamps has not maximized yet.