Optimize Energy Use Research Articles

Management Challenges and Opportunities for Energy Cloud Development and Diffusion

The use of emerging technologies such as cloud computing, Internet of Things, and Big Data, is increasing as tools to assist the management of data and information related to energy systems grow. This allows for greater flexibility, scalability of solutions, optimization of energy use, and management of energy devices. In this sense, the objective of this research is to present the basic elements and requirements for the energy cloud and its management and discuss the main management challenges and opportunities for the development and diffusion of the energy cloud. This study was based on a systematic review carried out to identify the elements that compose the energy cloud and what is necessary for its management, and to list the challenges and opportunities that may be explored by researchers and practitioners. The results show that the layout for the energy cloud and its management can be structured in layers and management support blocks’ format. It was found that 70 basic elements make up the main layers and 36 basic elements make up the management support blocks. The findings of this article also provide insights into the technical, scientific, and management development necessary for the evolution of energy systems toward the cloud computing environment.

Structural conflict under the new green dilemma: Inequalities in development of renewable energy for emerging economies

Climate Change related concerns affect multiple international and national policy forefronts. Globally, conflicts over renewables industry between the developed and emerging economies have affected the provision of green goods-thus slowing the overall welfare of global environmental governance. This article argues that the above phenomenon is a new form of green dilemma which arises from the long-lasting issue of balancing environmental protection and economic gains. It further tracks the historical evolutionary change of green dilemma, from version 1.0 to 2.0 to the current avatar of Green Dilemma 3.0. By developing the Green Dilemma Framework, the article aims to uncover the logic underlying the industrial policies and trade conflicts between the developed and emerging economies in their energy transitions. Utilizing the US vs China and US vs India conflicts in the solar PV industries as the two group of cases, the key feature of Green Dilemma 3.0 is illustrated as the conflict over status and control of the global division of labor in the new energy industry. This article offers a novel perspective on global inequality by deconstructing the unequal global production system that can act to restrict the optimization of energy use and production in tackling climate change and thus successively hindering global environmental governance in its realization of optimal results. Underneath global climate change governance, there is an unequal global production network and political system, and both these follow a core, semi-periphery, and periphery distribution of power structure. We argue that the inequality of global production system suppresses the effects of subsidy competition and erodes the economic foundation of global climate governance.

A Preliminary Analysis of Energy Consumption in Academic Buildings

Current technological advancement and pressing environmental issues emphasise the need for better energy management to minimise wasting depleting resources. Energy consumption can generally be divided into two, namely residential and commercial. Commercial energy consumption involves commercial buildings that include, but not limited to, banks, hotels, offices and academic buildings. While awareness on optimising energy use is more evident now, there is still a lack of understanding of the parametric values that are crucial in analysing the energy consumption of a commercial building that is unique to the building’s function. This study aims to identify the relationships between a number of identified variables and the overall building energy consumption. The study intended to become the preliminary case study in identifying the correlations between selected variables and energy consumption. The analysis was carried out using covariance matrix on identified variables such as electricity consumption, user traffics, the maximum outdoor temperature of the month and the academic term. This study identified positive relationships between electricity consumption, user traffic, and maximum outdoor temperature.

Performance of a new solar water heater design with natural circulation

ABSTRACT A year-round performance of a new design of a solar water heater with natural circulation was studied experimentally at Amman, Jordan (latitude of 32°N and the altitude of 985 m above sea level). The measured parameters were temperatures of ambient, water inlet, and outlet of the collector; the temperature of the heated water stored in the storage tank, and the solar incident radiation on the tilted angle. The obtained results showed that the performance of the solar water heater depended highly on both of the flow rate through the collector and the solar tilted incident radiation. A typical day analysis of the system showed a high solar collector efficiency especially around mid-day (a time when it receives the highest solar energy). Also, data revealed that the maximum total useful heat gain without water consumption was 200.55 MJ recorded during September, while the maximum useful heat gain with water consumption was 304.81MJ recorded during October. Meanwhile, the maximum daily efficiency without water consumption was 54% recorded during May, while the maximum daily efficiency with consumption was 55% recorded during September. Based on the results of this study, the new design of a solar water heater can be recommended for the optimal use of solar energy to heat water.

Technology Management Leading to a Smart System Solution Assuring a Decrease of Energy Consumption in Recreational Facilities

Improvement of the energy efficiency of public buildings appears to be one of the best ways to simultaneously reduce energy consumption as well as the negative impacts on the environment. The work is dedicated to the analysis of modernization process of the energy system in a sports facility in a way leading to design of smart energy system. The proposed solution, being a specific case study, offers optimal use of energy in the facility, significantly reducing the demand for energy derived from fossil fuels (heat providers and conventional power plants). The project, on its first step, consists of recovering energy from sewage that usually is irretrievably lost. This option allows to achieve the assumed goals simultaneously optimizing the investment costs. The proposed solution mitigates air pollution and harmful gas and dust emissions to the atmosphere, and contributes to an increase of both the attractiveness and competitiveness of the area in which the sports facility is located. The next step will be further automation of the system and intelligent synchronization of time-dependencies of the processes.

Environmental evaluation and optimization of energy use and greenhouse gases mitigation for farm production systems in Mashhad, Iran.

The current paper aimed at evaluating and optimizing the efficiency of energy use and mitigation of environmental pollution by minimizing the emissions and intensity of greenhouse gases (GHG) for farm production systems in Mashhad, Iran. The results indicated that the total values of consumed energy were equal to 28,648, 38,479, and 43,490MJha-1 for barley, canola, and forage corn, respectively. The highest rate of the consumed energy for all crops belonged to irrigation electricity, diesel fuel, and nitrogen consumption. The highest and lowest energy efficiencies were respectively achieved from forage corn and canola, while barley production led to the lowest GHG emissions. The estimation of GHG intensity demonstrated that canola with 53% took up the highest intensity, which was followed by barley (30%) and forage corn (17%). Since the intensity of GHG takes into account the amount of energy produced by each crop per hectare, this index is more suitable than GHG emissions for assessing environmental pollution. The results of optimal responses of the multiple goal programming (MGP) model revealed that the optimum evaluated cultivation areas (for meeting the goals of the study) for barley and forage corn were 10,088 and 3256ha, respectively, while the MGP model generally eliminates canola from the cultivation plan. On the other hand, the plan proposed by the MGP model increases the total energy efficiency from 103,625 for the current systems to 105,169 for the optimized systems per year. Furthermore, the emissions and intensity of GHG were reduced by the model to 311,786kgCO2eq and 10kgCO2eqMJoutput-1 per year, respectively.

Ultrasonic degradation of perfluorooctane sulfonic acid (PFOS) correlated with sonochemical and sonoluminescence characterisation.

Sonolysis has been proposed as a promising treatment technology to remove per- and polyfluoroalkyl substances (PFASs) from contaminated water. The mechanism of degradation is generally accepted to be high temperature pyrolysis at the bubble surface with dependency upon surface reaction site availability. However, the parametric effects of the ultrasonic system on PFAS degradation are poorly understood, making upscale challenging and leading to less than optimal use of ultrasonic energy. Hence, a thorough understanding of these parametric effects could lead to improved efficiency and commercial viability. Here, reactor characterisation was performed at 44, 400, 500, and 1000kHz using potassium iodide (KI) dosimetry, sonochemiluminescence (SCL), and sonoluminescence (SL) in water and a solution of potassium salt of PFOS (hereafter, K-PFOS). Then the degradation of K-PFOS (10mg L-1 in 200mL solution) was investigated at these four frequencies. At 44kHz, no PFOS degradation was observed. At 400, 500, and 1000kHz the amount of degradation was 96.9, 93.8, and 91.2%, respectively, over four hours and was accompanied by stoichiometric fluoride release, indicating mineralisation of the PFOS molecule. Close correlation of PFOS degradation trends with KI dosimetry and SCL intensity was observed, which suggested degradation occurred under similar conditions to these sonochemical processes. At 1000kHz, where the overall intensity of collapse was significantly reduced (measured by SL), PFOS degradation was not similarly decreased. Discussion is presented that suggests a hydrated electron degradation mechanism for PFOS may occur in ultrasonic conditions. This mechanism is a novel hypothesis in the field of PFAS sonolysis.

Evaluation of changes of room temperature according to Trombe wall system

The purpose of solar systems is to store heat by building materials to provide optimal heating inside the house. The Trombe wall is one of the most cost-effective solutions for the optimal use of solar energy for building heating. For this reason, in this study, the room temperature variation (with the use of a Trombe wall) was studied with a modified thermal model and compared with experimental results. Comparison of thermal model and experimental results refers to the remarkable acceptance of the studied thermal model. Based on the results, one-hour changes (from 9 o'clock to the initial temperature of 13.7 °C for 8 h to 17 o'clock), based on solar radiation, the temperature changes in experimental and computational results have an increasing trend. Gradually at 17 o'clock, due to the decrease in the intensity of solar radiation, a temperature equilibrium is created in the room space.

Optimal arrangement of a micro-CHP system in the presence of fuel cell-heat pump based on metaheuristics

ABSTRACT The current energy crisis in today's world has pushed human vision to the optimal use of available energy, and experts have always taken steps to realise this important issue. One of these solutions is the use of cogeneration cycles. The main purpose of this study is to present a multi-objective methodology to select the optimal arrangement of a heat pump (HP)-based CHP system. The optimal arrangement is based on select of the best model of three different HP technologies, trans-critical R744 cycle, Peltier device, and vapour compression cycle (VCC) to achieve the best efficiency for the hybrid HP-based and fuel cell-based micro-CHP system. The optimisation process is performed based on a developed model of the Coyote Optimization Algorithm (COA) by considering two dissimilar objectives: maximising the performance of the hydrogen energy consumption and minimising the combined yearly maintenance and capital costs. The final results indicate that the VCC technology gives the best performance with regards to its low-cost and efficient features.

Optimization and design of energy monitoring system in fuels terminal: a case study in North Sumatera province of Indonesia

Optimization of energy use in the PERTAMINA’s fuel terminal (TBBM) was carried out by the Energy Audit method. The data obtained during energy audit activities then processed to carry out the Energy Performance Indicators (EnPis) which produces Specific Energy Consumption (SEC) and energy baselines. The energy cost center that creates a web-based energy monitoring system is carried out to facilitate monitoring and control and will become supporting tools. The information provided from the energy monitoring system displays the profile of total energy consumption, distribution of energy consumption, the energy consumption of equipment in production facilities in the form of daily, monthly, and annual data. Energy intensity and baseline values obtained from energy consumption and production data for the past several years will be the target and warning system to maintain energy usage that exceeds reasonable limits. The results obtained by the value of energy intensity of 0.0023 GJ / KL, while the total emissions generated from energy consumption amounted to 1,144.4 tons-CO2 / year. 51% of energy is used for production facilities and the rest is used for supporting facilities. The use of electricity as well as thermal energy does not have a strong correlation with the level of fuel sales throughout the year and the use of NGS (New Gantry System) technology does not show a significant decrease in energy intensity, where IKE values fluctuate throughout the year. This reinforces the need for continuous and real time energy monitoring. By implementing the potential for energy savings, an energy use optimization is obtained by reducing energy consumption by an average of 10% - 15% per month or as much as 18,057 - 27,086 kWh per month, equivalent to 25 - 38 million rupiah per month.

Energy Management Controller for Fuel Cell Hybrid Electric Vehicle Based on Sat‐Nav Data

AbstractThe hybridization of fuel cells (FC) and battery in electric vehicles necessitates designing an energy management system (EMS) for optimal energy use of the two power sources. The EMS represents a high‐level controller (HLC) calculating the optimal power split between the two power sources, using a prediction model for the vehicle's electric load over a planned journey trajectory. However, the instantaneous actual power demand of the vehicle is likely to deviate from the prediction due to varying traffic circumstances. This power offset needs to be compensated for whilst the optimality is still considered. A control approach is proposed here that converts the optimal power split into a dimensionless power split ratio (PSR). This ratio is passed to a low‐level controller (LLC) to be implemented as a set‐point. The LLC is responsible for simultaneously controlling the power of the FC and the battery using solely one control element, which is the DC‐DC boost converter. The PSR will be maintained whatever the actual power demand of the vehicle is. This approach will result in a fully controlled optimal power utilization, so that the high efficiency of the battery and the extended range enabled by the FC system are used to best effect.

Mold cooling in thermoplastics injection molding: Effectiveness and energy efficiency

Energy use by thermoplastics injection molding machines is estimated to result in global CO2 emissions in the order of 80 million metric tons annually. Shortening the molding cycle time is a key factor in improving energy efficiency and since cooling occupies a major part of the cycle, effective design and operation of cooling systems is essential. While guidelines exist, there is a lack of quantitative generic information to complement these. To provide this, a parametric study of mold tool cooling is carried out using numerical simulations, examining coolant channel layout, coolant flowrate and temperature, and tooling thermal properties. Briefly, some findings for representative cases include:Within recommended guidelines for coolant channel layout (channel diameter, pitch and distance from the cavity) cooling time for the worst case was found to be 70% longer than for the best.Reduction of coolant temperature by 5 °C (35 °C to 30 °C) allows reduction of coolant flowrate by a factor of more than two while keeping the cooling time unchanged.Use of an aluminum tooling alloy reduces cooling time, as compared with tool steel, by about 30% (15 s–10 s in an example) across a range of coolant flowrates and temperatures.If the maximum plastic temperature variation on ejection is to be no more than 5 °C, coolant channel pitch should be less that 50 mm when the channels are 10 mm from the cavity, and 80 mm when at 20 mm.A coolant heat transfer coefficient of 5,000 W/m2K is recommended. This corresponds to a Reynolds number of 10,000 in a coolant channel of 10 mm diameter.The effectiveness of higher heat transfer coefficients is limited by the thermal resistance of the tool and rapidly increasing pumping costs.Cooling times can be collapsed onto a single line when plotted against an overall thermal resistance that takes into account the coolant channel layout, tooling thermal conductivity, and coolant heat transfer coefficient.A widely promoted formula for cooling time is found to be inadequate and an improved formula incorporating this overall thermal resistance provides better estimates.The need for careful balancing of opposing effects to optimize energy use in cooling is emphasized. The present results will assist with this in the early-stage design, with the aim of shortening cycle time to better amortize base loads. Furthermore, insights gained will be valuable in providing better estimates of cooling time for predictions of productivity, energy use and environmental impacts.

The Performance Gap in Energy-Efficient Office Buildings: How the Occupants Can Help?

Rising demand and limited production of electricity are instrumental in spreading the awareness of cautious energy use, leading to the global demand for energy-efficient buildings. This compels the construction industry to smartly design and effectively construct these buildings to ensure energy performance as per design expectations. However, the research tells a different tale: energy-efficient buildings have performance issues. Among several reasons behind the energy performance gap, occupant behavior is critical. The occupant behavior is dynamic and changes over time under formal and informal influences, but the traditional energy simulation programs assume it as static throughout the occupancy. Effective behavioral interventions can lead to optimized energy use. To find out the energy-saving potential based on simulated modified behavior, this study gathers primary building and occupant data from three energy-efficient office buildings in major cities of Pakistan and categorizes the occupants into high, medium, and low energy consumers. Additionally, agent-based modeling simulates the change in occupant behavior under the direct and indirect interventions over a three-year period. Finally, energy savings are quantified to highlight a 25.4% potential over the simulation period. This is a unique attempt at quantifying the potential impact on energy usage due to behavior modification which will help facility managers to plan and execute necessary interventions and software experts to develop effective tools to model the dynamic usage behavior. This will also help policymakers in devising subtle but effective behavior training strategies to reduce energy usage. Such behavioral retrofitting comes at a much lower cost than the physical or technological retrofit options to achieve the same purpose and this study establishes the foundation for it.

A hybrid stochastic approach for offline train trajectory reconstruction

The next generation of railway systems will require more and more accurate information for the planning of rail operation. These are essential for the introduction of automatic processes of an optimized traffic planning, the optimal use of infrastructure capacity and energy, and, overall, the introduction of data-driven approaches into rail operation. Train trajectories collection constitutes a primary source of information for offline procedures such as timetable generation, driving behaviour analysis and models’ calibration. Unfortunately, current train trajectory data are often affected by measurement errors, missing data and, in many cases, incongruence between dependent variables. To overcome this problem, a trajectory reconstruction problem must be solved, before using trajectories for any further purpose. In the present paper, a new hybrid stochastic trajectory reconstruction is proposed. On-board monitoring data on train position and velocity (kinematics) are combined with data on power used for traction and feasible acceleration values (dynamics). A fusion of those two types of information is performed by considering the stochastic characteristics of the data, via smoothing techniques. A promising potential use is seen especially in those cases where information on continuous train positions is not available or unreliable (e.g. tunnels, canyons, etc.).

Patterns of Household Energy Consumption in Kathmandu

Much of the world's energy is currently produced and consumed in ways that could not be sustained if technology were to remain constant and if overall quantities were to increase substantially. The objective of the paper is to examine the household energy consumption of the case study area. The paper also explores significant factors affecting energy saving measures at household level. A household questionnaire survey was conducted to identify energy consumption pattern and energy efficient measures. The study stabilized that, reducing the consumption of individual household energy by using energy efficient appliances and equipment is an obvious step for energy efficiency improvement. Results of the analysis revealed that electricity is predominately used for lighting and Liquefied Petroleum Gas (LPG) for cooking, the use of energy efficient lighting appliances increasing significantly. Also there is a strong relationship of monthly energy cost with number of family, occupied space and income. Based on the aforementioned result, it is clearly concluded that, in order to optimize energy use, appropriate energy efficient appliances are to be integrated into household level.

Evaluation of Compressor Heat Pump for Root Zone Heating as an Alternative Heating Source for Leafy Vegetable Cultivation

Protected horticulture is a high energy-consuming sector in which the optimization of energy use and cost for heating facilities is strategic in achieving high environmental and economic sustainability of production. The main aim of the project was to evaluate the use of a heat pump for basal heating as an alternative technology to grow crops with reduced canopies, such as basil. During the test, an area of the greenhouse contained two systems of coaxial pipes circulating warm water from a heat pump and a condensing boiler. These pipes were placed above the growing media. At the same time, a separate area of the same greenhouse contained a traditional heating system consisting of an air heater, the solution commonly used to heat greenhouses. Microclimatic conditions and energy consumption were analyzed for the three heating technologies. The energy analysis of the three experimental heating options showed that all of them could ensure suitable thermal conditions for cultivation in the winter period. Overall, the results confirmed the energy saving resulting from the adoption of the heat pump, underlining the importance of this device in terms of the support that the energy-saving goal receives.

A new fuzzy multi-hop clustering protocol with automatic rule tuning for wireless sensor networks

In today’s world, a major challenge is to conserve and make optimal use of energy. This is a critical matter in wireless sensor networks due to their wide application in different areas. More importantly, scant attention has been paid to the use of node energy for certain applications in such networks. This study used the Shuffled Frog Leaping Algorithm (SFLA) to propose a Fuzzy Multi-hop clustering protocol (FMSFLA). The SFLA is used for automated configuration and optimization of the rule-base table in a fuzzy inference system and five adjustable parameters in two phases, i.e. Cluster Head (CH) selection and parent selection, based on application features. The proposed protocol (FMSFLA) considers effective parameters including energy, distance from the base station (BS), the number of neighboring nodes, real node distance from the BS, mean route load, delay, overlap, and the problem of hot spots, to achieve the best application-based performance. The FMSFLA includes rounds, in each round the phases of CH selection, parent selection, cluster formation, and steady state are performed. In the CH selection phase, CHs are selected from candidate nodes based on the fuzzy output and energy threshold (i.e. a control parameter) with respect to the overlap rate of adjacent CHs. In our protocol, the parent selection phase began by determining the levels of CHs in the network. At the end of this phase, the parent of each CH is determined on the basis of the greatest fuzzy output based on application. In the cluster formation phase, the clusters are formed on the basis of the determined CHs. Finally, the information received by CHs is sent through their parents to the BS in the steady state phase. The FMSFLA is evaluated against the LEACH, LEACH-EP, LEACH-FL, ASLPR, SIF, and ERA protocols in terms of the number of alive nodes, received packets, and cluster heads in addition to their appropriate distribution rates and other parameters pertaining to the network lifetime and protocol scalability using three application-oriented scenarios. According to the simulation results, the FMSFLA functioned far better than the other protocols in all scenarios with respect to goals and application features.

Internet of Things (IoT) and the Energy Sector

Integration of renewable energy and optimization of energy use are key enablers of sustainable energy transitions and mitigating climate change. Modern technologies such the Internet of Things (IoT) offer a wide number of applications in the energy sector, i.e, in energy supply, transmission and distribution, and demand. IoT can be employed for improving energy efficiency, increasing the share of renewable energy, and reducing environmental impacts of the energy use. This paper reviews the existing literature on the application of IoT in in energy systems, in general, and in the context of smart grids particularly. Furthermore, we discuss enabling technologies of IoT, including cloud computing and different platforms for data analysis. Furthermore, we review challenges of deploying IoT in the energy sector, including privacy and security, with some solutions to these challenges such as blockchain technology. This survey provides energy policy-makers, energy economists, and managers with an overview of the role of IoT in optimization of energy systems.

Energetic and Environmental Constraints on the Community Structure of Benthic Microbial Mats in Lake Fryxell, Antarctica.

ABSTRACTEcological communities are regulated by the flow of energy through environments. Energy flow is typically limited by access to photosynthetically active radiation (PAR) and oxygen concentration (O2). The microbial mats growing on the bottom of Lake Fryxell, Antarctica, have well-defined environmental gradients in PAR and (O2). We analyzed the metagenomes of layers from these microbial mats to test the extent to which access to oxygen and light controls community structure. We found variation in the diversity and relative abundances of Archaea, Bacteria and Eukaryotes across three (O2) and PAR conditions: high (O2) and maximum PAR, variable (O2) with lower maximum PAR, and low (O2) and maximum PAR. We found distinct communities structured by the optimization of energy use on a millimeter-scale across these conditions. In mat layers where (O2) was saturated, PAR structured the community. In contrast, (O2) positively correlated with diversity and affected the distribution of dominant populations across the three habitats, suggesting that meter-scale diversity is structured by energy availability. Microbial communities changed across covarying gradients of PAR and (O2). The comprehensive metagenomic analysis suggests that the benthic microbial communities in Lake Fryxell are structured by energy flow across both meter- and millimeter-scales.

Design load controller and load shedding mechanism at DC house prototype

The DC house project is a pure DC electricity system to enable optimal use of renewable and alternative energy, DC House promotes a more sustainable solution by not using fossil-based fuels. DC sources are mainly from renewable generation, such as PV and wind turbines, the output from PV and Wind turbine produced is not stable, so there is a need for a regulatory system, arrangements can be made on the generation side and on the load side. Because the output of the generator is not constant, a setting on the load side is needed to adjust the generation capacity. If one of the offsets is to be released, a load shedding must be carried out to meet the load requirements. The release of the load is carried out when the supply is reduced because one of the generators is off, then the lower priority load will be released automatically. In this study simulated DC loads using PID control on the buck converter and load release using switching four loads with priority scale. The DC current sensor is used to determine the amount of current when determining the load released due to limited supply from the source.