Energy Consumption Load Research Articles

Improving Energy Efficiency performance utilizing building envelope design in High standard housing in Egypt

Nowadays Climate change is the main dilemma urging the world actions to mitigate it, mainly through fossil fuel independency and energy consumption management. Energy deficient performance of the building envelope in residential buildings is a major driver increasing energy consumption rates. Since the cooling loads and lighting are on top of the electric consumption rates in housing, then a key mitigator to improve the energy efficiency performance of a building envelope is the adequate management of energy flow through the household by the passive strategy (cooling and daylighting) techniques to acquire the best advantage of the local climate. Selecting the high standard housing segment represented in new Gated communities, spotting the gap between the formal and new market criteria and how it is widely spreading with no considerations to their building envelope energy deficiency performance and accumulation of energy consumption loads urges the need to take the High standard housing into an actual high standard not only per income level, but also in its energy high performance aligning with global aspect. Cases studied were analyzed to observe their passive cooling techniques implemented in the Building Envelope to improve the energy efficiency performance. Then one base case study (SODIC EAST-MVvilla) is selected and adapted with previously induced eight passive cooling techniques then simulated with DesignBuilder software to assess the energy consumption, thermal performance, and CO2 production of the building. The study resulted in significant electric consumption annual decrease by 41% thermal comfort annual improvement by 66% that lead to a decrease in CO2 production by 41% annually and that is when a building improves its energy efficiency utilizing the building envelope using passive cooling strategies.

Smart Energy Meter Reading and Billing System using GSM Modem

In this paper we are focusing on automatic billing and metering, The GSM Short Message Service (SMS) and Arduino connection gives the metre reading system several predefined automatic capabilities.The energy consumption and electricity bill and loads will be providing through GSM module to the customer and to the concern electricity department. An alert message will be send to the customer and vigilance squad when the consumption unit reading reaches beyond the specific threshold. And loads on and off through gsm This paper contains energy consumption details in terms of power units and power units will be displayed on the LCD and will be notified to the customer via SMS and customer will also be able to recharge with the help of GSM module as well as microcontroller.

Thermal load prediction and operation optimization of office building with a zone-level artificial neural network and rule-based control

Precise and quick thermal load prediction for buildings is imperative in realizing the flexibility of building energy systems. Operation optimization based on the prediction results can effectively mitigate the energy consumption and operation cost. Here, an artificial neural network (ANN) model is built to predict the load demand and energy consumption of an office building. Thermal zones division is considered to improve the prediction accuracy. Measured data are collected to establish and validate the ANN model. The total number of samples for training, validation and testing are 13674, 3978 and 3977, respectively. A rule-based control optimization model is introduced and combined with ANN model to optimize the operation of heating, ventilation and air-conditioning system. Building energy flexibility is activated by optimization model in a time-of-use electricity price scenario. The results indicate that ANN model has high precision and the coefficient of variation of root mean squared errors corresponding to the load demand prediction and energy consumption prediction are 10.76% and 15.59%, respectively. Furthermore, the optimization results can reduce the operation cost by 39.22% and 44.41% in the heating and cooling season, respectively.

Dynamic energy efficient load balancing strategy for computational grid

AbstractComputational grid is a pool of computational resources that is used by various organizations for storage purposes and execution of a large number of tasks. Load balancing and energy consumption are two core performance parameters in the computational grid. Since, performance of a computational grid is highly dependable to variations in load and energy consumption, therefore, it is important to pay attention to these aspects in grid. Therefore, we proposed an energy‐aware dynamic load balancing strategy for tasks scheduling in grid referred to as dynamic energy efficient load balancing strategy (DEEL) for computational grid. DEEL combined energy efficiency and load balancing paradigms in order to improve the utilization and reduce the energy consumption of resources. Simulations were performed by using GridSim. Simulation results were compared with published strategy IEGDC with respect to performance indices: finished gridlets, unfinished gridlets, resubmitted times, and response time. The simulation results were evaluated through performance metrics that is, (a) cost, (b) energy consumption, and (c) energy saved. As per simulation results, DEEL outperformed the published method IEGDC by reducing the execution time of finished gridlets up to 28%, minimizing the execution and resource cost up to 35%, and saving the energy consumption up to 38%.

Prediction of unregulated energy usage in office buildings

PurposeThe paper presents a technique for predicting the energy consumption of unregulated energy loads (UELs) in office buildings. It also presents an approach for determining a set of optimum values required by the technique.Design/methodology/approachThe proposed technique uses the optimum power drawn and optimum usage period in three modes of device operation, for the prediction. The usage modes are active mode, idle (low active) mode and off mode. The optimum powers and usage times are inserted into a linear mathematical equation to predict the energy consumption. Regarding the approach for determining the optimum values, the non-dominated sorting genetic algorithm II (NSGA-II) is applied to a range of values obtained from field measurements. The proposed prediction method and approach for determining optimum values were tested using data of energy consumption of UELs in a case study facility.FindingsTest results show that the method for predicting the energy consumption of UELs in offices is highly accurate and suitable for adoption by energy modelers, building designers and building regulatory agencies. The approach for determining the optimum values is also effective and can aid the establishment of workable benchmark values.Originality/valueA new and simple model has been developed for the prediction of unregulated energy. A method for determining a set of optimum values of power and usage periods required by the model has also been developed. Furthermore, optimum values have been suggested that can be fine-tuned for use as benchmark values. The proposed approaches are the first of their kind.

ANALYSIS OF ENERGY-EFFICIENT HOUSE LAYOUT DESIGN IN TROPICAL CLIMATE

Energy-efficient residential provision is an essential concern for the present and future city development. Currently, the residential buildings contribute approximately 37.5% to significant energy consumption and carbon emissions, which mainly used for cooling. This research aims to study the house layout arrangement to minimise cooling loads and further reduce energy consumption. Energy efficiency analysis is performed by comparing the cooling load and total energy consumption from variations of the hypothetical design of detached or semi-detached housing layouts commonly built in Indonesia. The calculation of cooling loads and energy consumption is performed by simulation in Energy Plus 8.4 with Jakarta weather data. The results show that the arrangement of the house layout may reduce the cooling load up to 24%. The total conditioned wall area that varies due to the variations of house layouts are found to affect the cooling loads.

Smart Home Automation System Using Wireless Sensor Networks

The architecture explains how load energy consumption readings can be digitised and shared through the internet. Human presence in electricity maintenance is eliminated with the proposed machine style. By having a channel id for the load, A webpage can be used to monitor energy usage in watts. The webpage makes use of THINGSPEAK analytics to look at energy use and provide a detailed overview and visual representation of the data. The Wi-Fi unit performs Cloud computing by providing load energy data to a website usable via the device’s channel id.. Client can control resources inside the proposed framework by tracking energy consumption over time. The Arduino microcontroller is used in this system. The created unit is frequently shown on the webpage via the Wi-Fi module. Wireless Sensor Networks, Power, Voltage, Current, and ZigBee are some of the terms used in this paper.

Frequency-Based Time-of-Use Pricing with Multiple Battery-buffered Smart Loads

This work discusses a new time-of-use energy pricing structure based on grid frequency. Under the proposed pricing structure, energy cost depends on the time of frequency deviation and the period during which energy is used. This pricing mechanism is intended for use with multiple behind-the-meter home batteries as part of a frequency-controlled smart load strategy known as a battery buffered smart load. The load energy consumption from the grid and energy storage rates thus depend on the frequency deviation and hours of use, which means that the proposed pricing encourages battery-using customers to not only utilise energy arbitrage, shifting peak demand but also to contribute to demand-side primary frequency control. The second contribution of this paper is the presentation of an operation strategy for multiple buffered battery smart load units in which charge and discharge decisions are made according to off- and on-peak period information to ensure continuous provision of primary frequency control under the proposed time of frequency division pricing. A MATLAB simulation of the proposed pricing and operation modes of the BBSL was conducted with multiple battery-buffered smart load to assess feasibility.

Research on theoretical energy saving rate of cooling and heating with intelligent temperature control of office buildings in Xinjiang typical climate zone

At present, many office buildings in Xinjiang generally use continuous movement of heating and cooling systems, heating and cooling excessively caused the energy waste, the use of intelligent control equipment system can effectively save energy. This paper uses the parametric performance simulation toolset (Ladybug tools) to model the energy consumption of office buildings in four typical climatic regions in Xinjiang. It simulates two methods of intelligent control (ICS) and continuous operation (COS) in different window-to-wall ratio (WWR) the influence of heating and cooling energy consumption load. Considering the additional equipment energy consumption (ΔE) of ICS, the control energy saving rate (ƞ) is compared ICS with COS. The results show that in different climate zones and with different WWR, ICS is more energy-efficient at the heating and cooling methods than COS. Moreover, in different climate conditions, office buildings with different WWR have different energy-saving rates. The change of the WWR has a small effect on the η value in the Severe Cold Zone C, and the η value in the Cold Zone A region decreases with the WWR becomes larger. This study further proves that the contribution of intelligently controlled heating and air-conditioning systems of building energy conservation and provides a favourable basis for refined energy development.

Sustainable advanced distribution management system design considering differential pricing schemes and carbon emissions

Advancedd distribution management systems (ADMSs) integrate distributed generation (DG) units and battery energy storage systems (BESSs), and they are a promising solution to reduce the greenhouse gas emissions in the energy sector. This study addresses the sustainable ADMS (SADMS) design problem by determining the power flow optimal economic dispatches from traditional power plants, DG units, and BESSs to residential areas while maximizing the total profit. The designed SADMS provides a demand response programs with various energy pricing schemes that correspond to different customers and energy consumption loads. Three carbon emission policies (carbon tax, carbon cap, and carbon trade) are considered in the model. An advancedd two-phase (ATP) approach is proposed to solve the described problem. In the first phase, an artificial neuro-fuzzy system (ANFS) is developed based on self-learning and self-adjusting processes to determine the customer demand response loads and DG unit output energies in uncertain environments. A combined ANFS and optimization solver is proposed in the second phase to determine the optimal SADMS economic dispatch. The application of the proposed approach is examined using an empirical case study in Taiwan. The results demonstrate that the proposed ATP approach can determine the optimal economic dispatch with an extremely small deviation in demand response load of 0.92%. In addition, our approach increases the total profit (improving total profit by approximately 1.1%, 0.8%, and 1.9% for the three different carbon emission policy objective functions) and reduces the computational time (by 3.0–6.0 times) compared to those of the genetic algorithm. Finally, the proposed model illustrates that carbon trade is the best policy for improving the total SADMS profit while satisfying the given environmental constraints.

Data driven occupancy information for energy simulation and energy use assessment in residential buildings

Occupant’s schedules and their energy-use behavior are substantial inputs for building energy simulations and energy management in buildings. In practice, most of the research studies consider default occupant schedules from the standards. Subsequently, the temporal variations associated with occupancy is often missed out, leading to uncertainties in simulation results. This study aims to address two research problems in terms of occupancy: 1) upon the availability of the data, how to systematically extract the different occupant schedules, 2) when the occupancy data is not available, what are the other commonly logged parameters (such as plug load, lighting energy consumption, indoor carbon dioxide (CO2) concentration, and indoor relative humidity data) that shall be used to represent the occupancy in buildings. Regarding the first objective, a generic data-driven framework with the combination of shape-based clustering and change-point detection method is proposed to extract the distinct occupancy in residential buildings in terms of occupant activity schedule and presence probability. To demonstrate the outcomes of the framework, it was applied to the dataset collected from eight apartments located in Lyon, France. The results show the existence of different occupant patterns in buildings with respect to day of the week and season of the year. To achieve the second objective, linear and logistic regression models were developed to represent the occupant activity level and occupant presence/absence state, respectively. The linear regression model results show that among the examined variables, the lighting, and plug load consumption data along with the hour of the day show better prediction results in terms of adjusted R2 and mean absolute percentage error. For the occupant presence/absence state, the logistic regression model developed using CO2 concentration and plug load energy consumption dataset shows better results in misclassification error, confusion matrix, and receiver operating characteristic curve.

Double sink energy hole avoidance strategy for wireless sensor network

To solve the energy hole problem in wireless sensor networks with double sinks, a double sink energy hole avoidance strategy is proposed. The main idea is that two data sinks are set at fixed positions on both sides of the rectangular network to collect nodes data in the corresponding area of the network. In the network, sensor nodes are organized in non-uniform clusters. Clusters close to sink have a smaller cluster radius, and clusters far from sink have a larger cluster radius. According to the results of threshold training, monitoring area of double sink is dynamically adjusted based on the difference of energy consumption and load of nodes in the double sink monitoring area, so that the energy consumption load of nodes in the double sink monitoring area tends to be the same, so as to avoid the premature occurrence of energy hole phenomenon in the area with large load, leading to network failure. The experimental results demonstrate that the strategy proposed in this paper can efficiently balance the energy dissipation of double sink and prolong the network energy utilization efficiency and network lifetime.

Load power and energy management system using proteus visual design software

At present, there is a serious energy crisis around the globe which impacts greatly on the power grid. A smart and user friendly energy management system can control the energy consumption. In this paper, load power and energy management system is developed and simulated using Proteus Visual Design software. The load analysis and measurement techniques are developed for single phase and three phase loads and implemented using Arduino Mega 2560 board. User friendly controls are developed using the visual design feature of the software to control the energy consumption. The load power management system is simulated by measuring the power consumed by various residential loads such as lights, fans, air-conditioners, heaters. The industrial loads are simulated by squirrel cage induction motor. The load analysis summary is displayed on the Arduino 2.8 inch TFT display shield in a table format. The simulaion model is created for future hardware implementation and is tested under various practical input conditions. The Proteus Visual Design software is chosen in this resesarch due to its advantages such as professional PCB layout package, availability of nearly 800 microcontrollers in the library package etc.The developed model successfully measured the energy consumption of several loads and assist the user in controlling the energy usage through automation control techniques. The accuracy of the results shows that the technique and the model developed in this research can be used by engineers, students and hobbyists who are working with energy monitoring systems and smart home applications directly. This is an ongoing project where in the next stage, the hardware design of the simulation model will be implemented and tested in real time application.

Development and simulation of the Institute of ionosphere measuring complex energy consumption

The work is devoted to solving an urgent problem - the development of a computer model of the energy consumption system of the Institute of the ionosphere of the National Academy of Sciences and the Ministry of Education and Science of Ukraine in order to solve the problem of increasing the energy efficiency of the measuring complex. The power supply system of the complex is described, a generalized structural diagram of the loads - powerful consumers of electricity is presented. The graphs characterizing the energy consumption of individual powerful loads are presented, the problem of compensating the reactive power of loads is shown. The adequacy of the developed model is confirmed by the coincidence of the shape and values of the experimentally obtained characteristics on loads with the characteristics of the model. The model adequacy was assessed by the variance of feedback deviations from the system mean. The results obtained confirmed the possibility of using the developed Matlab-model of the energy consumption system of the measuring complex for creating and testing on the model of an energy-efficient power supply system, which will ensure the stable operation of scientific equipment for the implementation of research programs of the NAS of Ukraine.

Comparative Analysis on Load Characteristic of Intermittently Conditioned Buildings for Different Wall Insulation Forms

The Air-conditioning System (ACS), used in office buildings in the hot summer and cold winter zone of China, are always operate intermittently. The dynamic thermal behaviors of building walls with real climate conditions may be different from those with only the representative day’s climate conditions, due to the time varying nature of the climate, which will lead to the variation of the ACS loads. A numerical calculation was performed to analyze the effects of insulation form on heat behavior of external walls and ACS loads. The results indicate that cooling transmission load with inside insulation reaches its maximum value when the solar-air temperature in daytime is the highest, while that with outside insulation occurs at the time when the air temperature at night is the highest during summer. Heating transmission load for the wall with external and internal insulation both peaks in the day with lowest mean outdoor temperature during the last non-working period. Inside insulation can be considered a better way to reduce the peak load, peak-valley load difference and energy consumption.

HARB: A Hypergraph-Based Adaptive Consortium Blockchain for Decentralized Energy Trading

The emergence of the Internet of Things (IoT) and distributed energy resources (DERs), has given rise to collaborative communities that manage their energy production and consumption load through peer-to-peer decentralized energy trading (P2P DET). To address the issue of distributed trust in these communities, blockchain technology is widely considered as a promising solution due to its ability to provide records provenance and visibility. However, the current blockchain-based platforms are known to compromise on scalability and privacy in favor of trustless interactions and often do not support interoperability. In this work, we propose a hypergraph-based adaptive consortium blockchain (HARB) framework, which coordinates DERs through high-order relationships rather than P2P pairwise relationships. HARB is presented in a three-layered network architecture to address the aforementioned challenges. The bottom layer (Underlay) addresses the issue of scalability, by exploiting the rich representation ability of hypergraphs to describe complex relationships among DERs and end users. We use the described complex relations to form scalable network clusters with intra- and inter-community energy trading relationships. The middle layer (Overlay) presents a blockchain service model to describe adaptive blockchain modules that support interoperability between the network clusters. To preserve privacy, we present a data tagging and anonymization model in the top layer (Contract), which attributes transactions to specific network clusters. To evaluate our framework, we modeled various IoT devices with different computing resource profiles to simulate a distributed energy trading (DET) environment. The analyzed results have shown that our proposed framework can effectively improve the performance of blockchain-based DET systems.

Heat utilization of a ventilated sunspace in a non-insulated apartment

ABSTRACT This study investigated the energy conservation of a non-insulated old apartment with a ventilated sunspace in Qingdao, China. The ventilation between the bedroom and sunspace of the apartment was controlled by the Delta temperature, which is equal to the sunspace temperature minus the bedroom temperature. EnergyPlus software was used to calculate the temperature, humidity, and thermal load of the apartment. The aim of this research is to analyze the sunspace performance at different flow rates and Delta temperatures. The flow rate between the sunspace and bedroom was set to range from 0.05 m3/s to 3 m3/s, and the Delta temperature was set to range from 0 to 2°C. It is found that when the ventilation between the sunspace and bedroom is activated under the condition that the Delta temperature is higher than 0.5°C, the heating load energy consumption decreases with increasing flow rate. When the flow rate is 0.3 m3/s and the Delta Temperature is 1.5°C in February, and the flow rate is 0.3 m3/s and the Delta temperature is 1°C in November, December, January, March, and April, the minimum energy consumption of the bedroom is 198.8 KWh/m2. Compared with bedroom without sunspace and with non-ventilated sunspace, Delta temperature-controlled ventilated sunspace can reduce the annual heating load energy consumption by nearly 14.7% and 4.4%, respectively.

Physarum-Inspired Autonomous Optimized Routing Protocol for Coal Mine MANET

Mobile Ad Hoc Network (MANET) is suitable for complex environment communication in coal mine. The processes of nutrient flux transfer and path choice in Physarum networks are similar to data transmission and routing decision in MANET. In this paper, we use a Physarum optimization model to design Physarum-inspired autonomous optimized routing (PIAOR) protocol to adapt to the dynamic network topology in underground mine. PIAOR introduces the status of MANET into the Poisson equation in the Physarum model, selects reasonable parameters to represent the transmission performance of the network, and uses the differential evolution equation of the Physarum model to evolve the parameters. PIAOR has achieved the distributed routing decision by automatically reconstructing the optimal routing path, which has reduced the algorithm complexity. Based on NS2, simulation experiments are performed to evaluate the performance of PIAOR, and the results are compared with GPSR, PIMAR, and P-IRP routing algorithms. The experimental results show that the routing path selected by PIAOR is better than that selected by the other three protocols in the performance of average end-to-end delay, delivery ratio, and throughput. The balance of energy consumption and network load is reached, and the network lifetime is effectively prolonged when using the PIAOR protocol.

Behavior of geopolymeric recycled aggregate concrete-filled FRP tube (GRACFFT) columns under lateral cyclic loading

In order to improve the environmental sustainability of concrete-filled FRP (fibre-reinforced plastic) tube (CFFT) column, a new kind of composite column, geopolymeric recycled aggregate concrete-filled FRP tube (GRACFFT) column, was proposed in this paper. The hysteretic behaviors of GRACFFT columns were experimentally investigated. The influences of different parameters, i.e., fiber types, section form, and reinforcement type were discussed. Based on the strain analysis, the plastic hinge length and utilization factor of FRP fibers for each GRACFFT column were also investigated. According to the experimental results, it was found that the proposed GRACFFT column showed favorable seismic performance with both high carrying capacity and deformation ability. The proposed GRACFFT column made with carbon FRP tube showed the best seismic behaviors in terms of yield displacement, peak load, ultimate displacement, and cumulative energy consumption. In terms of cross-section, the seismic behaviors of the circular GRACFFT column were better than that of the square column. Also, it was found that the substitution of steel reinforcements with steel tube could effectively increase the seismic behaviors of GRACFFT columns.

Impacts of Roof-top Solar Photovoltaic Modules on Building Energy Performance: Case Study of a Residence in HCM City, Vietnam

Vietnam is considered a country with high solar potential and solar irradiation is comparable to most countries in the region. However, high density solar project in areas causes overload state of transmission grid system and some plants wouldn’t operate at full design capacity. Therefore, roof-top solar PV projects in provinces and cities, which have large potential of solar irradiation, are promoted to reduce pressure on power supply. Besides, rooftop solar would be also affordable for home and business owners and communities by helping households halve electricity bills and gain energy efficiency. In this paper, we investigate case study of a residential building in HCM city, Vietnam for analysing impacts of roof-top solar photovoltaic modules on energy performance. The results showed not only the potential photovoltaic power, but also the reduction of roof heat transfer. In consequence, the building cooling load and total energy consumption are significantly reduced thanks to Roof-top PV installation. On the other hand, the reduction of solar incident on the building roof keeps cooling roof surface (outer and inner) and improves thermal comfort of attic space. Our research objective is to quantify indirect benefit of Roof-top PV on energy efficiency and to provide ideas for further researches.