Limited Energy Sources Research Articles

Towards a Near-Zero Energy Building using a Building-Integrated Photovoltaic System with Smart Energy Management Capabilities

Renewable energy resources, despite their advantages, it is uncertain due to the fluctuations in the weather. Clouds, dust, rain, and heat will negatively affect photovoltaic panels’ production, which leads to the problem of power supply interruption and a decline in reliability. For that, it is required a standalone photovoltaic system with a smart energy management strategy. On the other hand, the load’s reactive power decreased the system’s efficiency and caused an overcurrent fault. So, it requires the adopt a mechanism to correct the power factor to enhance efficiency. The proposed system adopted two strategies: the first adopt an energy consumption management that determines the schedule’s consumption loads. This strategy includes the predicted supplied power for the current day and two days ahead according to the available energy based on the forecast of solar radiation and the batteries’ energy to update and correct the expected values.Moreover, three operating modes are presented according to the battery state of charge (SoC). The second strategy is adopting an automatic power factor correction (APFC) unit. A capacitor bank is used, where the system adds one or more capacitors to enhance the power factor. The proposed system also offers an Internet of Things (IoT) technology to communicate between system components and implement remote monitoring and control. The simulation results showed an integrated system capable of saving energy and relying on a limited renewable energy source. Such a promised system will lead to near-zero energy buildings (NZEB) without affecting life quality.

LDCA: Lightweight Dynamic Clustering Algorithm for IoT-Connected Wide-Area WSN and Mobile Data Sink Using LoRa

Wide-area monitoring applications of the Internet-of-Things (IoT) connected wireless sensor network (WSN) consists of sensor nodes (SNs) with limited hardware and energy sources. The distributed nature of such a network and the difficulty of remote access make it more demanding to design an energy-efficient WSN. Moreover, long-range and low-power wireless connectivity is a challenge in IoT-connected applications. Present WSN topologies deal mainly with fixed SNs, SN distribution, and fixed data sink (DS). The majority of the control layer is implemented in the lower hierarchical layer or in a virtual middle layer, which reduces the network lifetime due to excessive processing and data transmission activities. This article proposes a real-time lightweight dynamic clustering algorithm (LDCA) for a WSN that supports the following two scenarios with limited processing resources: 1) with mobile DSs and static SNs (such as DS and SNs mounted on unmanned aerial vehicles, autonomous vehicles) and 2) with mobile SNs and static DSs (such as livestock monitoring or autonomous robots in smart farming, and urban monitoring). The proposed algorithm is based on the received signal strength indicator and signal-to-noise ratio of a long-range (LoRa) interface and its residual energy. Mathematical models were derived for real-time clustering using LoRa. Memory requirement and clustering efficiency of the constrained SN and DS for various mobility scenario were evaluated. The proposed LDCA reduces the energy requirement to 33% compared to static clustering, by reducing the number of concurrent clusters and hops. In addition, a hardware-based approach was used to validate the LDCA algorithm, and evaluate its performance in terms of energy efficiency, packet delivery rate, and network lifetime.

Study of Floating and Moving Houses for New Resilient Living and a Need of Tomorrow

The concept of plasticity in floating homes pattern is to go into the resilient characteristic and thus reveals some new ideas for the arrangement of this project. Resilient characteristic can be sum of characteristics for the natural disasters lick earthquake, uncomplicated implementation and the possibility to use of sustainable self - sufficient energy system in the location to limited energy sources, mobility, long life, water recycle system, prefabrication and modular construction with the potential for a reduced environmental impact .The benefits include potential for a comfortable and peaceful atmosphere directly connecting the nature considering the resilient features of the floating houses at the time of climate changes and attempts are made to design a low cost floating house for the people.

Static Analysis of the Last Stage Low Pressure Steam Turbine Blade to Improve Blade twist Angle

Demand for electricity is growing continuously and the production is still based on limited sources of energy, mainly the turbomachinery, which include basically the steam and gas turbines. Turbomachinery is responsible for about 80% of the electricity generated worldwide. A large variety of turbine blade geometries are in use today, however, there is no specific attempt made to compare them based on performance.This paper presents a study on the effect of the twist angle of the steam turbine blade on different choice blade materials. For the study, the aerodynamic and static loading of the 19th stage low pressure turbine blade of Egbin thermal power station was evaluated. Static analysis based on computational fluid dynamics (CFD) was used to simulate the conditions of the turbine blade during normal operating conditions. Alternative materials (such as stainless steel 316, Titanium alloy) and varying twist angles were observed to be showing different forms of results in the simulation on ANSYS. From these, an optimized twist angle was generated using Response Surface Optimization on ANSYS RSO, and the consequent results were discussed.

The Orientation of Village, the Most Important Factor in Rural Sustainability in Cold Climate (Case study: Masuleh and Uramantakht)

The rural fabric of every village is affected by both human interventions and environmental factors. Also, climate and nature can both influence the village structure. In other words, the climatic and vernacular architecture of rural areas are mutually interrelated, and the villages have to adapt to their environment to survive, provide welfare, and prevent the immigration of villagers to cities sustainably.A very important factor in the sustainability of vernacular buildings is the orientation of rural buildings and the possibility of using solar and wind energy, an issue that has been considered by vernacular builders throughout history. Limited sources of energy and reliance on renewable energy have made the inhabitants design and build their vernacular buildings according to climatic conditions to reduce energy consumption. In this regard, the proper orientation of the buildings to prevent energy loss is of particular importance.This study tries to discuss the factors influencing the orientation of rural housing. The vernacular architecture and the proper orientation of houses in Masuleh (Gilan province, north of Iran) and Uraman Takht (Kurdistan Province, west of Iran) villages are also discussed. The possibility of using key factors of vernacular architecture principles in similar climates is also discussed. Energy simulations with the Honeybee plugin are used as a tool for optimization orientation. Honeybee runs simulations with EnergyPlus through Rhino and Grasshopper software and visualizes results by the Ladybug plugin. For the finding best orientation, the parameters which related to building energy performance defined in honeybee plugin such as windows size and location, wall U-value, glazing construction U-value, glazing g-value, cooling and heating set-point. After energy modeling of building for the case study, the energy simulation has been conducted with EnergyPlus engine and the Ladybug plugin visualized the results.

Closed-Structure Compliant Gripper With Morphologically Optimized Multi-Material Fingertips for Aerial Grasping

Aerial grasping empowers unmanned aerial vehicles to find applications beyond structured logistics. However, it brings a number of challenges including inaccurate positioning of the end effector and limited energy sources. Moreover, solutions so far have difficulty in handling a variety of objects. A novel closed structure compliant gripper was developed to address the challenges above. The gripper has a large self-centering work envelope and is normally-closed for passive grasping. Introduction of compliance as a form of morphological computation was also considered to enhance grasping capabilities, where multi-material 3D printing would facilitate rapid design changes based on target application. To grasp different objects, the gripper has hot-swappable 3D printed fingertips which are optimized with a multi-objective Bayesian Optimization process using physical bench experiments mimicking drone grasping and ascent on a common object set. The morphology of the fingertip including tip width, curvature and distribution of soft and hard material on contact surface, are optimized with a bench test that mimics quadcopter takeoff and landing. The best design from optimization shows an improvement of more than 10% from the initial design in successful grasp operations, demonstrated by field tests with a quadcopter.

RETRACTED ARTICLE: An improved source location privacy protection using adaptive trust sector-based authentication with honey encryption algorithm in WSN

A wireless sensor network is a set of sensor nodes used to identify the environment and the corresponding object. It collects all the data of the situation and transmits this detected data to the central node through a wireless network. However, some challenges are encountered in wireless sensor networks i.e., the efficient deployment of sensor nodes in an environment. Some of the issues are limited sources of energy, limited transmission bandwidth, short coverage, data distribution, data persistence, faulty node, and data security redundancy. The Discovery Configuration Protocol (DCP) has been signed for a period of time to monitor the applications. It is required for alternate use, which is very important to recreate the correct data source. Recently, Source Location Privacy (SLP) security at the WSN has attracted a way to prevent opponents from pursuing a backtracking strategy to capture the data source. Delivery of messages from different source nodes to sink nodes is done through an end-to-end location privacy process. With location-based services, data must be retrieved by users who do not have information about the data’s location. So, introduce a proposed Adaptive Trust Sector-Based Authenticated System (ATSAS), which is meant to evaluate the trust confidence value of each node with the help of agent sinks node. When the joining nodes discover their neighbors, they exchange information about the number of single-hop neighbors. The updated confidence value of the node is formed in the network algorithm. The first stage is done using the Honey Encryption (HE) for message authentication and packet encryption to provide security in WSN. These encryptions are making Distribution-Transforming Encoder (DTE) for space of the un-encrypted plain text message into the seed space of n-bit string. The output encryption point is the input to feedback for key generation. To the next level, both direct and indirect observations, such as its neighbor’s trust value, are calculated based on two sources of information. This protocol thereby increases secure communication in a hierarchical WSN. The trust rate control of the network at the source of the packet, which helps drive the time control mechanism. Such Network Control Point (NCP) system development methods provide security and reduce the occurrence of overload on distributed sensor nodes. The theoretical analysis and test results demonstrate that the proposed method improves security, reduces directional attacks, and increases the network’s longevity.

Demand-side management for off-grid solar-powered microgrids: A case study of rural electrification in Tanzania

This work proposes a novel and sustainable energy development strategy for addressing the energy shortages in rural areas and the low energy efficiency of off-grid solar power systems. This study combines the analysis of power consumption type with consumption anomaly detection to characterize households’ power consumption habits and ensure the safety of a system. Specifically, the proposed anomaly detection method is a hybrid nonintrusive model. The home power usage data are collected and processed by auto-data-binning without manual labeling, and thus, the training cost is reduced to enable the application of machine learning technologies in underdeveloped areas with limited computational resources. With the premise of limited energy sources in off-grid areas, the proposed power consumption analysis method divides home power usage habits into four different types. Different feedback mechanisms are adopted to extend the microgrid’s supply time according to the analysis results. The proposed method significantly increases the utilization of local renewable energy and improves residents’ experience. The proposed method is implemented in a rural village in Tanzania; after long-term monitoring, the validity of the proposed method is demonstrated.

Cuddle death algorithm using ABC for detecting unhealthy nodes in wireless sensor networks

Wireless sensor networks consist of some sensor nodes that have a minimum operational capability, with less memory capacity for storing data and limited energy source. The deployment of these nodes or sensors takes place randomly in a dynamic or static environment. This type of placement of nodes in a hostile environment can be charge by the malicious nodes in a wireless sensor network (WSN). This vulnerability in nodes makes the wireless sensor network unstable and leads to many types of demerits like limited battery lifetime, less computing, and limited memory space. To avoid these attacks and to reduce the impact created by the malicious nodes, we suggest a simple and effective way of detecting and removing unhealthy nodes in the environment. We proposed a simple scheme by using the Artificial Bee Colony algorithm which is known as the cuddle death design. The theme of a scheme is to find the unhealthy or malicious cluster head nodes in the network and removing that particular node without creating any harm to the other nodes in the environment. It also helps to improve the energy efficiency, packet delivery ratio with maximum throughput in WSN.

Energy-Aware Geographic Routing for Real-Time Workforce Monitoring in Industrial Informatics

Workforce monitoring is a vital activity in large factories in order to oversee the worker's concentration on their duty and increase productivity. Workforces are kind of moving targets which can be monitored via wireless sensor networks (WSNs). As sensor nodes have a limited source of energy, optimal energy consumption is of crucial importance in these networks. Several protocols for routing are designed in order to consider efficient energy consumption in conjunction with target tracking and coverage. In this article, a new energy-efficient routing algorithm geographic routing time transfer (GRTT) is proposed to use topological information of sensor nodes for target tracking and coverage applications. In this article, a weight called relay ability is defined for each node according to the sensor network topology. These weights are calculated and announced to sensor nodes by cluster heads (CHs). Once a target enters the area covered by sensor nodes, a signal is sent to the CH through the route having maximum predefined weights in the network. Simulations show better results than other tracking routing methods based on the metrics of energy consumption of the network, power consumption, and throughput for GRTT (proposed method), dynamic energy-efficient routing protocol (DEER), virtual force-based energy-hole mitigation (VFEM), nonequal-probability multicast routing protocol (MRP-NEP), and trace-announcing routing scheme (TARS) methods.

A fuzzy control system for energy‐efficient wireless devices in the Internet of vehicles

Embedded systems are common in the Internet of Things domain: their integration in vehicles and mobile devices is being fostered in the Internet of vehicles (IoV). IoV has direct applications on intelligent transportation systems and smart cities. Besides basic requirements, such as ease of installation, cost-effectiveness, scalability, and flexibility, IOV applications need to guarantee energy-efficient and good-quality communication. In fact, IoV implementations are commonly based on wireless nodes, which rely on a limited energy source; therefore, an efficient communication among the nodes is desirable to prolong the lifetime of the devices. In particular, the alternation of active and sleep states and the regulation of the transmission power represent two common approaches to save energy. Based on this strategy, an effective fuzzy control system is presented in the paper to manage power consumption and quality of services of IoV applications. Two fuzzy controllers increase the battery life while keeping a good throughput to workload ratio. This technique has been simulated with two leading technologies in IoV: IEEE 802.11b/g/n and IEEE 802.11p. Experimental results show a network lifetime improvement ranging from 30% to 40%, according to the adopted medium access control protocol.

Analyzing the sensitivity and energy efficiency of a residential complex in warm and dry climate of Iran: the case study Yazd Province

In recent years, the limited energy sources and their huge costs in many countries to save money have attracted the attention of many scholars. The purpose of the energy consumption assessment of a building is to reduce the waste of the energy, and this reduction in the energy has a direct relationship to the lower costs. In this paper, the researcher tends to investigate the sensitivity and the energy analysis of a warm and dry residential complex in Iran (Yazd). Initially, the simulation of the energy consumption of a building was calculated by using the eQUEST software, to determine the thermal load of the building for a range of important parameters (such as wall insulation, roof and floor insulation, air penetration, glass type and window size). Then by using the SPSS software, the relationships have been extracted to connect the energy of the building with these factors. Then, by using the SPSS software, it attempted to connect a meaningful relationship between the energy consumption of the building and the mentioned factors. Also, the energy efficiency of the building was optimized by converting the data to the neural network, by using the genetic algorithm. Finally, this study was also carried out in warm and dry areas, to describe the accuracy of the results, and in each step, appropriate validations have been done.

Soft Computing Techniques for Clustering in WSN

The large Wireless Senor Networks (WSNs) comprises Sensor Nodes (SN) in some hundreds with sensing and communication capabilities. Major limitation of WSN is limited energy source of SN. Clustering is one of energy efficient method for energy conservation in WSNs. Clustering is the process to distribute SN in various logical groups known as cluster. Each cluster bears a Cluster Head (CH), who is responsible for transmitting aggregated data of its cluster to Base Station (BS). The literature is enriched by various clustering protocols proposed with the assistance of soft computing. This paper, presents the survey of soft computing paradigm-based clustering protocols.

Energy performance analysis of pasta and macaroni factory-a case study

The great expansion of industries in Ethiopia has significantly increased the demand for the limited energy source of the country. Hence, effective and efficient way of utilizing the available energy is a crucial issue in all industries. This study investigates the energy consumption performance and possible energy saving potentials of Pasta and Macaroni Factory-a case of Africa PLC which is located in Adama city. It is the biggest pasta and macaroni producing factory in the city and consuming a very large amount of energy. The thermal and electrical energy consumption of the factory has been analyzed based on the actual data measured. The thermal performances of the two boilers (steam generators) are analyzed using an indirect method (i.e., calculating the different losses) and the typical boiler efficiency obtained are 81% and 80% for boiler #1 and #2 respectively. It is found that the major heat loss from the boilers is due to the dry exhaust gas. Similarly, water chiller, air compressor, electrical motors, pumps and lighting system equipment energy utilization have been analyzed. The various energy saving measures are analyzed and it is found that the industry can save 2,301 GJ/year of electrical energy by using high efficient motors instead of the existing normal standard motors, 782.6 GJ/year of heat energy can be recovered from the dry exhaust gas by using air preheater and 1,221 GJ/year of heat energy can be recovered by controlling the air to fuel ratio which is a significant energy saving potential. Finally this study reveals that the total possible annual bill saving potential of the factory is 1,676,871 ETB.

Mitigation of Certain Power Quality Issues in Wind Energy Conversion System Using UPQC and IUPQC Devices

Due to limited conventional energy sources and to meet the increase of load demand there is a need for utilization of renewable energy sources. Among the all renewable energy sources wind energy is widely used and is highly sustainable as compared to other sources of energy. Many wind energy conversion devices working with doubly fed induction generators and synchronous generators and it is integrated to the grid produces the power quality issues like as voltage sags, swells, harmonics, voltage imbalance and short interruptions etc. Many power electronic based Flexible AC Transmission Systems (FACTS) are designed to solve above problems and facilitate to meet the required power demand. In this paper, UPQC (Unified Power Quality Conditioner) and IUPQC (Improved Unified Power Quality Conditioner) models are designed to mitigate the above power quality issues. In this paper, mainly voltage sags, voltage swells and harmonics are considered as a power quality issues to analyze the UPQC and IUPQC devices. The conventional PID controller is employed in control circuit of both the devices. It also discusses the comparative analysis between UPQC and IUPQC devices. The MATLAB/SIMULINK Software is used for above analysis.

A fork in the road: Which energy pathway offers the greatest energy efficiency and CO2 reduction potential for low-carbon vehicles?

A future energy system for road transport requires optimised energy use and primary energy decarbonisation to achieve global CO2 reduction goals. Simultaneously decarbonising transport with other sectors of the economy places additional demands on limited low-carbon energy sources, requiring efficient processes within a fuel pathway from energy source to -energy use. Battery electric vehicles (BEVs) and fuel-cell electric vehicles (FCEVs) are low-carbon options that reduce tailpipe emissions, but differ in overall efficiency, associated carbon intensity, and cost. Current commercialised technologies, as well as theoretical maximums, are aggregated in a stochastic analysis to quantify the energy efficiency and CO2 differences for BEV and FCEV energy systems. Carbon capture and storage improves source-to-wheels CO2 intensity for hydrogen produced from steam methane reformation (27 gCO2/km with carbon capture and store and 140 gCO2/km without for light-duty FCEVs). Light-duty BEVs have a lower CO2 intensity (11 gCO2/km) using decarbonised grid electricity and are 65% more efficient than light-duty FCEVs using grid energy. These effects translate to heavy-good vehicles but with added complexity. In a maximised trailer volume scenario, electric and fuel-cell heavy-good vehicles have similar projected carbon intensities from a natural gas primary energy source, but electric heavy-good vehicle using conventional battery systems or an electric road system are able to achieve a 55% and 67% carbon reduction (gCO2/m3 km) compared to fuel-cell heavy-goods vehicles, respectively.

Design principles for biochemical oscillations with limited energy resources

As biochemical systems may frequently suffer from limited energy resources so that internal molecular fluctuation has to be utilized to induce random rhythm, it is still a great theoretical challenge to understand the elementary principles for biochemical systems with limited energy resources to maintain phase accuracy and phase sensitivity. Here, we address the issue by deriving the energy accuracy and the sensitivity-accuracy trade-off relations for a general biochemical model, analytically and numerically. We find that, biochemical systems consume much lower energy cost by noise-induced oscillations to keep almost equal efficiency to maintain precise processes than that by normal oscillations, elucidating clearly the survival mechanism when energy resources are limited. Moreover, an optimal system size is predicted where both the highest sensitivity and accuracy can be reached at the same time, providing a new strategy for the design of biological networks with limited energy sources.

Decompositions for MPC of Linear Dynamic Systems with Activation Constraints

The interconnection of dynamic subsystems that share limited resources are found in many applications, and the control of such systems of subsystems has fueled significant attention from scientists and engineers. For the operation of such systems, model predictive control (MPC) has become a popular technique, arguably for its ability to deal with complex dynamics and system constraints. The MPC algorithms found in the literature are mostly centralized, with a single controller receiving the signals and performing the computations of output signals. However, the distributed structure of such interconnected subsystems is not necessarily explored by standard MPC. To this end, this work proposes hierarchical decomposition to split the computations between a master problem (centralized component) and a set of decoupled subproblems (distributed components) with activation constraints, which brings about organizational flexibility and distributed computation. Two general methods are considered for hierarchical control and optimization, namely Benders decomposition and outer approximation. Results are reported from a numerical analysis of the decompositions and a simulated application to energy management, in which a limited source of energy is distributed among batteries of electric vehicles.

Identifying cost-optimal options for a typical residential nearly zero energy building’s design in developing countries

High population growth rate and the limited non-renewable energy sources such as fossil fuels have made different challenges for the energy supply in the building sector, especially for the residential buildings. Nearly zero energy buildings are viable solutions for reducing the dependency of the building sector on non-renewable energy sources and reducing the destructive environmental impacts of building sector during their operational period. Besides, nearly zero energy buildings are climate-specific. That means their development needs to be addressed in various economic, technical, and climatic conditions of different countries. Consequently, the present study tries to identify the cost-optimal options for designing a residential nearly zero energy building in Kabul city, the capital and largest city of Afghanistan. In this regard, the optimal options are identified using energy simulation and non-dominated sorting genetic algorithm. The results showed that due to some economic limitations such as high interest rates and low energy prices, improving the performance of the building envelope has played a crucial role in determining the cost-optimal options for a nearly zero energy building design in Kabul city. For the optimal options, the payback period is two years, and the total energy consumption is reduced by 83%.

Random Access and Detection Performance of Internet of Things for Smart Ocean

Over the last decade, the Internet of Things (IoT) has been employed as an enabling technology for the smart ocean. As one of the key technologies in the IoT, machine-type communication (MTC) has been considered to support devices’ connectivity. In the MTC, random access is introduced for devices to share a common access channel during the packet transmission with low signaling overhead. However, the collision caused by the presence of multiple devices is inevitable. Since maritime sensors have limited energy sources, in this article, we propose a relay-aided random access (RARA) scheme for the smart ocean, where retransmissions are carried out by maritime buoys with the relay function, to deal with collisions. In the RARA scheme, a base station (BS) is able to recover multiple collided signal packets simultaneously by using multiuser detection with multiple copies of collided signals forwarded by buoy nodes. As a result, our proposed scheme becomes energy efficient and reliable to be suitable for the smart ocean. Theoretical and simulation results show that a high throughput and a low outage probability can be achieved with a large number of buoy nodes.