Energy-saving Scheme Research Articles

Assessment method of comprehensive energy saving potential of distribution network considering source-load power uncertainty

Abstract The comprehensive energy-saving potential evaluation method of the energy-saving schemes of a distribution network considering the power uncertainty of source and load is studied in this paper. The K-means clustering method is firstly employed to extract typical scenarios of distribution network, and the forward-push back method is used to calculate the power flow in typical scenarios, then energy-saving reconstruction schemes are formulated according to the power flow calculation results. A comprehensive energy saving potential evaluation index system that consists the improvement rate of network loss, line loss rate, transformer loss rate, annual electricity saving cost, annual equipment investment cost, annual maintenance cost and voltage quality improvement rate is built, and the comprehensive evaluation method based on DEMATEL-ANP-TOPSIS mixed decision model is used to evaluate the comprehensive energy-saving potential of the energy-saving reconstruction schemes regarding the index system. Finally, the optimal reconstruction scheme is selected based on the evaluation results of energy saving potential in multiple scenarios. The effectiveness of the proposed method is verified by an example in IEEE-33 node distribution network.

Energy-saving strategies on power hydraulic system: An overview

Different strategies for improving the energy efficiency of a power hydraulic system have been reviewed in this article. The energy-saving scheme is classified into three categories: S ystem design, Improving components or product functions and Loss reduction. The sub-categories of energy-saving strategies are discussed briefly. Also, different energy-saving potentials of power hydraulic system are presented in tabular form for clear understanding on the chronological development toward energy-efficient fluid power system.

Lattice based EPON energy-saving scheme analysis

• The state of the art of PON energy saving is discussed. • The lattice theory and fixed point are used to solve the sleep and doze duration time. • We examined the QoS performance based on different simulation scenarios. • We compared our results with the architecture without energy-saving mechanism. Time-division multiplexing passive optical network (TDM-PON) is referred to as a green network because it consumes minimum energy compared to the other access networks technologies. The optical network unit (ONU) mainly chooses to adjust energy-saving in TDM-PON by turning off its receiver and/or transmitter for the substantial time that is called doze or sleep mode respectively. The main challenge in the TDM-PON energy-saving is finding acceptable sleep/doze duration time to achieve energy-saving and guarantee the quality of service (QoS). This paper proposes a mathematical model built based on the lattice theory, which is applied to the results of the fixed-point theory. In the domain of nonlinear systems, each monotone function on a chosen complete lattice has a fixed point, and this point can be interpreted as the solution of the system. The output of the mathematical model is the sleep/doze duration domain that satisfies all requirements and guarantees the QoS metrics. The mathematical model is adopted with doze mode conditions to evaluate the system. Simulation results approve our model that achieves energy-saving up to 63% while keeping the QoS parameters in the acceptable boundary.

Different Energy Saving Schemes in Wireless Sensor Networks: A Survey

Wireless sensor networks (WSNs) are one of the very active research area. They have many applications like military, health care, environmental monitoring and industrial monitoring. The sensor nodes have limited energy source. Since in many cases the nodes are deployed in unreachable areas, hence recharging or replacing the battery of the sensor nodes is not an option. Therefore, one must employ techniques to conserve the energy by reducing the energy consumption by the nodes. In this paper, we discuss about the different energy saving schemes investigated by different research community in WSNs to reduce the energy consumption of the nodes and thereby improving the lifetime of the overall network. Energy saving protocols such as duty cycle, energy efficient routing, energy efficient medium access control (MAC), data aggregation, cross layer design and error control code (ECC) are discussed. Sleep/wake up method is adopted by the duty cycle approach to reduce the active time of the nodes and conserve their energy. The routing and MAC protocols use suitable energy efficient algorithms for saving energy. The data aggregation aims to save energy by reducing the number of transmissions. On the other side, cross layer approach looks for a cross layer optimization solution to improve the energy efficiency of the network. ECC reduces energy consumption by virtue of coding gain it offers which allows lower signal-to-noise ratio (SNR) to achieve the same bit error rate (BER) as an uncoded system. Some techniques such as use of directional antennas, topology control and transmission power control which have been widely investigated for other ad-hoc networks for energy conservation are also discussed in brief in this paper.

Increasing the parameters of electrical distribution networks of town districts with low load density

This article presents the results of research on the parameters of electrical networks with a voltage of 6 (10) and 0.38 kV in relation to capital investments. The analysis of existing methods of estimation of parameters before designing for power supply networks in a small town with low load density is carried out. In modern conditions, in the distribution of electrical networks is of paramount importance the introduction of energy-saving schemes and parameters of power supply systems. One of the main ways to implement them is to increase the efficiency of 6-10 / 0.38 kV networks. In the actual design of electrical networks, economic proportionality can not always be maintained for various reasons: the impact of technical constraints, the discreteness of the rated power of transformers and cable crossing scales, a significant deviation of individual capacities of consumers from the average value. In that case there is an increase in the reduced costs. A methodology for determining the optimal power of transformer substations and optimal sections of 0.38 kV power transmission lines is proposed, taking into account the probable nature of the applied load. When assembling the power supply circuit for the optimal form of parameters, voltage, principles of voltage regulation and reactive power compensation. Decisions of this kind are substantiated by technical and economic comparisons of a series of technically acceptable variants of power supply networks. An important measure that facilitates the selection of the most economical option is the assessment of the proposed project, which relates to the selection of the optimal capacity of transformer substation (TS) networks using calculation formulas. The aim of the research was to improve the existing methods on the basis of separate accounting of the reliability coefficient of 0.38 kV and 6-10 kV network. Key words - electric power supply network, network parameters, transformer substation, load density, line wire section, specific load, unit costs, optimum parameter, distribution networks, electric energy.

Energy saving based lighting system optimization and smart control solutions for rail transportation: Evidence from China

As the natural resources are becoming exhausted, energy consumption by metro systems dominates internal transportation resources in urban areas. The comprehensive exploration of energy improvements in lighting system energy is necessary. To evaluate the energy-saving potential and identify the efficiency improvement opportunities for lighting operations in metro systems, an intelligent energy management system for metro stations is examined through a case study in Nanchang city of China. First, the study explores the main factors influencing the lighting energy consumption of metro systems and analyses the lighting distribution in different station regions. Second, DIALux software is employed to optimize and monitor the best illuminating effect for hall lighting in the selected station. Third, an intelligent model is proposed for the lighting system based on the energy-saving scheme and solution using BECH energy analysis software combined with DIALux software. A thermal model is proposed to verify the energy and load performances. Results show that (1) the proper layout by means of DIALux software, can not only meet the functional demands of lighting but also reduce energy consumption; (2) intelligent lighting control system can improve the lighting energy-saving design, and the lighting control framework is capable of refined control; and (3) based on the performance analyses, the solution with the adopted DALI digital light adjustment is helpful for increasing passengers' comfort and realizing the goals reduction.The novelty is to integrate the lighting energy saving solution with software within an intelligent management and verified its valuable application, it is practical for construction emission control.

Energy Optimization for Software-Defined Data Center Networks Based on Flow Allocation Strategies

Nowadays, energy consumption has become an important issue in data center networks. The most promising energy-saving schemes are those that shut down unnecessary network devices and links while meeting the demand of traffic loads. Existing research mainly focuses on the strategies of energy savings in software-defined data center networks (SD-DCN). Few studies have considered both energy savings and the quality of service (QoS) of the traffic load. In this paper, we investigate the energy savings guaranteed by traffic load satisfaction ratio. To ensure the minimum-power consumption in data centers, we formulate the SD-DCN energy consumption optimization problem as an Integer Linear Programming model. To achieve a high success rate for traffic transmission, we propose three flow scheduling strategies. On this foundation, we propose a strategy-based Minimum Energy Consumption (MEC) heuristic algorithm to ensure the QoS satisfaction ratio in the process of energy optimization. The results show that our algorithm can save energy efficiently under the conditions of low traffic load and medium traffic load. Under high traffic load, our algorithm can achieve better network performance than existing solutions in terms of quality of service satisfaction ratio of flow allocation.

Energy analysis and heat recovery opportunities in spray dryers applied for effluent management

Thermal dewatering using spray dryers is an energy-intensive process, which recently, applied for removal of water from industrial effluents by evaporation. Reduction of energy consumption is vital to reduce operating cost in addition to sustainable development. In this paper, the modern integrated energy savings scheme is proposed in four parts. (i) An advanced energy saving configuration named as a hybrid heat recovery system for a spray dryer, (ii) Developed rigorous but simple mathematical model for direct and hybrid heat recovery system, (iii) A generalized performance indicator for investigation of environmental impact on energy recovery called as ‘Sustainability Index’ is proposed for thermal systems and demonstrated for spray dryer, and finally (iv) The proposed methods are explained with the help of an illustrative example taken from the literature. Up to 80% recirculation ratio, performance enhancement, and Sustainability Index are significantly higher for the hybrid heat recovery system than the direct heat recovery system, while for higher than 80% recirculation ratio, both are approaching towards nearly same value. Furthermore, with increasing recirculation ratio, moisture recirculation into the drying chamber also increases, which reduces the requirement of the mass flow rate of dry hot air due to the higher heat capacity of recirculated moisture. A reduction in hot air requirement reduces the high-grade blower power in addition to net heat supplied. Dryer efficiency and sustainability index, both show a strong dependency on the amount of heat recovery for spray dryer.

Power Allocation Based on Proportional-Integral Controller in Femtocell Networks With Consideration of Maximum Power Constraint

In this paper, a two-tier uplink femtocell network operating in orthogonal frequency-division multiple access is investigated. Femtocell base stations endowed with cognitive capacity can sense the void spectrum of macrocell. We aim at an energy-saving scheme of power allocation for femtocell users. The new idea that performance of Femtocell networks can be analyzed using control theory is proposed in this paper. A simple and novel power control algorithm is designed based on the virtual Proportional-Integral (PI) controller. When considering the maximum power constraints, different from the proof of the convergence via standard interference functions, we establish a linear system with state saturation (maximum power constraint) for femtocell networks, and the power's convergence is verified in theory with iterative linear matrix inequality algorithm. Two introduced control parameters not only guarantee the stability of power control algorithm, but also can adjust the transient response and save energy. Numerical results illustrate the convergence performance and advantages of the PI algorithm.

A market-oriented incentive mechanism for emergency demand response in colocation data centers

Rapidly developing colocation data centers (or colocations, for short) have become important participants in emergency demand response (EDR) programs. Different from traditional data centers, in colocations, tenants control their own servers; thus, they may not coordinate to reduce their power consumption. In this paper, to encourage tenants to join EDR programs, we propose a market-oriented incentive mechanism, MicDR, which can effectively reduce energy costs. MicDR includes a local incentive mechanism (LiMec), a global incentive mechanism (GiMec) and a server-sharing incentive mechanism (SiMec). LiMec motivates tenants to improve their energy efficiency locally. GiMec encourages tenants to improve their energy efficiency by requesting public server resources. To support the requests sparked by GiMec, SiMec encourages tenants to share idle server resources. A (1+ϵ)-approximation algorithm is proposed to achieve an asymptotic optimal energy-saving scheme. The performance of the proposed algorithm is evaluated, and trace-driven simulations verify the effectiveness and feasibility of MicDR.

Energy-Aware Virtual Optical Network Embedding in Sliceable-Transponder-Enabled Elastic Optical Networks

Network virtualization has been widely considered to improve the resource efficiency of network infrastructure by allowing multiple virtual networks to coexist on a shared substrate network. With the exponential growth of Internet traffic, the network energy consumption incurs a considerable increase around the world. In this paper, we consider energy-aware virtual optical network embedding (EA-VONE) issue in flexible-grid elastic optical networks (EONs), while sliceable transponders (TPs) are assumed to be equipped in each node. First, an integer linear programming (ILP) model for the energy-minimized VONE is developed to optimally solve this problem. Due to the non-scalability of the ILP model, we then design two energy-saving policies for data centers (DCs) and TPs in the process of the node mapping and link mapping, respectively. Based on the two policies, two heuristic schemes are also developed: 1) DC-EA scheme, which only considers DC energy-saving in the node mapping procedure and 2) DC&TP-EA scheme, which simultaneously considers the energy-saving for both the DCs in the node mapping and TPs in the link mapping. Moreover, offline and online EA-VONE algorithms are developed. To investigate the benefits of the two energy-saving (i.e., DC-EA and DC&TP-EA) schemes, a benchmark scheme is also realized, which only maintains traffic-balancing (TB) policy without any energy-saving consideration. The simulation results indicate that our proposed DC&TP-EA scheme achieves the maximum power saving efficiency compared with the DC-EA and TB schemes. Also, in the DC-EA and DC&TP-EA schemes, the effect of DC energy saving is very remarkable when the traffic load is smaller. With the increase of traffic load, the DC energy saving may matter less, meanwhile, the TP energy-saving plays a more and more important role. Moreover, both the DC&TP-EA and DC-EA schemes maintain similar blocking performance as that of the TB scheme, which shows the superiority of our proposed schemes.

Benchmarking Energy consumption in Nigeria Universities

That energy is an important development factor is now common knowledge. Without energy, services and societal activities will virtually grind to a halt. In Nigeria, there are several federal and state universities that receive their funding from the government. Because of their peculiar nature as knowledge-transfer-based institutions, the energy source predominantly in use in the universities is electricity. Therefore, the issues of electric energy availability, consumption and costs in universities with resident students and staff quarters can present a formidable challenge to any responsible administration. Due to the inadequate and epileptic supply of electricity in our universities, this paper establishes the need for baseline energy consumption profile in the Universities as a framework for future energy savings scheme and policy formation. This will help to identify where energy is being wasted, together with appropriate energy efficiency measures that can be considered in order to reduce energy consumption, costs and mitigate associated environmental externalities.

A Clustering-Based Energy Saving Scheme for Dense Small Cell Networks

A Clustering-Based Energy Saving Scheme for Dense Small Cell Networks

Mobility Prediction-Based Autonomous Proactive Energy Saving (AURORA) Framework for Emerging Ultra-Dense Networks

Increased network wide energy consumption is a paramount challenge that hinders wide scale ultra-dense networks (UDNs) deployments. While several energy saving (ES) enhancement schemes have been proposed recently, these schemes have one common tenancy. They operate in reactive mode, i.e., to increase ES, cells are switched ON/OFF reactively in response to changing cell loads. Though, significant ES gains have been reported for such ON/OFF schemes, the inherent reactiveness of these ES schemes limits their ability to meet the extremely low latency and high QoS expected from future cellular networks vis-a-vis 5G and beyond. To address this challenge, in this paper we propose a novel user mobility prediction based autonomous proactive energy saving (AURORA) framework for future UDN. Instead of observing changes in cell loads passively and then reacting to them, AURORA uses past hand over traces to determine future cell loads. This prediction is then used to proactively schedule small cell sleep cycles. AURORA also incorporates the effect of cell individual offsets for balancing load among cells to ensure QoS while maximizing ES. Extensive system level simulations leveraging realistic SLAW model based mobility traces show that AURORA can achieve significant energy reduction gain without noticeable impact on QoS.

URT train energy-saving scheme optimized on case intelligence using SRS and RBF

Great challenge of energy consumption in urban rail transit (URT) has been attracting much greater concerns for its more complicated impact factors. To find the energy-efficient train speed curve is the essential way for energy-saving propulsion, but it is a difficult task full of uncertainty knowledge involving in real-time train operation, which is a complicated CSP (constraint satisfaction problem) with so much inconsistent constrains that cannot be solved effectively. The paper proposes case intelligence based on CBR (case-based reasoning) to acquire the train operation preferences from the former stored cases, and constructs a flexible system integrated with efficient machine learning methods for synthesis-reasoning. The subsequent research indicates that similarity rough sets (SRS) and radial basis function network (RBF) can conquer the complexity and uncertainty of real problem, for the experimental results indicates that the hybrid system gives a fine performance as shown in real-time URT train operation.

Train Energy-Saving Scheme Optimized On Case Intelligence with Synthesis-Reasoning Technology in Urban Rail Transit

Train energy consumption in URT has been attracted much greater concerns for it becomes more serious with the large scale operation and expansion of operation network. One of the important ways for energy-saving propulsion is to find the energy-efficient train speed curve, which is a complicated CSP (constraint satisfaction problem) with uncertainty, and cannot be solved effectively with such inconsistent constrains. The case intelligent based on CBR (case-based reasoning) is proposed in this paper for its problem-solving ability, for which the domain expertise is rich while rule knowledge deficient, to construct a flexible system integrated with efficient machine learning components and acquire the train operation preferences from the former stored cases. The experiments testing on the spot indicates that the system performs well in synthesis-reasoning, which can conquer the complexity and uncertainty of real problem from both RBR (Rule-based reasoning) and CBR, to minimize the energy consumption for train traction with punctuality and safety demands.

Utilizing The Heat Of Flue Gases Of The Boiler Room By Using The Organic Renkine Cycle

A feasibility of the installation of energy saving cogeneration plant in the high-power water heating boiler room has been studied. The boiler-room is equipped with the four PTVM-100 boilers with the heat capacity of 100 GCal/year that fire natural gas. The two boilers are used to cover the heat loading of it. The energy-saving power generating plant was built on the basis of organic Renkine cycle (ORC) and it is heated by boiler flue gases of 90 to 117 °С.Technical characteristics of PTVM-100 boilers were analyzed using the process flow diagrams and their average thermal loading in summer, in winter and for transient seasons was calculated. Many energy-saving schemes were proposed for the ORC to utilize the heat of flue gases of boilers. Consideration was given to the freon characteristics that are used for the operation with low-temperature energy carriers. The freons R600aand R142b were chosen as promising low-boiling actuating media for the ORC. Based on a minimum of required investments we selected a simple heat balance circuit with the ORC loop. A comparison of computation characteristics of heat balance circuit in summer, in winter and during transient periods showed that freon R600a is an efficient actuating medium for it. It has been shown that the payback period for suggested cogeneration plants of 100, 200 and 300 KW is equal to 11, 13 and 16 months, accordingly (the project realization time was not taken into consideration) for the investments of 200, 400 and 600 thousand USD.

Energy-efficient heterogeneous extractive distillation system for the separation of close-boiling cyclohexane/cyclohexene mixture

Abstract Cyclohexane and cyclohexene are close-boiling compounds with relative volatility extremely close to unity, thus, separation via conventional distillation is impractical. In this paper, an energy-efficient heterogeneous extractive distillation system using ethylene glycol as heavy entrainer is proposed. By adding ethylene glycol into the system, large liquid-liquid envelope will form. However, the principle of separation is not exclusively the formation and split of heterogeneous azeotrope like that of a typical heterogeneous azeotropic distillation process, but also because of ethylene glycol greatly enhances the relative volatility of cyclohexane over cyclohexene when treated as a heavy entrainer. The proposed heterogeneous extractive distillation column includes a top decanter and no rectifying section. After establishing the base design of the proposed system, energy-saving schemes are also suggested to further reduce the total annual cost and the annual operating cost. The results show that the proposed heterogeneous extractive distillation system with a process-to-process heat exchanger has the predominant benefit of the lowest total annual cost. To compare the optimal result of this design flowsheet with a recently published separation method utilizing two reactive-distillation columns, our proposed design is much more economical with 61.4% savings in total annual cost and 64.6% savings in annual operating cost.

Energy-efficient hadoop for big data analytics and computing: A systematic review and research insights

As the demands for big data analytics keep growing rapidly in scientific applications and online services, MapReduce and its open-source implementation Hadoop gained popularity in both academia and enterprises. Hadoop provides a highly feasible solution for building big data analytics platforms. However, defects of Hadoop are also exposed in many aspects including data management, resource management, scheduling policies, etc. These issues usually cause high energy consumption when running MapReduce jobs in Hadoop clusters. In this paper, we review the studies on improving energy efficiency of Hadoop clusters and summarize them in five categories including the energy-aware cluster node management, energy-aware data management, energy-aware resource allocation, energy-aware task scheduling and other energy-saving schemes. For each category, we briefly illustrate its rationale and comparatively analyze the relevant works regarding their advantages and limitations. Moreover, we present our insights and figure out possible research directions including energy-efficient cluster partitioning, data-oriented resource classification and provisioning, resource provisioning based on optimal utilization, EE and locality aware task scheduling, optimizing job profiling with machine learning, elastic power-saving Hadoop with containerization and efficient big data analytics on Hadoop. On one hand, the summary of studies on energy-efficient Hadoop presented in this paper provides useful guidance for the developers and users to better utilize Hadoop. On the other hand, the insights and research trends discussed in this work may inspire the relevant research on improving the energy efficiency of Hadoop in big data analytics.

Dynamic power allocation based on second-order control system in two-tier femtocell networks

In this paper, we investigate the joint uplink power allocation problem for the macrocell and femtocells in the new view of Control Theory. Since the wireless channels in the macrocell and the femtocells fluctuate with time, we aim at an energy-saving and adaptive power allocation scheme that is robust to channel fluctuations. An optimal power allocation problem, which can satisfy the requirement of signal-to-interference-plus-noise ratio and subject to the maximum power constraint, is formulated. To obtain the robust power allocation of each user (both macrocell and femtocell users), a second-order control system is created for each cell (macrocell and femtocell). According to the second-order control system and considering the maximum power constraint, we derive a distributed robust power control algorithm. The dynamic performance and convergence of the formulated system are analyzed based on control theory. The advantage of the scheme is that some dynamic control indexes can be set in advance and the dynamic process can be controlled by setting appropriate parameters. Since femtocells share the same spectrum with the macrocell, the interference from femtocells to the macrocell base station has to be controlled to protect the normal communication of the macrocell. Then an admission control algorithm is proposed to remove the user that causes the serious interference to the macrocell, if the signal-to-interference-plus-noise ratio requirement of the macrocell user can not be satisfied. Two algorithms are particularly attractive, especially in view of practical implementation issues. Numerical simulation results are presented to illustrate the effectiveness and advantages of the proposed algorithms.