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The modular multilevel converter (MMC) is considered a very promising candidate for medium-voltage and/or high-power grids. One of the major concerns in half-bridge MMCs, especially with large number of levels, is the fault occurs at the converter submodule (SM). Hence, an appropriate control with an SM fault tolerance of the MMC is required to enhance its reliability. This paper addresses the issue and proposes a fault tolerant control-based adaptive carrier phase disposition pulse width modulation (AC-PDPWM) technique for MMCs with superior symmetrical and asymmetrical fault-tolerant capabilities. The proposed control-based AC-PDPWM acts to regulate the flow of energy between arms, rebalance the SM capacitors, and redistribute the pulses to the SM switches. In this study, a single-phase grid connected MMC having both symmetrical and asymmetrical fault conditions is investigated. Compared with other control methods, the proposed control can tolerate the SM fault conditions without requiring redundant SMs or additional computational burden, which decreases the cost and volume of the MMC design and simplifies its control. Simulation and experimental results are included to verify the fault-tolerant capability of the proposed control.

In previous project we made a home automation system, where we can control our appliances through Blynk app and Google assistant with the help of IFTTT. As an extension we will provide feedback to user whether the appliance is on or off. We will also use sensors like LDR for measuring light intensity in this project to make it smart. We will also include security system where in we have sensors to doors and windows and give buzzer along with an alert message to the user. On a whole we will provide a smart home automation system.

Vehicles have made extraordinary commitment to the development of current culture by fulfilling the requirements for more prominent portability in everyday life. The development of Internal Combustion Engine has contributed a ton to the car area. In any case, a lot of harmful discharges as carbon dioxide (CO2), carbon monoxide (CO), nitrogen oxides (NOx), unburned hydrocarbons (HCs, etc have been messing contamination up, a dangerous atmospheric devation, and annihilation of the ozone layer. As the current pattern proposes, this method of transport is probably going to supplant inside burning motor (ICE) vehicles soon. Every one of the primary EV segments has various innovations that are at present being used or can get conspicuous later on. Improved control assignment approach strategies are fit for securing ideal force taking care of, obliging framework errors, and fitting ongoing applications can fundamentally improve the powertrain productivity at various working conditions. Rule-based techniques are just organized and effectively implementable continuously; however, a restricted optimality in force dealing with choices can be achieved. Enhancement based strategies are more fit for achieving this optimality at the cost of expanded computational burden. Over the most recent couple of years, these improvement based strategies have been being worked on to suit continuous application utilizing more prescient, recognitive and man-made reasoning apparatuses. This paper presents a conversation about these new patterns continuously improved control assignment approach. Consequently HEVs give better fuel economy contrasted with ICE based vehicles/regular vehicle. Energy management techniques are the calculations that choose the force split among motor constantly to improve the fuel economy and advance the presentation of HEVs.

This paper analyzes the security algorithm and energy cost of wireless sensor networks in depth, and designs and implements a series of energy-optimized security solutions to ensure the secure establishment and operation of wireless sensor networks. This paper proposes an improved Ad hoc network routing protocol based on energy control. It introduces a low-energy balanced routing algorithm to reduce routing transmission energy consumption, balance network traffic, and improve the energy control performance of network routing protocols. The protocol uses a cross-layer design in this way, the route selection combines the information of the link the remaining energy. A joint function is formed by the transmit power level remaining energy. The joint function of all nodes on the path is used as the basis for route selection and applied to the route discovery stage. At the same time, the protocol introduces edge degree parameters in the establishment process, the idea of minimum energy consumption path and the introduction of energy consumption ratio parameters in the cluster skull backbone network generation process are adopted to realize the energy optimization of the path establishment process. At the same time, the protocol uses the message interaction mechanism in the path establishment process to implement a node security authentication scheme based on secret shared information without adding any routing communication messages, which effectively prevents the passive and active attacks of the attacker on the network. The results of simulation experiments prove that the secure routing protocol achieves the network’s balanced energy consumption while ensuring the secure communication of the network, and solves the energy problem.

Conventionally, the multilevel converter-based multi-terminal hybrid microgrids require a large number of power switches and have a limited operation capability under unbalanced power distribution in medium and low voltage (MV/LV) AC/DC microgrids. To solve this issue, this paper proposes the novel modular multilevel converter (MMC)-based five-terminal MV/LV hybrid AC/DC microgrids. The proposed hybrid microgrids realize the interconnection between the medium-voltage AC (MVAC), MVDC, low voltage AC (LVAC), and two LVDC terminals. In addition, the MVAC grid is connected to the AC terminal of MMC, and the MVDC microgrid is connected to the DC terminal of MMC through a dual active bridge (DAB) converter. Based on MMC, the compact interlinking converters are established, providing three LVDC terminals, which are connected to two LVDC microgrids and one LVAC microgrid through a DC/AC converter. Compared with the conventional MMC-based hybrid microgrids, the proposed topology can significantly reduce the number of power switches. Moreover, to overcome the control challenge of arm energy balancing in MMC and meet the requirement of different operation modes in microgrids, a hierarchical energy control method is proposed, where the low circulating currents are injected to balance the arm energy. Therefore, the system operation capability can be improved under unbalanced power distribution. Validation results in different conditions (power step, power reversal, and unbalanced MVAC voltages) indicate that by the proposed method, the arm energy and capacitor voltages in MMC are well balanced, and the proposed hybrid AC/DC microgrids can operate normally at different modes.

Wave energy has a significant part to play in providing a carbon-free solution to the world’s increasing appetite for energy. In many countries, there is sufficient wave energy to cater for the entire national demand, and wave energy also has some attractive features in being relatively uncorrelated with wind, solar and tidal energy, easing the renewable energy dispatch problem. However, wave energy has not yet reached commercial viability, despite the first device designs being proposed in 1898. Control technology can play a major part in the drive for economic viability of wave energy and this paper charts the progress made since the first wave energy control systems were suggested in the 1970s, and examines current outstanding challenges for the control community.

OBJECTIVE. The objective of our study was to evaluate the clinical performance of a new high-frequency (HF) microwave ablation (MWA) technology with spatial energy control for treatment of lung malignancies in comparison with a conventional low-frequency (LF) MWA technology. MATERIALS AND METHODS. In this retrospective study, 59 consecutive patients (mean age, 58.9 ± 12.6 [SD] years) were treated in 71 sessions using HF spatial-energy-control MWA. Parameters collected were technical success and efficacy, tumor diameter, tumor and ablation volumes, ablation time, output energy, complication rate, 90-day mortality, local tumor progression (LTP), ablative margin size, and ablation zone sphericity. Results were compared with the same parameters retrospectively collected from the last 71 conventional LF-MWA sessions. This group consisted of 56 patients (mean age, 60.3 ± 10.8 years). Statistical comparisons were performed using the Wilcoxon-Mann-Whitney test. RESULTS. Technical success was 98.6% for both technologies; technical efficacy was 97.2% for HF spatial-energy-control MWA and 95.8% for LF-MWA. The 90-day mortality rate was 5.1% (3/59) in the HF spatial-energy-control MWA group and 5.4% (3/56) in the LF-MWA group; for both groups, there were zero intraprocedural deaths. The median ablation time was 8.0 minutes for HF spatial-energy-control MWA and 10.0 minutes for LF-MWA (p < 0.0001). Complications were recorded in 21.1% (15/71) of HF spatial-energy-control MWA sessions and in 31.0% (22/71) of LF-MWA sessions (p = 0.182); of these complications, 4.2% (3/71) were major complications in the HF spatial-energy-control MWA group, and 9.9% (7/71) were major complications in the LF-MWA group. The median deviation from ideal sphericity (1.0) was 0.195 in the HF spatial-energy-control MWA group versus 0.376 in the LF-MWA group (p < 0.0001). Absolute minimal ablative margins per ablation were 7.5 ± 3.6 mm (mean ± SD) in the HF spatial-energy-control MWA group versus 4.2 ± 3.0 mm in the LF-MWA group (p < 0.0001). In the HF spatial-energy-control MWA group, LTP at 12 months was 6.5% (4/62). LTP at 12 months in the LF-MWA group was 12.5% (7/56). Differences in LTP rate (p = 0.137) and time point (p = 0.833) were not significant. CONCLUSION. HF spatial-energy-control MWA technology and conventional LFMWA technology are safe and effective for the treatment of lung malignancies independent of the MWA system used. However, HF spatial-energy-control MWA as an HF and high-energy MWA technique achieves ablation zones that are closer to an ideal sphere and achieves larger ablative margins than LF-MWA (p < 0.0001).

SUMMARYRegrasping is a manipulation to alternate between grasp configurations of an object to perform different tasks. We address a regrasping problem termed longitude regrasping to reposition a gripper along an elongated object. We propose an algorithm using the dynamics of the arm and a non-dexterous gripper to perform the manipulation. Energy control is used to toss the object up and catch it under the goal position. Clipped Linear Quadratic Regulator control approach is then applied to the gripper jaws to control the friction force on the object and to let it slide to the final goal position. The object sliding within the gripper is modeled as a semi-active linear joint where only dissipative forces can be applied to it. A set of experiments validated the feasibility of the method.

At present, the DC micro-grid power supply system based on new energy generation has become the primary developmental direction for improving the endurance of an unmanned surface vehicle (USV). In this study, an adaptive energy control strategy based on the moving average filtering algorithm is proposed to solve the severe impact of the pulsing load mutation on the hybrid energy storage system (HESS) in the DC micro-grid. The moving average filtering algorithm is used to filter the pulsating load power, and a battery slows the power change. Meanwhile, the super capacitor compensates for the instantaneous power mutation, optimizing the charge and discharge process of the battery. In addition, gain-varying adaptive control for the terminal voltage of the supercapacitor is adopted to stabilize it near the reference value, which solves the problem of voltage off-limit caused by the unequal output and absorption energy of the supercapacitor. The simulation results show that the proposed control strategy can effectively and quickly suppress the power fluctuation caused by the load mutation of the photovoltaic DC micro-grid system, improve the quality of the system output power, and enhance the reliability and stability of the system.

We propose a novel concept of the robot of energy control based on parallel cyber-physical-social systems for the next generation of energy and electric power systems. We thoroughly investigate its knowledge automation technologies and discuss its main challenges in preparation of promising evolution from Energy 4.0 to Energy 5.0 in China.

The internet of things (IoT) has been useful in different sectors and attracted more attention in researches. IoT technologies are mainly used to enable the physical objects to collect and exchange data by using wireless network protocols. Moreover, IoT technologies have been applied in different applications including energy control and monitoring. However, energy efficiency has been the main challenge in industries, when comparing the energy consumption, production and cost. Therefore, this research project develop an IoT-based Intelligent Energy Efficiency Management System to enhance energy efficiency in current industries and the Industry 4.0 by focusing on smart industries, where the results show that the data of humidity and temperature was monitored directly to the NODE-RED platform, and a notification to personal email to an operator. Thus, help an operator to act accordingly based on the change of the data prescribed on dashboard.

Regenerative braking systems are an efficient way to increase the energy efficiency of electric rail vehicles. During the development phase, testing of a regenerative braking system in an electric vehicle is costly and potentially dangerous. For this reason, Hardware-In-the-Loop (HIL) simulation is a useful technique to conduct the system’s testing in real time where the physical parts of the system are replaced by simulation models. This paper presents a HIL simulation of a tram regenerative braking system performed on a scaled model. First, offline simulations are performed using a measured speed profile in order to validate the tram, supercapacitor, and power grid model, as well as the energy control algorithm. The results are then verified in the real-time HIL simulation in which the tram and power grid are emulated using a three-phase converter and LiFePO4 batteries. The energy flow control algorithm controls a three-phase converter which enables the control of energy flow within the regenerative braking system. The results validate the simulated regenerative braking system, making it applicable for implementation in a tram vehicle.

Independence is a major concern for individuals with severe handicaps. Welfare assistance robotic technology is a popular solution to this concern (e.g. Hashino, 1996; Takahashi, Ogawa, and Machida, 2002 and 2008). Assistance robotic technologies offer potential alternatives to the need for human helpers. People bound to wheelchairs have limited mobility reliant on battery life, which only allows for short distance travel between charges. In addition, recharging batteries is time consuming.

Many degrees of freedom are available for the branch energy control of modular multilevel converters. These degrees of freedom comprise different components of the common-mode voltage and the internal circulating currents. If all degrees of freedom are used simultaneously, undesired cross-couplings occur in the branch energy control. In the conventional branch energy control, either the internal circulating currents or the common-mode voltage are used to avoid the coupling terms. The paper presents a novel solution that uses both the circulating currents and the common-mode voltage while omitting the couplings. Thereby, the branch currents and thus the losses in the branches can be reduced without affecting the control dynamics. The proposed control approach is validated through simulations and experimentally on a downscaled converter prototype. Furthermore, the improved performance is demonstrated by means of a comparison to the conventional control. In general, the proposed control approach is expected to be especially beneficial for drive systems operated below rated speed and for a low-voltage ride-through of grid-tied converters.

Recently, a Quasi-Three-Level Operation Mode for a new modular multilevel converter topology has been proposed. This paper presents a fundamental improvement of this operation mode which is achieved through a closed-loop branch current and energy control. The proposed approach uses the available degrees of freedom of the topology to actively balance the energies of the input capacitors and module capacitors. Moreover, the branch currents are controlled during both constant output voltage levels and transitions. In comparison to the operation mode from the literature, the proposed approach enables a stable operation with reduced input capacitances, module capacitances, peak branch currents, and converter losses. This is validated through simulations.

This paper discusses a revolutionary system of interrelated computing devices and technologies known as the Internet of Things (IoT), with the objective of improving energy efficiency for both residential and commercial buildings. A thorough review of a profusion of empirical surveys and studies was carried out to fully comprehend the use of IoT to improve energy efficiency in buildings. The present study also examines methods by which these technologies can be further enhanced to provide solutions that are more requisite. Most of the studies reviewed discuss the applicability of various aspects of IoT to a specific application, and were invariably concerned with the problem of efficient heating systems in buildings. Some aspects of the core elements of IoT, such as the hardware and software required for control are analyzed in all the studies reviewed. Although the kind of application in each study is different, similar patterns are discernible in their design factors. Some common design factors include: the choice of sensors and actuators and their powering methods; control strategies for gathering data and actuating devices; collection of historical data to predict future energy use; and interaction approaches between IoT elements. Results showed that certain variables are application-specific and must all be factored into the decisions. Finally, from the studies surveyed, some areas of future research were recommended.

This study has been developed to analyse the fuzzy logic rules in thermal energy assessment of box type solar cooker under local climatic condition in Chennai, Tamilnadu, India. Different cooking test of food stuffs has been produced with vessels viz., copper, aluminium, bottom side and bar plate is coating black paint mixed in Nanoparticles (Al2O3) for the system. The influence of the solar cooker parameters are performed to the following in fuzzy logic rules. It has been established a cooker to thermal act of (15.14%), Nanoparticles adeptness are (7.10%). It is received to give the shortly time for the enhancement of the cooker affordable to a manufacture.

In the new era, the monitoring and control of electricity production and consumption in a factory remain important objectives. Following the emergent Industry 4.0 paradigm, plants and manufacturing companies shift to a new development strategy of automation. We present a solution and the supporting technology to create a factory network infrastructure for monitoring and optimizing the electrical power consumption using Kaa IoT technology for data transfer and infrastructure configuration.

Published in IFAC-PapersOnLine (51)11:758-763, 2018; International audience; This work is a positioning research paper for energy efficient building based on ICT solutions. Through the literature about the solutions for energy control of buildings during operational phase, a 3-layers model is proposed to integrate these solutions: first level consists in communication technologies, second level is about data modelling and third level is related to decision-making tools. For each level, key research topics and remaining problems are identified in order to achieve a concrete step forward. 1. CONTEXT AND PROBLEMATICS Through studies on ICT solutions for energy control of buildings, a 3-layers model is proposed to integrate these solutions and position a new way for energy efficiency. The building sector is the largest user of energy and CO 2 emitter in the EU, estimated at approximately 40% of the total consumption (Sharples et al., 1999). According to the International Panel on Climate Change (European Union, 2010), 30% of energy used in buildings could be reduced with net economic benefits by 2030. Such a reduction, however, is meaningless unless "sustainability" is considered. Because of these factors, healthy, sustainable, and energy efficient buildings have become active topics in international research; there is an urgent need for a new kind of high-technology driven and integrative research that should lead to the massive development of smart buildings and, in the medium term, smart cities. From a building lifecycle perspective, most of the energy (~80%) is consumed during the operational stage of the building (European Union, 2010) (Bilsen et al., 2013). Reducing building energy consumption may be addressed by the physical modifications which can be operated on a building like upgrading windows, heating systems or modifying thermic characteristics by insulating. Another possible path to reduce the energy consumption of a building is to use Information and Communication Technologies (ICT). According to the International Panel on Climate Change, a reduction of energy even greater than the 30% can be targeted by 2030 by considering ICT solutions. In support of this claim, some specialists believe that ICT-based solutions have the potential to enable 50-80% greenhouse gas reduction globally. In this respect, ICT innovation opens prospects for the development of a new range of new services highly available, flexible, safe, easy to integrate, and user friendly (Bilsen et al., 2013). This, in turn, should foster a sophisticated, reliable and fast communication infrastructure for the connection of various distributed elements (sensors, generators, substations...) that enables to exchange real-time data, information and knowledge needed to improve efficiency (e.g., to monitor and control energy consumption), reliability (e.g., to facilitate maintenance operations), flexibility (e.g., to integrate new rules to meet new consumer expectations), and investment returns, but also to induce a shift in consumer behaviour.

The analysis of fork-join queueing systems has played an important role for the performance evaluation of distributed systems where parallel computations associated with the same job are carried out and a job is considered served only when all the parallel tasks it consists of are served and then joined. The fork-join nodes that we consider consist of K ≥ 2 parallel servers each of which is equipped with two First Come First Served queues, namely the service-queue and the join-queue. The former stores the tasks waiting to be served while the latter stores the served tasks waiting to be joined. Under heavy load conditions, the variance of the service times associated with the tasks tends to cause long join-queue lengths. In this work, we propose an algorithm to dynamically control the servers’ speeds (e.g., via frequency scaling), that aims at reducing the power consumption of the servers whose join-queue lengths are longer than the others’. Under Markovian assumptions, we provide a model for the performance evaluation of the system in saturation that allows us to derive the expression for the steady-state distribution, the system’s throughput and balance index. Finally, we derive the analytical expression for the marginal state probabilities of each server and provide upper and lower bounds for the expected power consumption.

© 2017 The Authors. A smart city exploits sustainable information and communication technologies to improve the quality and the performance of urban services for citizens and government, while reducing resources consumption. Intelligent energy control in buildings is an important aspect in this. The Internet of Things can provide a solution. It aims to connect numerous heterogeneous devices through the internet, for which it needs a flexible layered architecture where the things, the people and the cloud services are combined to facilitate an application task. Such flexible IoT hierarchical architecture model will be introduced in this paper with an overview of each key component for intelligent energy control in buildings for smart cities. publisher: Elsevier articletitle: A Review on Internet of Things Solutions for Intelligent Energy Control in Buildings for Smart City Applications journaltitle: Energy Procedia articlelink: http://dx.doi.org/10.1016/j.egypro.2017.03.239 content_type: article copyright: © 2017 The Author(s). Published by Elsevier Ltd. ispartof: pages:770-779 ispartof: 8TH INTERNATIONAL CONFERENCE ON SUSTAINABILITY IN ENERGY AND BUILDINGS, SEB-16 vol:111 pages:770-779 ispartof: 8th International Conference on Sustainability in Energy and Buildings (SEB) location:Turin, Italy date:11 Sep - 13 Sep 2016 status: published

China has the largest number of industrial parks in the world. These parks are not only crucial for the country to accelerate industrialization but also to achieve its climate change targets. Constructing CO2 emission inventories for industrial parks is the first step in analysing the park's emission patterns and designing low-carbon policies. However, most of the previous emission accounts for industrial parks adopted various scopes and methodologies, making them incomparable with each other. This study develops a self-consistent methodology and framework for China's industrial parks based on enterprise-level data. We consider both Scope 1 and 2 emissions and construct the inventories by 19 energy types and 39 industrial sectors, which are consistent with the existing national, provincial, and city-level emission inventories. Such sectoral-based emission inventories will be not only able to provide data support for the design of emission/energy control policies, but also help the central/local governments evaluate a park's emission reduction performance. Finally, an empirical study is applied to four industrial parks to verify the method. In addition, we review the eco-industrial park programmes in Japan and South Korea, as well as their emissions accounting framework. We find that most of the Japanese industrial parks provide Scope 1, 2 and 3 emissions, while for South Korea, parks mostly focus on Scope 1 emissions. The discussion of Japan and South Korea's eco-industrial parks have referential significance for the construction China's low-carbon parks.

© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works With an increasing number of renewable energy resources being integrated into the power system through power electronics, conventional power plants based on large synchronous machines tend to be reduced in the upcoming future. With the modular multilevel converter (MMC) as the state-of-the-art power electronics solution for power systems, it will be necessary to operate some of these converters in grid-forming mode, in order to either preserve the stability and robustness of the ac grid or as the only solution to generate the ac grid in cases with no available synchronous generation. This article aims to understand how the internal energy control of the MMC can be used to effectively mitigate the propagation of ac power disturbances to the dc side, thanks to its buffering capability. Different energy control structures are explored, and a comprehensive discussion and comparison among them are provided, including stability analysis, transient performance, and tuning guidelines. Simplified and linear models are used to address the analysis, whereas detailed nonlinear models implemented in MATLAB Simulink are used to verify the results via time-domain simulations.

International audience; The G-protein-coupled receptor accessory protein MRAP2 is implicated in energy control in rodents, notably via the melanocortin-4 receptor1. Although some MRAP2 mutations have been described in people with obesity1-3, their functional consequences on adiposity remain elusive. Using large-scale sequencing of MRAP2 in 9,418 people, we identified 23 rare heterozygous variants associated with increased obesity risk in both adults and children. Functional assessment of each variant shows that loss-of-function MRAP2 variants are pathogenic for monogenic hyperphagic obesity, hyperglycemia and hypertension. This contrasts with other monogenic forms of obesity characterized by excessive hunger, including melanocortin-4 receptor deficiency, that present with low blood pressure and normal glucose tolerance4. The pleiotropic metabolic effect of loss-of-function mutations in MRAP2 might be due to the failure of different MRAP2-regulated G-protein-coupled receptors in various tissues including pancreatic islets.

International audience; We propose a solution for Electric Vehicle (EV) energy management in smart cities, where a deep learning approach is used to enhance the energy consumption of electric vehicles by trajectory and delay predictions. Two Recurrent Neural Networks are adapted and trained on 60 days of urban traffic. The trained networks show precise prediction of trajec-tory and delay, even for long prediction intervals. An algorithm is designed and applied on well known energy models for traction and air conditioning. We show how it can prevent from a battery exhaustion. Experimental results combining both RNN and energy models demonstrate the efficiency of the proposed solution in terms of route trajectory and delay prediction, enhancing the energy management

This paper presents a novel method for designing a decentralized fuzzy controller for DC microgrids, aiming to reduce operating costs. Therefore, a classical fuzzy control is created for each power supplying grid user based on the voltage droop control. The control of the active rectifier is then extended with respect to the electric costs as an additional input. The input membership functions of this controller are in a next step optimized with a genetic algorithm, whereas two different approaches were used: first, only the membership function of the rectifier was optimized, secondly, the energy storage system was added to the optimization. The optimization was performed in terms of minimizing the operative costs of the DC microgrid. This method and its results were in the end compared with the optimized characteristic diagrams presented in [1]. These diagrams were an extension of the voltage droop curves and the optimization was also based on the operating costs of the grid. Results achieved with the new concept are as good as in the previously presented characteristic diagrams approach. In addition optimization time is reduced significantly (up to 50 times) and the definition of membership functions is more handy.

Energy storage technology plays a role in improving new energy consumption capacities, ensuring the stable and economic operation of power systems, and promoting the widespread application of renewable energy technologies. Several new developments, ideas, approaches, and technologies have been introduced into this area from fields including materials, knowledge manage, electricity, control, and artificial intelligence. Based on the technical characteristics of renewable energy, this study reviews the roles, classifications, design optimisation methods, and applications of energy storage systems in power systems. First, we introduce the different types of energy storage technologies and applications, e.g. for utility-based power generation, transportation, heating, and cooling. Second, we briefly introduce the states of an energy storage system, along with its operation processes and energy storage capacity. Third, a comprehensive review is conducted on artificial intelligence applications in regards to optimisation system configuration, and energy control strategy, along with the applicability of different energy storage technologies. Finally, several issues and insights are discussed, offering new inspiration and concepts for the future study of integrated energy storage systems.

The performance of a positively biased external ring anode in combination with a hollow cathode (HC) discharge or a magnetron sputtering (MS) discharge, both with a Ti cathode and with Ar as working gas, is investigated. Plasma and floating potential increase as function of anode voltage. Energy-resolved mass spectrometry reveals that the kinetic energy of argon and titanium ions is enhanced by a positive anode voltage allowing for an effective energy control of plasma ions.

This paper summarises a literature review on the applications of Internet of Things (IoT) with the aim of enhancing building energy use and reducing greenhouse gas emissions (GHGs). A detailed assessment of contemporary practical reviews and works was conducted to understand how different IoT systems and technologies are being developed to increase energy efficiencies in both residential and commercial buildings. Most of the reviewed works were invariably related to the dilemma of efficient heating systems in buildings. Several features of the central components of IoT, namely, the hardware and software needed for building controls, are analysed. Common design factors across the many IoT systems comprise the selection of sensors and actuators and their powering techniques, control strategies for collecting information and activating appliances, monitoring of actual data to forecast prospect energy consumption and communication methods amongst IoT components. Some building energy applications using IoT are provided. It was found that each application presented has the potential for significant energy reduction and user comfort improvement. This is confirmed in two case studies summarised, which report the energy savings resulting from implementing IoT systems. Results revealed that a few elements are user-specific that need to be considered in the decision processes. Last, based on the studies reviewed, a few aspects of prospective research were recommended.

The merge of urbanization in Indonesia results in a sharp increase in household energy consumption. Energy conservation is a global challenge for both individuals and decision-makers. The increasing household energy consumption is mostly caused by unwanted usage of electrical energy. The purpose of this paper is to design an improved smart home electricity management system based on consumer behaviour, which will help household occupant to control the usage of electricity automatic using sensor and manual using a smartphone. The sensor used in the system are a motion sensor, temperature sensor, sound sensor, and light sensor also wireless technology is used for controlling electricity outside of the home using a smartphone. The proposed system has multiple benefits of saving electricity bill of the house and keep the owner of the house updated about home security with the ability to control the home appliances and reduce electrical energy consumption.

Increasing resource and energy efficiency for a sustainable production has led to the analyses of saving potentials and subsequently to the development of saving strategies in a multitude of disciplines. Each of those strategies resulted in numerous improvements, however, they still lack universal valid consideration. To overcome this deficit, a machine- and machine control-independent energy control system has been developed in the research group ECOMATION. The energy control system allows to execute any control- or operation-based energy optimizer. To use this energy control system more efficient machine tool controls need to be extended by additional functionality. The energy control system and the necessary migration strategy of machine tool controls will be discussed in this paper.

Continuous development of intelligent network applications drives the demand for deployment-ready hardware and software solutions. Such solutions are highly valued not only by distributed producers of energy but by energy consumers as well. The use of intelligent network applications enables the development and improvement of the quality of services. It also increases self-sufficiency and efficiency. This paper describes an example of such device that allows for the control of a dual active bridge (DAB) converter and enables its remote control in real time over an IP-based network. The details of both hardware and software components of proposed implementation are provided. The DAB converter gives a possibility to control and manage the energy between two DC power systems with very different voltage levels. Not only information, but also the quality of energy, the direction of power flow, and energy storage systems can be easily controlled through an IP-based network and power electronics converters. Information technology, together with intelligent control of power electronics technology, provides a flexible solution, especially for sustainable smart grids.

We consider the requirements of the energy-control system of the PICO laser facility and describe a design of the calorimeter based on the proposed method of laser-radiation-energy measurements using the calorimeter–sensor thermal response. We present the results of an experimental study of the calorimeter temporal parameters and dynamic analog memory.

Today, the need for a more economic handling of energy in the production context is urgent. Moreover, structural changes in the energy market are taking place due to a growing share of renewable energy sources in power generation. These circumstances require solutions to reduce and flexibilize the electric load demand of production facilities. Machine tools are subject to a wide range of applications. Besides, they integrate diverse cross-sectional technologies. Therefore, research results regarding the optimization of the load demand of machine tools can serve as a basis for the optimization of the power intake of numerous production machines. In this context, the paper at hand presents a two-step approach to optimize the electric load demand of machine tools in productive state. In a first step, a potentials analysis is carried out to identify modules suitable for load demand control. Additionally, the amount of achievable peak load reductions through managing the load for a specific use case (primary process and designated machine tool) is determined. The potentials analysis considers the load demand of auxiliary modules of a machine as well as the module-specific control mode and internal operational concept. If a sufficient potential can be detected, the actual optimization of the load profile of the machine in productive state is carried out in a subsequent step. The optimization process seeks to incorporate the independently controlled auxiliary units into a global control concept. The aim of the optimization is to find an operating schedule for the considered auxiliary units leading to a cumulative load profile featuring desired load objectives. These load objectives can be peak minimization, flexibilization, or smoothing.

In this paper we present the most innovative aspects of the EC-FP7 EcoThermo project. The main aim of the project consists on innovating the technique of heat cost allocation in buildings with a centralized heating system, overcoming the heat cost allocator drawbacks for reliability, measurement reproducibility and traceability and contexts of applications. Given the complexity of the project, we will focus on its main aspects, such as the use of a virtual sensor to estimate the radiators heating power, the design of electronic valves fitted out with an energy harvesting system and the original wireless communication protocol.

At the present time, trains in heavy haul operations are typically hauled by several diesel-electric locomotives coupled in a multiple unit. This paper studies the case of a typical consist of three Co–Co diesel-electric locomotives, and considers replacing one unit with an alternative version, with the same design parameters, except that the diesel-electric plant is replaced with flywheel energy storage equipment. The intelligent traction and energy control system installed in this unit is integrated into the multiple-unit control to allow redistribution of the power between all units. In order to verify the proposed design, a three-stage investigation has been performed as described in this paper. The initial stage studies a possible configuration of the flywheel energy storage system by detailed modelling of the proposed intelligent traction and energy control system. The second stage includes the investigation and estimation of possible energy flows using a longitudinal train dynamics simulation. The final stage compares the conventional and the proposed locomotive configurations considering two parameters: fuel efficiency and emissions reduction.

The time-optimal control for boost converters can achieve the minimum recovery time. However, their output voltage deviation is quite large. Since the minimum output voltage deviation and minimum recovery time cannot be obtained at the same time, a novel energy control is proposed to achieve a superior tradeoff between them in this paper. The peak value of the inductor current can be decreased as well. Its control parameter is easy to choose. When compared with the conventional control methods, the proposed control shows a better dynamic performance. Experimental results, which are in agreement with the theoretical analysis, are provided to verify the proposed control method.

This chapter contains sections titled: Introduction Overview of EMS Functions Power Flow Control Power Flow Stability Considerations Power System State Estimation Power System Security Contingency Analysis Optimal Preventive and Corrective Actions Dynamic Security Analysis

To evaluate the clinical performance of a new microwave ablation (MWA) system with enabled constant spatial energy control (ECSEC) to achieve spherical ablation zones in the treatment of liver malignancies.In this retrospective study, 56 hepatic tumours in 48 patients (23 men, 25 women; mean age: 59.6 years) were treated using a new high-frequency MWA-system with ECSEC. Parameters evaluated were technical success, technical efficacy, tumour diameter, tumour and ablation volume, complication rate, 90-day mortality, local tumour progression (LTP) at the 12-month follow-up, ablative margin and ablation zone sphericity. These parameters were compared using the Kruskal-Wallis test with the same parameters collected retrospectively from cohorts of patients treated with conventional high-frequency (HF) MWA (n = 20) or low-frequency (LF) MWA (n = 20).Technical success was achieved in all interventions. The technical efficacy was 100% (ECSEC) vs. 100% (LF-MWA) vs. 95% (HF-MWA). There were no intra-procedural deaths or major complications. Minor complications occurred in 3.57% (2/56), 0% (0/20) and 0% (0/20) of the patients, respectively. The one-year mortality rate was 16.1% (9/56), 15% (3/20) and 10% (2/20), respectively. The LTP was 3.57% (2/56), 5% (1/20) and 5% (1/20), respectively. The median deviation from ideal sphericity (1.0) was 0.135 (ECSEC) vs. 0.344 (LF-MWA) vs. 0.314 (HF-MWA) (p 0.001). The absolute minimal ablative margin was 8.1 vs. 2.3 vs. 3.1 mm (p 0.001).Microwave ablation of liver malignancies is a safe and efficient treatment independent of the system used. Hepatic MWA with ECSEC achieves significantly more spherical ablation zones and higher minimal ablative margins.

The Modular Multilevel Converter (MMC), being a complex system, requires a number of controllers to function properly. These range from low level switching pattern generation to high level control loops. Among these controllers are modulation techniques that calculate the insertion indices, control inputs that decide the number of sub-modules inserted in a given arm. One such technique is compensated modulation which divides the reference voltages, generated by high level controllers, by the respective arm voltages (sum of capacitor voltages) when calculating the insertion indices. This prevents the arm voltage ripple from affecting the generated output voltage. For this purpose, the arm voltages can be measured (closed-loop approach) or estimated (open-loop approach). This paper presents an arm voltage estimation technique for compensated modulation of MMCs. The proposed technique combines the benefits of the open-loop approach with that of the closed loop one. © 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Resumen Los Sistemas Solares Fotovoltaicos Autónomos (SFVA), a pesar de sus ventajas, presentan algunos inconvenientes, siendo el principal de ellos la falta de un sistema controlador de energía para optimizar su funcionamiento. Este trabajo presenta el análisis y diseño de un Sistema de Control Supervisor de Acceso Remoto, SCSAR, para clientes con acceso remoto de sistemas solares fotovoltaicos autónomos de 500 W. La función del SCSAR es la de medir y administrar la energía consumida por los usuarios del SFVA. Para ello se consideran tres variables principales: el tiempo de conexión y desconexión por carga y por día, autorizados al usuario; la corriente consumida por cada dispositivo o carga autorizado por el diseñador; el nivel de carga de la batería para mantenerlo por encima del mínimo permitido para su correcta operación. El SCSAR aquí propuesto, es un sistema que garantiza que se cumplan los objetivos de diseño, monitoreando y controlando las variables críticas de los sistemas clientes. De esta forma será posible diagnosticar remotamente los SFVA, reduciendo los tiempos y costos de soporte y mantenimiento, con el fin de brindar seguridad, disponibilidad, versatilidad, economía, robustez y confiabilidad a todos los usuarios de estas fuentes de energía alternativa. Abstract The Autonomous Photovoltaic Solar Systems (APSS), in spite of its disadvantages, offers some inconveniences, being the main one of them, the lack of an energy control system to optimize its operation. This work presents the analysis and design of a Remote Access Supervisor Control System, RASCS for customers with remote access of 500 W photovoltaic solar systems. The RASCS's function is to measure and manage the energy consumed by the users of APSS. For this reason, three main variables are considered: the time of connection and disconnection per load and per day, authorized to the user; the current consumed by each device or charger authorized by the designer; the battery charge level to keep it above the proper amount for proper operation. RASCS here is a system that ensures that it meets the design objectives, monitoring and controlling the critical variables of the customer systems. In this way, it will be possible to remotely diagnose APSS, reducing the time and costs of support and maintenance, with the completion of security, availability, versatility, economy, robustness and reliability to all users of these alternative energy sources.