Achieving the renewable energy integration target will require the extensive engagement of consumers and the private sector in investment and operation of renewable-based energy systems. Virtual power plants are an efficient way to implement this engagement. In this paper, the detailed costs and benefits of implementing a realistic virtual power plant (VPP) in Western Australia, comprising 67 dwellings, are calculated. The VPP is designed to integrate and coordinate rooftop solar photovoltaic panels (PV), vanadium redox flow batteries (VRFB), heat pump hot water systems (HWSs), and demand management mechanisms. An 810-kW rooftop solar PV system is designed and located using the HelioScope software. The charging and the discharging of a 700-kWh VRFB are scheduled for everyday use over a year using an optimization algorithm, to maximize the benefit of it for the VPP owners and for the residents. The use of heat pump HWSs provides a unique opportunity for the residents to save energy and... [more]

Energy-saving strategies cannot be implemented without having detailed and regular power consumption data of a facility. The installation of an energy monitoring and data logging system can help in planning energy efficiency improvement policies by providing daily, monthly, and yearly energy consumption reports and graphs. The purpose of this study was to demonstrate the impact of an energy monitoring and management system on the improvement of energy efficiency in the industrial sector of developing countries. This study introduced an energy monitoring and data logging system installed in an automobile factory in Pakistan. Energy consumption data, which also included power quality data, were collected with the help of energy analyzers and transmitted to a centralized supervisory control and data acquisition (SCADA) software for data logging and monitoring purposes. This system was developed by combining Modbus with industrial Ethernet to communicate real-time energy consumption data o... [more]

Europe aims to diversify energy sources and reduce greenhouse gas emissions. On this field, large PV power growth is observed that may cause problems in existing networks. This paper examines the impact of distributed PV systems on voltage quality in a low voltage feeder in terms of the European standard EN 50160. As the standard defines allowable percentage of violation during one week period, time-series analyses are done to assess PV hosting capacity. The simulations are conducted with 10-minute step and comprise variable load profiles based on Gaussian Mixture Model and PV profiles based on a distribution with experimentally obtained parameters. In addition, the outcomes are compared with “snapshot” simulations. Next, it is examined how energy storage utilization affects the hosting capacity. Several deployments of energy storages are presented with different number and capacity. In particular, a greedy algorithm is proposed to determine the sub-optimal energy storage deployment ba... [more]

In this research, a model is proposed for predicting the number of days absent from work due to sick or health-related leave among workers in the industry sector, according to ergonomic, social and work-related factors. It employs selected microdata from the Sixth European Working Conditions Survey (EWCS) and combines a genetic algorithm with Multivariate Adaptive Regression Splines (MARS). The most relevant explanatory variables identified by the model can be included in the following categories: ergonomics, psychosocial factors, working conditions and personal data and physiological characteristics. These categories are interrelated, and it is difficult to establish boundaries between them. Any managing program has to act on factors that affect the employees’ general health status, process design, workplace environment, ergonomics and psychosocial working context, among others, to achieve success. This has an extensive field of application in the energy sector.

The increasing presence of nonprogrammable renewable energy sources (RES) forces towards the development of new methods for voltage control. In the case of centralized generation, the hierarchical regulation or secondary voltage regulation (SVR) is guaranteed by coordinated voltage and reactive power controls in transmission systems. This type of regulation loses effectiveness when the generation becomes distributed and based on small and medium sized generators. To overcome this problem, it is important that also distributed generators, typically based on RES, participate in the voltage regulation. By starting from the methodologies already applied, this work wants to present a new method for involving distributed generators in SVR. The novelty is given by the application of an existing methodology to the new configuration of electrical grids characterized by a relevant distributed generation. The aim is to control the distributed generators (DGs) as coordinated sources of reactive po... [more]

50 m3 of legacy liquid radioactive waste at the Saakadze site in Georgia was treated using a modular type facility with apparatuses encased in three metallic 200 L drums using as purification method the sorption/ion exchange technology. The main contaminant of water in the underground tank was the long-lived radionuclide 226Ra. The casing of processing equipment enabled an effective conditioning of all secondary waste at the end of treatment campaign which resulted in the fully purified water stored on site for further reuse or discharge, and three 200 L metallic drums with cemented radioactive waste which are currently safely stored.

It is very important to minimize the waste generation for decontamination of the reactor coolant system in a nuclear facility. As an alternative to commercial decontamination technologies, an inorganic acid chemical decontamination (SP-HyBRID) process can be effectively applied to the decontamination because it can significantly reduce the waste generation. In this study, the decontamination of a contaminated reactor coolant pump shaft from a nuclear facility was conducted using the SP-HyBRID process. First, equipment for a mock-up test of the decontamination was prepared. Detailed experimental conditions for the decontamination were determined through the mock-up test. Under the detailed conditions, the contaminated shaft was successfully decontaminated. The dose rate on the shaft surface was greatly reduced from 1400 to 0.9 μSv/h, and the decontamination factor showed a very high value (>1500).

In modern power systems, reliable provision of grid services (e.g., primary and ancillary services) are highly dependent on automation systems in order to have monitoring, processing, decision making and communication capabilities. The operational flexibility of automation systems is essential for the reliable operation of power systems during and after disruptive events. However, this is restricted by integrated hardware-software platforms. Therefore, it will be difficult to reconfigure control strategies during run time. This paper presents the concept of Grid Function Virtualization (GFV) as a potential approach to improve the operational flexibility of grid automation systems. GFV has been proposed to offer a new way to deploy and manage grid services by leveraging virtualization technology. The main idea of GFV is to run grid services (i.e., software implementation of services) independently from underlying hardware. To realize the important design considerations, the GFV architec... [more]

The cyber−physical system (CPS) architecture provides a novel framework for analyzing and expanding research and innovation results that are essential in managing, controlling and operating complex, large scale, industrial systems under a holistic insight. Power systems constitute such characteristically large industrial structures. The main challenge in deploying a power system as a CPS lies on how to combine and incorporate multi-disciplinary, core, and advanced technologies into the specific for this case, social, environmental, economic and engineering aspects. In order to substantially contribute towards this target, in this paper, a specific CPS scheme that clearly describes how a dedicated cyber layer is deployed to manage and interact with comprehensive multiple physical layers, like those found in a large-scale modern power system architecture, is proposed. In particular, the measurement, communication, computation, control mechanisms, and tools installed at different hierarch... [more]

The decommissioning of nuclear facilities indicates that the site is finally released according to a limited or unlimited site reuse purpose. In this process, the assessment of exposure dose to decommissioning workers and nearby residents is essential. Based on MARSSIM, a widely used decommissioning guideline in the United States, derivation of the exposure dose and derived concentration guideline level (DCGL) is mandatory using the probabilistic analysis of the RESRAD code. Here, DCGL is the radionuclide-specific concentration that satisfies the site release criteria. By applying the priority 1 parameter, which has the greatest effect on the dose, the dose is derived through deterministic and probabilistic analyses. The results were compared and analyzed. The purpose of this study was to provide a basic database that can be applied to the development of parameter lists and distributions suitable for the characteristics of nuclear facilities in South Korea. In addition, the process of... [more]

A high penetration of distributed generators, such as solar and wind power generators in low voltage network systems, impose voltage rise problems. Reactive power control of distributed generators can contribute to mitigating the voltage rise. In the existing reactive power control, reactive power was controlled using only one local variable, such as voltage at point of connection or the active power output of distributed generator. In case of PF(P) method, which provides certain power factors, depending on the active power of distributed generator, the voltage regulation ability is strong, but network losses are large. Q(V) method, which provides a certain amount of reactive power depending on the local voltage, has few network losses, but the voltage regulation ability is weak. In this paper, a reactive power control method that combines the PF(P) method and Q(V) method was proposed. The proposed method determines the reactive power output by using the active power of the distributed... [more]

This paper presents the idea of a combined analysis of long-term power quality data using cluster analysis (CA) and global power quality indices (GPQIs). The aim of the proposed method is to obtain a solution for the automatic identification and assessment of different power quality condition levels that may be caused by different working conditions of an observed electrical power network (EPN). CA is used for identifying the period when the power quality data represents a different level. GPQIs are proposed to calculate a simplified assessment of the power quality condition of the data collected using CA. Two proposed global power quality indices have been introduced for this purpose, one for 10-min aggregated data and the other for events—the aggregated data index (ADI) and the flagged data index (FDI), respectively. In order to investigate the advantages and disadvantages of the proposed method, several investigations were performed, using real measurements in an electrical power ne... [more]

Effective detection of electricity theft is essential to maintain power system reliability. With the development of smart grids, traditional electricity theft detection technologies have become ineffective to deal with the increasingly complex data on the users’ side. To improve the auditing efficiency of grid enterprises, a new electricity theft detection method based on improved synthetic minority oversampling technique (SMOTE) and improve random forest (RF) method is proposed in this paper. The data of normal and electricity theft users were classified as positive data (PD) and negative data (ND), respectively. In practice, the number of ND was far less than PD, which made the dataset composed of these two types of data become unbalanced. An improved SOMTE based on K-means clustering algorithm (K-SMOTE) was firstly presented to balance the dataset. The cluster center of ND was determined by K-means method. Then, the ND were interpolated by SMOTE on the basis of the cluster center to... [more]

Reactive power sharing among distributed generators (DGs) in islanded microgrids (MGs) presents control challenges, particularly in the mismatched feeder line condition. Improved droop control methods independently struggle to resolve this issue and centralized secondary control methods exhibit a high risk of collapse for the entire MG system under any failure in the central control. Distributed secondary control methods have been recently proposed to mitigate the reactive power error evident in the presence of mismatched feeder lines. This paper details a mathematical model of an adaptive virtual impedance control that is based on both leaderless and leader-followers consensus controls with a novel triangle mesh communication topology to ensure accurate active and reactive power sharing. The approach balances an enhanced rate of convergence with the anticipated implementation cost. A MATLAB/Simulink model with six DG units validates the proposed control performance under three differe... [more]

This paper presents a study on revenue active electrical energy meters. The huge installation along the distribution network of these devices made them a key element for energy billing, but also for monitoring the grid status. Hence, it is evident that the relevance of guaranteeing a trusty metering performance, and consequently a proper standardization, is needed. The operation of the meters is regulated by standards harmonized with the European Directive 2014/32/EU (known as MID). Still, and not infrequently, compliance to some legacy standards is declared on the device specifications. Thus, a brief comparison between the latest standards is presented. In particular, the focus was set on evaluating the potential impact of the harmonic disturbances on the energy meter accuracy, since they are omnipresent in the modern power networks. The evaluation has been carried out on three off-the-shelf class B meters by means of a new test procedure that considers realistic and quasi-realistic h... [more]

Transactive energy is a novel approach for energy management and trading, which can be used in microgrids to facilitate the integration of distributed energy resources (DERs) in existing networks. The key feature in transactive energy is using market-based solutions for energy management. Hence, an appropriate transactive energy market (TEM) framework should be designed to enable and incentivize DER owners to participate in different markets. The efficient implementation of TEM for microgrid energy management encompasses the application of a variety of design principles. In this rapidly developing area, this paper presents a complete proposal of the TEM as a framework for the design, implementation, and deployment of transactive energy solutions for energy management in microgrids. In particular, we outline the requirements to design an effective market mechanism for the TEM. The applicability of this perspective is demonstrated through the introduction of the Monash Microgrid as a rea... [more]

Off-grid power systems based on photovoltaic and battery energy storage systems are becoming a solution of great interest for rural electrification. The storage system is one of the most crucial components since inappropriate design can affect reliability and final costs. Therefore, it is necessary to adopt reliable models able to realistically reproduce the working condition of the application. In this paper, different models of lithium-ion battery are considered in the design process of a microgrid. Two modeling approaches (analytical and electrical) are developed based on experimental measurements. The derived models have been integrated in a methodology for the robust design of off-grid electric power systems which has been implemented in a MATLAB-based computational tool named Poli.NRG (POLItecnico di Milano—Network Robust desiGn). The procedure has been applied to a real-life case study to compare the different battery energy storage system models and to show how they impact on t... [more]

This paper studies the system unbalance caused by rooftop Photovoltaic Generation Systems (PVGSs) in distribution networks and proposes an improved method. The voltage and current unbalance studies for three extreme cases considering all rooftop PVGSs being connected to one single phase and then the stochastic analyses for the integration cases of rooftop PVGSs are considered. These three extreme cases lead to severe system unbalance problems. An improving method that combines the On Load Tap Changer (OLTC) and the optimal phase arrangement of distribution transformers is proposed in this paper to mitigate the system unbalance. The OLTC-based improving method is applied first. If the system unbalance is still out of range, the optimal phase arrangement of distribution transformers is further used to mitigate the system unbalance problem. The objective function of optimal phase arrangement is to minimize the system unbalance with the constraints of voltage limits, line flow limit, etc.... [more]

A modern renewable energy forecasting system blends physical models with artificial intelligence to aid in system operation and grid integration. This paper describes such a system being developed for the Shagaya Renewable Energy Park, which is being developed by the State of Kuwait. The park contains wind turbines, photovoltaic panels, and concentrated solar renewable energy technologies with storage capabilities. The fully operational Kuwait Renewable Energy Prediction System (KREPS) employs artificial intelligence (AI) in multiple portions of the forecasting structure and processes, both for short-range forecasting (i.e., the next six hours) as well as for forecasts several days out. These AI methods work synergistically with the dynamical/physical models employed. This paper briefly describes the methodology used for each of the AI methods, how they are blended, and provides a preliminary assessment of their relative value to the prediction system. Each operational AI component add... [more]

A fully integrated piezoelectric energy harvesting interface is proposed for harvesting energy from irregular human motion. To handle irregular pulse inputs generated by the piezoelectric transducer (PZT), the proposed harvesting interface includes a wake-up controller that activates the harvesting interface only when human motion is detected and deformation is applied on the piezoelectric material, thereby keeping static power loss low. The PZT output voltage is increased to its peak voltage by removing any type of external load capacitance seen by the PZT during its deformation. Once the peak voltage is detected, a multi-voltage conversion-ratio-based switched-capacitor circuit is activated to transfer PZT-generated energy to the battery in multiple ratio steps to maximize the conversion efficiency, with the help of a carefully designed harvesting controller. To deal with open-circuit voltages (VOCS) higher than the maximum voltage tolerated (VMAX) by available technology, capacitive... [more]

The number of renewable energy systems is still increasing. To reduce the worldwide CO2 emissions, there will be even more challenges in the distribution grids like currently upcoming charging stations or heat pumps. All these new electric systems in the low voltage (LV) and medium voltage (MV) levels are characterized by an unsteady behavior. To monitor and predict the behavior of these new flexible systems, a grid state forecast is needed. This software tool calculates wind, photovoltaic, and load forecasts. These power forecasts are already in the focus of research, but there are some specific use cases, which require a more specific solution. To get a variously applicable software tool, different new functions to improve an already existing grid state forecast tool were developed and evaluated. For example, it will be proofed if a grid state forecast tool can be improved by calculating the number or the base load of the loads in grid areas by just one available measurement. Another... [more]

Electricity consumption forecasting is a vital task for smart grid building regarding the supply and demand of electric power. Many pieces of research focused on the factors of weather, holidays, and temperatures for electricity forecasting that requires to collect those data by using kinds of sensors, which raises the cost of time and resources. Besides, most of the existing methods only focused on one or two types of forecasts, which cannot satisfy the actual needs of decision-making. This paper proposes a novel hybrid deep model for multiple forecasts by combining Convolutional Neural Networks (CNN) and Long-Short Term Memory (LSTM) algorithm without additional sensor data, and also considers the corresponding statistics. Different from the conventional stacked CNN−LSTM, in the proposed hybrid model, CNN and LSTM extracted features in parallel, which can obtain more robust features with less loss of original information. Chiefly, CNN extracts multi-scale robust features by various f... [more]

Crude oil is one of the strategic energies and plays an increasingly critical role effecting on the world economic development. The fluctuations of crude oil prices are caused by various extrinsic and intrinsic factors and usually demonstrate complex characteristics. Therefore, it is a great challenge for accurately forecasting crude oil prices. In this study, a self-optimizing ensemble learning model incorporating the improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN), sine cosine algorithm (SCA), and random vector functional link (RVFL) neural network, namely ICEEMDAN-SCA-RVFL, is proposed to forecast crude oil prices. Firstly, we employ ICEEMDAN to decompose the raw series of crude oil prices into a group of relatively simple subseries. Secondly, RVFL is used to forecast the target values for each decomposed subseries individually. Due to the complex parameter settings of ICEEMDAN and RVFL, SCA is introduced to optimize the parameters for ICEEMDAN... [more]

Data Distribution Service (DDS) has emerged as a potential solution for data communication challenges in smart grids. DDS is designed to support quality communication for large scale real-time systems through a wide range of QoS policies. However, a smart grid involves various types of communication applications running on different computing environments. Some environments have limited computing resources such as small memory and low performance, which makes it difficult to accommodate DDS. In this paper, we present a feature-based approach for tailoring DDS to configure lightweight DDS by selecting only the necessary features for the application in consideration of the resource constraints of its running environment. This allows DDS to serve as a uniform communication middleware across the smart grid, which is critical for interoperability. We analyze DDS in terms of features and design them using Unified Modeling Language (UML) and Object Constraint Language (OCL) based on inheritan... [more]

In this paper, a vehicle−grid integration (VGI) control strategy for radial power distribution networks is presented. The control schemes are designed at both microgrid level and distribution level. At the VGI microgrid level, the available power capacity for electric vehicle (EV) charging is optimally allocated for charging electric vehicles to meet charging requirements. At the distribution grid level, a distributed voltage compensation algorithm is designed to recover voltage violation when it happens at a distribution node. The voltage compensation is achieved through a negotiation between the grid-level agent and VGI microgrid agents using the alternating direction method of multipliers. In each negotiation round, individual agents pursue their own objectives. The computation can be carried out in parallel for each agent. The presented VGI control schemes are simulated and verified in a modified IEEE 37 bus distribution system. The simulation results are presented to show the effe... [more]