The assessment of electromagnetic compatibility (EMC) is important for both technical and legal reasons. This manuscript addresses specific issues that should be taken into account for proper EMC assessment of energy systems that use power electronic interfaces. The standardized EMC measuring techniques have been used in a laboratory setup consisting in two identical DC/DC converters with deterministic and random modulations. Measuring difficulties caused by the low frequency envelopes, resulting from frequency beating accompanying aggregation of harmonic components of similar frequencies, were indicated as a phenomenon that might lead to significant problems during the EMC assessment using currently binding standards. The experimental results describing deterministic and random modulated converters might be useful for practitioners implementing power interfaces in microgrids and power systems as well as for researchers involved in EMC assurance of power systems consisting in multiple... [more]

The integration of advanced measuring technologies in distribution systems allows distribution system operators to have better observability of dynamic and transient events. In this work, the applications of distribution grid measurement technologies are explored in detail. The main contributions of this review are: (a) a comparison of eight advanced measurement devices for distribution networks, based on their technical characteristics, including reporting periods, measuring data, precision, and sample rate; (b) a review of the most recent applications of micro-Phasor Measurement Units, Smart Meters, and Power Quality Monitoring devices used in distribution systems, considering different novel methods applied for data analysis; and (c) an input-output table that relates measured quantities from micro-Phasor Measurement Units and Smart Meters needed for each specific application found in this extensive review. This paper aims to serve as an important guide for researches and engineers... [more]

Complexity is a widely acknowledged feature of urban areas. Among the different levels to which this definition applies, the energy sector is one of the most representative of this way of conceiving cities. An evidence of this complexity can be detected in the growing impact of prosumers. Prosumers produce energy to meet their own demands, distribute it directly to neighbors and, eventually, store the energy neither consumed nor distributed. The modelling of distribution networks is a challenging task that requires ad hoc models to simulate the mutual energy exchanges occurring among prosumers. To serve at this scope, this paper proposes an agent-based model aiming at determining which operating conditions enhance the energy distribution among prosumers and diminish the supply from traditional power plants. An application of the model within a residential territory is then presented and simulations are conducted under two scenarios: the first investigating the distribution among prosum... [more]

The detection, mitigation, and classification of power quality (PQ) disturbances have been issues of interest in the power system field. This paper proposes an approach to detect and classify various types of PQ disturbances based on the Stockwell transform (ST) and decision tree (DT) methods. At first, the ST is developed based on the moving, localizing, and scalable Gaussian window to detect five statistical features of PQ disturbances such as the high frequency of oscillatory transient, distinction between stationary and non-stationary, the voltage amplitude oscillation around an average value, the existence of harmonics in a disturbance signal, and the root mean square voltage at the internal period of sag, swell or interruption. Then, these features are classified into nine types, such as normal, sag, swell, interruption, harmonic, flicker, oscillatory transient, harmonic voltage sag, and harmonic voltage swell by using the DT algorithm that is based on a set of rules with the str... [more]

Recently, with the penetration of numerous Distributed Energy Resources (DER) in Smart Distribution Networks (SDN), Local Transactive Markets have emerged. Exchanging energy between all participants of local markets results in the satisfaction of producers and consumers. Based on these issues, this study provides a novel framework for the participation of SDN-independent entities in wholesale and local electricity markets simultaneously. In this regard, the considered system’s players, namely Distribution System Operator (DSO) and DER Aggregator (AG), take part within local as well as wholesale markets in two-day ahead and real-time stages. Moreover, to deal with the inherent conflict between the existing players’ interests, a Stackelberg game-based technique is proposed. In the raised competition, the leader, DSO, attempts to minimize its operating costs, while the follower, DER AG, tends to maximize its profit. Therefore, actors’ actions choices within both markets are made non-coope... [more]

The number of battery energy storage systems (BESSs) installed in the United Kingdom and worldwide is growing rapidly due to a variety of factors, including technological improvements, reduced costs and the ability to provide various ancillary services. The aim of this paper is to carry out a comprehensive literature review on this technology, its applications in power systems and to identify potential future developments. At first, the main BESSs projects in the UK are presented and classified. The parameters provided for each project include rated power, battery technology and ancillary services provided, if any. In the next section, the most commonly deployed ancillary services are classified and described. At the same time, the nomenclature found in the literature is explained and harmonised. The second part of the paper focuses on future developments and research gaps: ancillary services that currently are not common but that are likely to be deployed more widely in the future wil... [more]

It is widely recognized that in the transition from conventional electrical power systems (EPSs) towards smart grids, electrical voltage frequency will be greatly affected. This is why this research is extremely valuable, especially since rate-of-change-of-frequency (RoCoF) is often considered as a potential means of resolving newly arisen problems, but is often challenged in practice due to the noise and its oscillating character. In this paper, the authors further developed and tested one of the new technologies related to under-frequency load shedding (UFLS) protection. Since the basic idea was to enhance the selected technology’s readiness level, a hardware-in-the-loop (HIL) setup with an RTDS was assembled. The under-frequency technology was implemented in an intelligent electronic device (IED) and included in the HIL setup. The IED acted as one of several protection devices, representing a last-resort system protection scheme. All main contributions of this research deal with usi... [more]

This article presents an original predictive strategy, based on a new mid-term forecasting model, to be used for trading physical electricity futures. The forecasting model is used to predict the average spot price, which is used to estimate the Risk Premium corresponding to electricity futures trade operations with a physical delivery. A feed-forward neural network trained with the extreme learning machine algorithm is used as the initial implementation of the forecasting model. The predictive strategy and the forecasting model only need information available from electricity derivatives and spot markets at the time of negotiation. In this paper, the predictive trading strategy has been applied successfully to the Iberian Electricity Market (MIBEL). The forecasting model was applied for the six types of maturities available for monthly futures in the MIBEL, from 1 to 6 months ahead. The forecasting model was trained with MIBEL price data corresponding to 44 months and the performances... [more]

Recently, the development in combining point forecasts of electricity prices obtained with different length of calibration windows have provided an extremely efficient and simple tool for improving predictive accuracy. However, the proposed methods are strongly dependent on expert knowledge and may not be directly transferred from one to another model or market. Hence, we consider a novel extension and propose to use principal component analysis (PCA) to automate the procedure of averaging over a rich pool of predictions. We apply PCA to a panel of over 650 point forecasts obtained for different calibration windows length. The robustness of the approach is evaluated with three different forecasting tasks, i.e., forecasting day-ahead prices, forecasting intraday ID3 prices one day in advance, and finally very short term forecasting of ID3 prices (i.e., six hours before delivery). The empirical results are compared using the Mean Absolute Error measure and Giacomini and White test for co... [more]

Although renewable technologies are progressing fast, there are still challenges such as the reliability and availability of renewable energy sources and their cost issues due to capital intensity that hinder their broad adoption. This research aims at developing a configuration-sizing approach to enhance the cost efficiency and sourcing reliability of renewable energies integrated in microgrids. To achieve this goal, various technologies were considered, such as solar PV, wind turbines, converters, and batteries for system configuration with minimization of net present cost (NPC) as the objective. Grid connection scenarios with up to 100% renewable contribution were analyzed. The results show that the integration of renewable technologies with some grid backup could reduce the levelized cost of energy (LCOE) to about half of the price of the electricity that the university purchases from the grid. Also, different kinds of solar tracker systems were studied. The outcome shows that by u... [more]

This paper aims to develop the long short-term memory (LSTM) network modelling strategy based on deep learning principles, tailored for the very short-term, near-real-time global solar radiation (GSR) forecasting. To build the prescribed LSTM model, the partial autocorrelation function is applied to the high resolution, 1 min scaled solar radiation dataset that generates statistically significant lagged predictor variables describing the antecedent behaviour of GSR. The LSTM algorithm is adopted to capture the short- and the long-term dependencies within the GSR data series patterns to accurately predict the future GSR at 1, 5, 10, 15, and 30 min forecasting horizons. This objective model is benchmarked at a solar energy resource rich study site (Bac-Ninh, Vietnam) against the competing counterpart methods employing other deep learning, a statistical model, a single hidden layer and a machine learning-based model. The LSTM model generates satisfactory predictions at multiple-time step... [more]

In 2018, the revised Energy Performance of Buildings Directive (EPBD) included for the first time the application of a smart readiness indicator (SRI). Based on the fact that load shifting in and across buildings plays an increasingly important role to improve efficiency and alleviate the integration of renewable energy systems, the SRI is also aimed at providing an indication of how well buildings can interact with the energy grids. With the clustering of buildings into larger entities, synergies related to the integration of renewable energy and load shifting can be efficiently exploited. However, current proposals for the SRI focus mainly on qualitative appraisals of the smartness of buildings and do not include the wider context of the districts. Quantitative approaches that can be easily applied at an early planning stage are still mostly missing. To optimize infrastructure decisions on a larger scale, a quantifiable perspective beyond the building level is necessary to evaluate a... [more]

Wind Power Plants (WPPs) are generally located in remote areas with weak distribution connections. Hence, the value of Short Circuit Capacity (SCC), WPP size and the short circuit impedance angle ratio (X/R) are all very critical in the voltage stability of a distribution system connected WPP. This paper presents a new voltage stability model based on the mathematical relations between voltage, the level of wind power penetration, SCC and X/R at a given Point of Common Coupling (PCC) of a distribution network connected WPP. The proposed model introduces six equations based on the SCC and X/R values seen from a particular PCC point. The equations were developed for two common types of Wind Turbine Generators (WTGs), including: the Induction Generator (IG) and the Double Fed Induction Generator (DFIG). Taking advantage of the proposed equations, design engineers can predict how the steady-state PCC voltage will behave in response to different penetrations of IG- and DFIG-based WPPs. In a... [more]

Microgrids have emerged as a solution to address new challenges in power systems with the integration of distributed energy resources (DER). Inverter-based microgrids (IBMG) need to implement proper control systems to avoid stability and reliability issues. Thus, several researchers have introduced multi-objective control strategies for distributed generation on IBMG. This paper presents a review of the different approaches that have been proposed by several authors of multi-objective control. This work describes the main features of the inverter as a key component of microgrids. Details related to accomplishing efficient generation from a control systems’ view have been observed. This study addresses the potential of multi-objective control to overcome conflicting objectives with balanced results. Finally, this paper shows future trends in control objectives and discussion of the different multi-objective approaches.

In response to climate change and environmental issues, many countries have gradually optimized carbon market management and improved the carbon market trading mechanism. Carbon price prediction plays a pivotal role in promoting carbon market management when investors are guided by prediction to conduct rational carbon trading. A novel carbon price prediction methodology is constructed based on ensemble empirical mode decomposition, improved bat algorithm, and extreme learning machine (EEMD-IBA-ELM) in this study. Firstly, the carbon price is decomposed into multiple regular intrinsic mode function (IMF) components by the ensemble empirical mode decomposition, and partial autocorrelation analysis (PACF) is used to find IMF historical data affecting the current value of IMF. Secondly, the improved bat algorithm (IBA) is used to heighten extreme learning machine (ELM) while adaptive parameters are obtained. Finally, EEMD-IBA-ELM was established to predict carbon price. Simultaneously, en... [more]

The emergence of Internet of Things (IoT) architectures and applications has been the driver for a rapid growth in wireless technologies for the Machine-to-Machine domain. In this context, a crucial role is being played by the so-called Low Power Wide Area Networks (LPWANs), a bunch of transmission technologies developed to satisfy three main system requirements: low cost, wide transmission range, and low power consumption. This last requirement is especially crucial as IoT infrastructures should operate for long periods on limited quantities of energy: to cope with this limitation, energy harvesting is being applied every day more frequently, and several different techniques are being tested for LPWAN systems. The aim of this survey paper is to provide a detailed overview of the the existing LPWAN systems relying on energy harvesting for their powering. In this context, the different LPWAN technologies and protocols will be discussed and, for each technology, the applied energy harves... [more]

Digital flicker detection devices need to store a large amount of evaluation data during measurement process, which leads to high requirements for hardware resources and algorithm execution efficiency. In this paper, a digital flicker detection method based on probability resampling is studied. In particular, before statistical evaluation, probability resampling is applied to screen the instantaneous flicker visual sensitivity data to compress redundant data. Additionally, the effectiveness of the method was numerically simulated and experimentally tested. The results show that the proposed method can accurately measure the voltage flicker value and can effectively compress the redundant evaluation data to be evaluated and has significant advantages in releasing hardware storage space, in improving algorithm execution efficiency and real-time performance, and in reducing processor workload. This method provides an engineering application reference for designing digital flicker detector... [more]

Microgrids have been popularized in the past decade because of their ability to add distributed generation into the classic distribution systems. Protection problems are among several other problems that need solutions in order to extract the full capability of these novel networks. This research follows the branches of two major solutions, namely adaptive protection and protection optimization. Adaptive protection implementation with a novel concept of clustering is considered, and protection setting optimization is done using a novel hybrid nature-inspired algorithm. Adaptive protection is utilized to cope with the topology variations, while optimization techniques are used to calculate the protection settings that provide faster fault clearances in coordination with backup protection. A modified IEEE 14 bus system is used as the test system. Validation was done for the fault clearing performance. The selected algorithm was effective than most other algorithms, and the clustering app... [more]

Electricity demand is increasing, as a result of increasing consumers in the electricity market. By growing smart technologies such as smart grid and smart energy management systems, customers were given a chance to actively participate in demand response programs (DRPs), and reduce their electricity bills as a result. This study overviews the DRPs and their practices, along with home energy management systems (HEMS) and load management techniques. The paper provides brief literature on HEMS technologies and challenges. The paper is organized in a way to provide some technical information about DRPs and HEMS to help the reader understand different concepts about the smart grid, and be able to compare the essential concerns about the smart grid. The article includes a brief discussion about DRPs and their importance for the future of energy management systems. It is followed by brief literature about smart grids and HEMS, and a home energy management system strategy is also discussed in... [more]

Renewable Energy Sources are becoming widely spread, as they are sustainable and low-carbon emission. They are mostly penetrating the MV Distribution Networks as Distributed Generators, which has determined the evolution of the networks’ control and supervision systems, from almost a complete lack to becoming fully centralized. This paper proposes innovative voltage control architectures for the distribution networks, tailored for different development levels of the control and supervision systems encountered in real life: a Coordinated Control for networks with basic development, and an optimization-based Centralized Control for networks with fully articulated systems. The Centralized Control fits the requirements of the network: the challenging harmonization of the generator’s capability curves with the regulatory framework, and modelling of the discrete control of the On-Load Tap Changer transformer. A realistic network is used for tests and comparisons with the Local Strategy curre... [more]

In this article, the practical comparison of the operational performance of the modular (or multiport) and non-modular bidirectional buck/boost (bi-BB) DC/DC converter is realized. The main contribution of the work is the evaluation of both concepts based on various aspects, considering the qualitative indicators of the systems relevant for microgrids. Here, we discuss efficiency, electrical properties, costs, and component values. At the same time, critical comparisons are provided for converters based on SiC and GaN technology (non-modular high-voltage SiC-based dual-interleaved converter and modular low-voltage GaN-based). The concepts are specific with their operating frequency, whereby for each solution, the switching frequency is different and directly influences relevant components. The efficiency, overall system volume, output voltage ripple, and input current ripple are compared mutually between both concepts with a dependency on power delivery. These factors, together with ov... [more]

Harmonic currents of electric vehicle (EV) chargers could jeopardize the power quality of distribution systems and add to the transformer’s losses, thus degrading its lifetime. This paper assesses and mitigates the impacts of different EV chargers on distribution transformers and the voltage quality of distribution systems. The effect of state-of-charge (SOC) of the EV battery is considered through applying weighted arithmetic mean to accurately assess the impacts of EV harmonic currents on aging and losses of the EV interfacing transformer. The voltage quality of the IEEE 33-bus distribution system, supplying several EV parking lots, is also assessed at different charging levels using a fast-decoupled harmonic power flow. A new optimal harmonic power flow algorithm—that incorporates photovoltaic-based distribution generation units (DGs)—is developed to enhance the voltage quality of distribution systems, and elongate the lifetime of the substation transformer. The effectiveness of the... [more]

The cognitive smart grid (SG) communication paradigm aims to mitigate quality of service (QoS) issues in obsolete communication architecture associated with the conventional electrical grid. This paradigm entails the integration of advanced information and communication technologies (ICTs) into power grids, enabling a two-way flow of information. However, due to the exponential increase in wireless applications and services, also driven by the deployment of the Internet of Things (IoT) smart devices, SG communication systems are expected to handle large volumes of data. As a result, the operation of SG networks is confronted with the major challenge of managing and processing data in a reliable and secure manner. The existing works in the literature proposed architectures with the objective to mitigate the underlying QoS issues such as latency, bandwidth, data congestion, energy efficiency, etc. In addition, a variety of communication technologies have been analyzed for their capacity... [more]

Power systems are susceptible to disturbances due to their nature. These disturbances can cause overloads or even contingencies of greater impact. In case of an extreme situation, load curtailment is considered the last resort for reducing the contingency impact, its activation being necessary to avoid the collapse of the system. However, load shedding systems seldom work optimally and cause either excessive or insufficient reduction of the load. To resolve this issue, the present paper proposes a methodology to enhance the load curtailment management in medium voltage distribution systems using Particle Swarm Optimization (PSO). This optimization seeks to minimize the amount of load to be cut off. Restrictions on the optimization problem consist of the security operation margins of both loading and voltage of the system elements. Heuristic optimization algorithms were chosen, since they are considered an online basis (allowing a short processing time) to solve the formulated load curt... [more]

While smart meters can provide households with more autonomy regarding their energy consumption, they can also be a significant intrusion into the household’s privacy. There is abundant research implementing protection methods for different aspects (e.g., noise-adding and data aggregation, data down-sampling); while the private data are protected as sensitive information is hidden, some of the compulsory functions such as Time-of-use (TOU) billing or value-added services are sacrificed. Moreover, some methods, such as rechargeable batteries and homomorphic encryption, require an expensive energy storage system or central processor with high computation ability, which is unrealistic for mass roll-out. In this paper, we propose a privacy-preserving smart metering system which is a combination of existing data aggregation and data down-sampling mechanisms. The system takes an angle based on the ethical concerns about privacy and it implements a hybrid privacy-utility trade-off strategy, w... [more]