Multisource energy data, including from distributed energy resources and its multivariate nature, necessitate the integration of robust data predictive frameworks to minimise prediction error. This work presents a hybrid deep learning framework to accurately predict the energy consumption of different building types, both commercial and domestic, spanning different countries, including Canada and the UK. Specifically, we propose architectures comprising convolutional neural network (CNN), an autoencoder (AE) with bidirectional long short-term memory (LSTM), and bidirectional LSTM BLSTM). The CNN layer extracts important features from the dataset and the AE-BLSTM and LSTM layers are used for prediction. We use the individual household electric power consumption dataset from the University of California, Irvine to compare the skillfulness of the proposed framework to the state-of-the-art frameworks. Results show performance improvement in computation time of 56% and 75.2%, and mean squar... [more]

The increasing prevalence and severity of wildfires, severe storms, and cyberattacks is driving the introduction of numerous microgrids to improve resilience locally. While distributed energy resources (DERs), such as small-scale wind and solar photovoltaics with storage, will be major components in future microgrids, today, the majority of microgrids are backed up with fossil-fuel-based generators. Small modular reactors (SMRs) can form synergistic mix with DERs due to their ability to provide baseload and flexible power. The heat produced by SMRs can also fulfill the heating needs of microgrid consumers. This paper discusses an operational scheme based on distributed control of flexible power assets to strengthen the operational resilience of SMR-DER integrated-energy microgrids. A framework is developed to assess the operational resilience of SMR-DER microgrids in terms of system adaptive real-power capacity quantified as a response area metric (RAM). Month-long simulation results a... [more]

Driven by the proliferation of DC energy sources and DC end-use devices (e.g., photovoltaics, battery storage, solid-state lighting, and consumer electronics), DC power distribution in buildings has recently emerged as a path to improved efficiency, resilience, and cost savings in the transitioning building sector. Despite these important benefits, there are several technological and market barriers impeding the development of DC distribution, which have kept this technology at the demonstration phase. This paper identifies specific end-use cases for which DC distribution in buildings is viable today. We evaluate their technology and market readiness, as well as their efficiency, cost, and resiliency benefits while addressing implementation barriers. The paper starts with a technology review, followed by a comprehensive market assessment, in which we analyze DC distribution field deployments and their end-use characteristics. We also conduct a survey of DC power and building profession... [more]

The energy transition to renewable energy in a democratic way is directly connected to the development of energy communities and community microgrids. Los Molinos del Rio Aguas (LMRA), an ecological community in the south of Spain, offers a promising case study for an off-grid community-owned microgrid. In this paper, the interconnection of autonomous solar home systems is proposed with the addition of community assets in order to create an off-grid community microgrid that is financially beneficial for the community. Based on this scenario, a Local Energy Market (LEM) based on Distributed Ledger (DL) technologies is implemented in order to foster the energy exchange and contribute to the social welfare of the community. The results provide a win-win scenario for the community and provides an example of an off-grid community microgrid in combination with a LEM that takes into consideration the social aspect of the community.

This research presents a secondary control for a grid-supporting microgrid with photovoltaics sources to guarantee grid code compliance and ancillary services. The secondary control accomplishes the fault ride-through, which implements a delayed signal cancellation (DSC) algorithm for negative sequence detection. Without mode switching, the proposed control strategy meets grid code requirements and ensures voltage regulation at the secondary level, which is active and more salient throughout the transient period of host grid disturbances. This control also ensures a constant supply of the microgrid’s sensitive local load while adhering to grid code requirements. Similarly, active power injection into the main grid is limited by progressively altering the MPPT operating point dependent on the depth of voltage sag to optimize reactive power injection to sustain grid voltage sag. The recommended secondary control is triggered by utilizing the DSC process’s detection algorithm to identify... [more]

The recent coronavirus (COVID-19) pandemic has wreaked havoc on the global economy, causing major shifts in energy use and output patterns. For some countries, this has had a significant effect on energy demand and carbon emissions, at least in the short term. Since the United Arab Emirates is currently exerting many efforts towards sustainability, it is important to assess and understand the impacts of the pandemic and the lockdown measurements on the local energy sectors. Data for this analysis were gathered by the Sharjah Electricity Water & Gas Authority (SEWA) for Sharjah City which is the capital of the Emirate of Sharjah. The changes in electricity after the implementation of quarantine and lockdown-like measures were assessed, and the results indicate that the electric power demand in Sharjah City was reduced in the commercial, industrial, and agricultural sectors, whereas the residential and government sectors witnessed a higher power demand. The overall electricity consumptio... [more]

With the continuous penetration and development of renewable energy power generation, the distributed grid and the microgrid are becoming increasingly important in modern power systems. In distribution networks and the microgrid, the grid impedance is comparatively large and cannot be ignored. Usually, the parallel compensation is used to improve the grid quality. In the grid with parallel compensation, the large phase angle difference between the impedance of the grid-connected inverter and the impedance of the grid at amplitude intersection will result in high frequency resonance (HFR). Because the inverter shows filter characteristics due to limited bandwidth of the controller, the parallel compensation grid, respectively, performs as the capacitance characteristic and inductance characteristic in different high frequency range. Compared with the three-phase, three-wire system, an additional zero-sequence path exists in the three-phase four-wire split capacitor inverter (TFSCI) syst... [more]

The evolution of electricity markets has led to increasingly complex energy trading dynamics and the integration of renewable energy sources as well as the influence of several external market factors contributed towards price volatility. Therefore, day-ahead electricity price forecasting models, typically using some kind of neural network, play a crucial role in the optimal behavior of market agents. The most prominent models and benchmarks rely on improving the accuracy of predictions and the time for convergence by some sort of a priori processing of the dataset that is used for the training of the neural network, such as hyperparameter tuning and feature selection techniques. What has been overlooked so far is the possible benefit of a posteriori processing, which would consider the effects of parameters that could refine the predictions once they have been made. Such a parameter is the estimation of the residual training error. In this study, we investigate the effect of residual... [more]

This article attempts to identify the key forces driving the successful digitalization of the energy sector, ensuring improvements in the energy triangle including sustainability, stability, and economic performance. The article sheds light on the diverse energy priorities at supra-, national, and managerial levels, and the role of digitalization in achieving these objectives. Catching up economies (such as Poland), being post-socialist EU member states, in order to transform its energetic sector, must overcome a number of infrastructural and social shortcomings retained as a legacy of the socialist economy. As such, sustainability (as the core priority at EU energy agenda) may not be the leading objective at both national and company level in the energy sector transformation. This article presents the results of empirical research carried out through distribution of e-questionnaire addressed to Polish managers from the energy sector. The results were analyzed using the fsQCA method. T... [more]

In a modern smart energy system, the amount of available data from various sources is growing significantly. Other sectors such as medical or social sectors exhibit the same phenomenon. Due to the amount, complexity and heterogeneity of data, a complex algorithm is required for the integration and analysis of heterogeneous data sources. The Web of Things and semantic-based approaches address the fragmentation of standards, platforms, services and technologies in smart energy and non-energy sectors, and enable heterogeneous data integration and interoperability. This paper presents SiSEG, a semantic annotation service that is developed to automate the process of annotating data and address the problem of heterogeneous data integration in a reusable and extensible way by using the fuzzy method. Moreover, the accuracy of SiGEG has been evaluated.

Battery Electric Buses (BEBs) are considerably integrated into cities worldwide. These buses have a strict schedule; thus, they could be charged in a very short time with a power level up to 600 kW. The high-power systems and short charging times imply special grid operation conditions that should be taken into account. Therefore, it is necessary to consider the influence of their charging infrastructure on the distribution system operation, especially near the charging point. This work presents two Use Cases (UCs) from two demos (Germany and the Netherlands) to investigate the impact of the slow and fast-chargers’ integrations on the power grid and environment. Fast-chargers up to 350 kW based on pantograph technology and slow-chargers up to 50 kW based on Combined Charging System Type 2 (CCS2) are used on the BEB line route and in the depot, respectively. The charging of BEBs with these solutions is studied here to investigate their impact on the grid in terms of power quality. It wa... [more]

Local area energy networks (E-LANs) are cyber-physical systems whose physical layer is a meshed low-voltage microgrid fed by a multiplicity of sources, i.e., utilities, energy storage systems, and distributed power sources. The cyber layer includes distributed measurement, control, and communication units, located at end-user premises, as well as centralized supervision and dispatchment control. As compared with standard microgrid, the E-LAN encompasses the ability for end-users to actively contribute to the operation of the microgrid while acting as independent energy traders in the electrical market. Operational goals include active contribution of end-users to power sharing, loss reduction, voltage stability, demand response, fault identification and clearing, isolation of sub-grids for maintenance, islanding, and black start. Economic goals include the possibility, for each end-user, to decide in every moment, based on convenience, how his energy and power capacity is shared with o... [more]

This paper describes the process of setting up an appropriate volt−var curve for the reactive power control of a photovoltaic (PV) inverter interconnected to a distribution line that is voltage controlled by a load ratio control transformer (LRT). Computer simulations with 360 patterns of volt−var curves applied to five actual distribution line models are presented. The number of patterns was narrowed down to 23 by using voltage, distribution-line loss, number of LRT tap operations, and a new evaluation index, the match ratio. When a power-factor constraint is imposed on the PV inverter, it may not output the reactive power according to the volt−var curve depending on the active power output. The match rate is an index to show the percentage of the operating points of the PV inverter that conform with the volt−var curve. By evaluating the match rate, it can be demonstrated if the PV inverter efficiently contributes to the voltage control, which greatly contributes to narrowing of the v... [more]

Background: Understanding the market competition is one of the most important factors for examining and assessing competition issues, and is of growing interest in business sustainability research. Markets in the energy industry, which are notoriously harder to monitor, are often presented with scenarios in which the strength of various market parties varies, making harmonization a significant problem. This article’s aim is to find the feasibility of measuring the HHI in the implementation of business strategies in order to avoid market distortions in the energy industry. The uniqueness of this article is that it outlines the capabilities of the fuzzy VIKOR approach for assessing the HHI in order to avoid a distorted market by examining the most important economic parameters in the energy market. This paper’s contribution is compiling the HHI evaluation system in the energy sector, with the goal of identifying the market conditions of corporate entity and assisting in the attainment of... [more]

In an open electricity market, increased accuracy and real-time availability of electricity price forecasts can help market parties participate effectively in market operations and management. As the penetration of clean energy increases, it brings new challenges to electricity price forecasting. An electricity price forecasting model is constructed in this paper for markets containing a high proportion of wind and solar power, where the scenario with a high coefficient of variation (COV) caused by the high frequency of low electricity prices is particularly concerned. The deep extreme learning machine optimized by the sparrow search algorithm (SSA-DELM) is proposed to make predictions on the model. The results show that wind−load ratio and solar−load ratio are the key input variables for forecasting in power markets with high proportions of wind and solar energy. The SSA-DELM possesses better electricity price forecasting performance in the scenario with a high COV and is more suitabl... [more]

The present research article focuses on an analytically based method for the optimal allocation and sizing of a renewable energy source (RES) capable of injecting both active and reactive powers in the distribution network. The placement of distributed generation (DG) in the distribution network reduces the magnitude of branch current in between the reference bus and the bus where DG is to be installed. Due to this, system power loss decreases significantly. The proposed method considers different levels of load in addition to peak load demand. The goal of the developed method is to minimize system losses by optimal DG allocations. In the proposed method, the optimum size of the DG is obtained on the basis of maximum loss saving criterion. For the execution of proposed method, only a base case load flow solution is required. The developed method has been tested on IEEE 69-bus and 33-bus radial distribution networks. On the basis of obtained results, it has been realized that the develo... [more]

Distributed generation systems (DGSs) are one of the key developments enabling the energy transition. DGSs provide users with increased control over their energy use and generation, but entail greater complexity in their design and operation. Traditionally, optimization models have been used to overcome this complexity, and currently, research is focusing on integrating uncertainties on them. This review attempts to analyze, classify and discuss 170 articles dealing with optimization of DGSs under uncertainty. A survey has been performed to identify the selected manuscripts and the strengths and weaknesses of previous reviews. As a result, an innovative classification has been designed and the distinct elements of optimization models in DGSs have been highlighted: microgrid architecture, sources of uncertainty, uncertainty addressing methods, problem types and formulations, objective functions, optimization algorithms and additional features. Each part is detailed thoroughly to provide... [more]

The electric machines are the elements most used at an industry level, and they represent the major power consumption of the productive processes. Particularly speaking, among all electric machines, the motors and their drives play a key role since they literally allow the motion interchange in the industrial processes; it could be said that they are the medullar column for moving the rest of the mechanical parts. Hence, their proper operation must be guaranteed in order to raise, as much as possible, their efficiency, and, as consequence, bring out the economic benefits. This review presents a general overview of the reported works that address the efficiency topic in motors and drives and in the power quality of the electric grid. This study speaks about the relationship existing between the motors and drives that induces electric disturbances into the grid, affecting its power quality, and also how these power disturbances present in the electrical network adversely affect, in turn,... [more]

In order to manage electric vehicles (EVs) connected to charging grids, this paper presents an orderly charging approach based on the EVs’ optimal time-of-use pricing (OTOUP) demand response. Firstly, the Monte Carlo approach is employed to anticipate charging power by developing a probability distribution model of the charging behavior of EVs. Secondly, a scientific classification of the load period is performed using the fuzzy clustering approach. Then, a matrix of demand price elasticity is developed to measure the link between EV charging demand and charging price. Finally, the charging scheme is optimized by an adaptive genetic algorithm from the distribution network and EV user viewpoints. This paper describes how to implement the method presented in this paper in an IEEE-33-bus distribution network. The simulation results reveal that, when compared to fixed price and common time-of-use pricing (CTOUP), the OTOUP charging strategy bears a stronger impact on reducing peak−valley d... [more]

Climate change already affects all inhabited regions of the world, with human influence contributing to many observed changes in climate extremes and to mitigate this trend, important decisions have been taken by different world organizations and countries to achieve global net-zero emissions. At the European Union level (EU27 countries), two of the main pillars for achieving carbon neutrality are: (1) The “Energy Efficiency First principle” in the formulation of energy policy and in taking relevant investment decisions and (2) the electrification of the energy sector, supported by generating electricity through endogenous renewable energy sources. In this context, a comprehensive review was carried out on what has been developed by the scientific community and main international energy organizations on the electrification of the energy sector. Additionally, with the purpose of better understanding the state of the art of a country regarding the decarbonization process, the Portuguese... [more]

The research presented in this paper focuses on the impact of fast charging stations (FCSs) on voltage quality. When the operation of FCSs causes a voltage fluctuation and light flicker, the FCSs may be disconnected, as per the utility general standard practice, which results in financial loss represented by FCS downtime. FCS downtime can be avoided by mitigating voltage fluctuation and light flicker. Flicker mitigation devices that are available in the market are characterized by their high total annual equivalent costs. As an alternative, a novel smart charging method is proposed in this study in order to mitigate both voltage fluctuation and light flicker, whereby customers can select one of three charging services available in fast chargers: premium, regular, or economic charging power. The charging power is selected according to customer priority in relation to time and cost, which offers more flexibility than those currently available in the literature. For instance, the premium... [more]

Recent years have seen an increase in the role of social media in the communication of energy sector companies (ESCs) with consumers. Currently, consumers look for information, create it themselves, and share it with other Internet users. eWOM communication means that energy companies, firstly, must be present in social media so that consumers can get to know them better, and secondly, they must consciously shape their image according to the expectations of their customers. One-way communication, such as customer satisfaction measurements, is no longer enough to know their preferences. Market trends indicate that for current buyers—both consumer and non-consumer products—the image of a “green product” or a “green company” is expected. Only a few companies report that they are harmful for environment. All companies report that they are generally community friendly. The consumer would like to know, in particular, about the harmfulness to the environment. Thus, there is a knowledge gap th... [more]

Operation of distribution networks involves a series of criteria that should be met, aiming for the correct and optimal behavior of such systems. Some of the major drawbacks found when studying these networks is the real losses related to them. To overcome this problem, distribution network reconfiguration (DNR) is an efficient tool due to the low costs involved in its implementation. The majority of studies regarding this subject treat the problem by considering networks only as three-phase balanced, modeled as single-phase grids with fixed power demand, which is far from representing the characteristics of real networks (e.g., unbalanced loads, variable power and unbalance indexes). Due to the combinatorial nature of the problem, metaheuristic techniques are powerful tools for the inclusion of such characteristics. In this sense, this paper proposes a study of DNR considering balanced and unbalanced systems with variable power demand. An analysis of the direct influence of voltage un... [more]

The motive for the functioning of enterprises in the market economy is the maximization of benefits by achieving positive financial results with the minimum possible involvement of capital. The positive results achieved are perceived very positively by the stakeholders. To achieve this, it is necessary to carry out reorganization processes (mergers and acquisitions) within capital groups, which are perceived as necessary (positive) measures. These phenomena have been observed in the energy sector for many years, and the years 2010−2021 were adopted as the research period. The aim of this article is to attempt to answer the question of whether the multi-energy concern is the result of activities carried out in light of the 2030 Agenda. The effect of merging the entities is capital concentration. This fact has been verified by reviewing changes in the structures of capital groups in the energy sector against the background of the largest mergers and acquisitions in Poland in terms of val... [more]

Monitoring of railroad wagons is important for logistical processes, but above all for safety. One of the key parameters to be monitored is the temperature of the axle box and the bearings in the bogie. The problem with monitoring these parameters is the harsh environment and lack of power supply. In our research, we present a power supply system for a WSN node monitoring the bogie parameters. Knowing the operating conditions, we built a power supply system using a piezoelectric energy harvester. The harvester consists of three piezoelectric elements placed on a double arm pendulum beam. The circuit was modeled in the Comsol Multiphysics environment and then built and tested in laboratory conditions. After confirming energy efficiency, the system was tested on a freight car bogie during an 8 h trip. At typical car vibration frequencies (4−10 Hz), the system is able to generate 73 uW. Combined with an energy buffer of 1000 mAh (3.7 V), it can power a WSN node (based on the nRF5340 chip)... [more]