Spectrum demand has increased with the rapid growth of wireless devices and wireless service usage. The rapid development of 5G smart cities and the industrial Internet of Things makes the problem of spectrum resource shortage and increased energy consumption even more severe. To address the issues of high energy consumption for spectrum sensing and low user access rate in the cognitive radio networks (CRN) model powered entirely by energy harvesting, we propose a novel energy harvesting (EH)-distributed cooperative spectrum sensing (DCSS) architecture that allows SUs to acquire from the surrounding environment and radio frequency (RF) signals energy, and an improved distributed cooperative spectrum sensing scheme based on energy-correlation is proposed. First, we formulate an optimization problem to select a leader for each channel; then formulate another optimization problem to select the corresponding cooperative secondary users (SUs). Each channel has a fixed SUs cluster in each ti... [more]

Circuit theory and nonlinear dynamics are instrumental to design efficient energy harvesters for ambient mechanical vibrations. In this work, we show that an impedance matching networks can be designed that maximizes the harvested power, and improves the power efficiency. The proposed matching network achieves impedance matching at a single frequency, that can be chosen at will by the designer, and does not need to coincide with the resonant frequency of the harvester. Moreover, the matching network also increases the harvested power over a wide frequency bandwidth. According to our numerical simulations, the matching network increases the maximum harvested power by a factor greater than 3, and the power harvested over the whole frequency spectrum by a factor of 6. The frequency bandwidth can be further extended considering nonlinear energy harvesters. Even using the matching network designed for the linear case, performance is significantly nonetheless improved for the nonlinear harve... [more]

Energy storage systems is expected to be utilized to cover the increased electrification of energy demands and to alleviate the electrical energy production from intermittent energy sources such as solar and wind. Aggregated and distributed battery energy storage systems may improve electricity grids operability and security by providing smart energy management options and efficient resources allocation. In this paper, battery storage at the secondary distribution level is explored. The investigation is based on the end-user energy demand behavior. As such, the electrical energy consumption patterns are measured and analyzed in a residential area. Measurements were collected and analyzed in order to record the customers’ behaviors aiming to reveal their differences and similarities. Following this, aggregated and distributed battery energy storage systems are computed based on the features of the measured electrical power consumption patterns aiming to estimate the factors that could p... [more]

Deployment of renewable energy sources in Malta is limited by grid integration constraints. Photovoltaic (PV) systems pose a significant risk to grid stability due to their inherent intermittency and result in overvoltages at the medium-voltage and low-voltage networks. Investments in utility-scale battery energy storage systems (BESS) will facilitate further deployment of renewables and will help to achieve energy security. This study proposed a novel sizing strategy for utility-scale battery energy storage systems (BESS) based only on technical considerations to find the minimum required storage capacity based on historical electricity demand and PV generation. The modeling and simulation were constrained to a section of the Gozitan 11 kV electrical distribution network and the results showed that the utility-scale storage can reduce the impact of PV systems on the grid infrastructure by avoiding reverse power flows and improve the local energy security by reducing the peak electrici... [more]

Identifying power quality (PQ) disturbances is an important prerequisite for developing mitigation measures to improve PQ. However, the coupling of multiple PQ disturbances in the noise condition makes it difficult to achieve effective feature extraction and classification. This article proposes a novel method to identify multiple PQ disturbances by integrating improved TQWT with XGBoost algorithm. The improved TQWT is proposed to automatically select the proper tuning parameters by screening the spectral information of PQ signals. Then, the improved TQWT is used to decompose PQ disturbances into sub-bands for further feature extraction. Optimum feature selection and classification are implemented in XGBoost. Classification accuracies of 26 categories of synthetic PQ disturbances under different noisy levels are tested and compared with existing methods. Results indicate that the proposed method is efficient and noise-resistant, and the classification accuracy can reach 97.63% under 20... [more]

In recent years, efficient modeling and forecasting of electricity prices became highly important for all the market participants for developing bidding strategies and making investment decisions. However, as electricity prices exhibit specific features, such as periods of high volatility, seasonal patterns, calendar effects, nonlinearity, etc., their accurate forecasting is challenging. This study proposes a functional forecasting method for the accurate forecasting of electricity prices. A functional autoregressive model of order P is suggested for short-term price forecasting in the electricity markets. The applicability of the model is improved with the help of functional final prediction error (FFPE), through which the model dimensionality and lag structure were selected automatically. An application of the suggested algorithm was evaluated on the Italian electricity market (IPEX). The out-of-sample forecasted results indicate that the proposed method performs relatively better th... [more]

Energy production and supply are important challenges for civilisation. Renewable energy sources present an increased share of the energy supply. Under these circumstances, small-scale grids operating in small areas as fully functioning energy systems are becoming an interesting solution. One crucial element to the success of micro-grid structures is the accurate forecasting of energy consumption by large customers, such as factories. This study aimed to develop a universal forecasting tool for energy consumption by end-use consumers. The tool estimates energy use based on real energy-consumption data obtained from a factory or a production machine. This model allows the end-users to be equipped with an energy demand prediction, enabling them to participate more effectively in the smart grid energy market. A single, long short-term memory (LSTM)-layer-based artificial neural network model for short-term energy demand prediction was developed. The model was based on a manufacturing plan... [more]

The bipolar DC microgrid topology is characterized by three voltage levels and is able to transfer power more efficiently than a conventional DC microgrid. This paper proposes an advanced control strategy aiming to ensure the voltage balancing between the upper and lower terminals of a bipolar DC microgrid regardless of the distribution of loads. The proposed controller is based on the backstepping method, which is well known for its the robustness and the global asymptotic stability that can be guaranteed for the system. A particle swarm optimization algorithm has also been adopted for an optimal design of the proposed controller parameters. Simulation results in a Matlab/Simulink environment has been presented to verify the effectiveness and reliability of the proposed voltage-balancing controller.

Using renewable energy sources instead of fossil fuels is one of the best solutions to overcome greenhouse gas (GHG) emissions. However, in designing clean power generation microgrids, the economic aspects of using renewable energy technologies should be considered. Furthermore, due to the unpredictable nature of renewable energy sources, the reliability of renewable energy microgrids should also be evaluated. Optimized hybrid microgrids based on wind and solar energy can provide cost-effective power generation systems with high reliability. These microgrids can meet the power demands of the consuming units, especially in remote areas. Various techniques have been used to optimize the size of power generation systems based on renewable energy to improve efficiency, maintain reliability, improve the power grid’s resilience, and reduce system costs. Each of these techniques has shown its advantages and disadvantages in optimizing the size of hybrid renewable energy systems. To increase t... [more]

The European Union’s Green Deal emphasises the importance of improving the efficiency of the energy sector in its countries, which is why the issues involved are relevant in both scientific and practical terms. The article sets out the hypothesis that conveying the state of the economic efficiency of energy development by grades does not reflect the real situation. Instead of ranks, it is proposed to form homogeneous groups of some countries based on non-linear data normalisation instead of today’s universally used linearisation. Grouping the euro area countries in the European Union on the basis of the value of the cost-effectiveness indicator for the energy development of their industrial sector confirmed the appropriateness of the proposed method-ology. In this way, three groups of countries were formed according to the level of cost-effectiveness achieved. The proposed methodology for grouping countries is universal and can be used for international comparisons of any kind.

A new paradigm has appeared in the electricity sector with the rapid development of new renewable energy sources, storage systems, information and communication technologies, and ways of integrating distributed energy sources [...]

The number of microgrids within a smart distribution grid can be raised in the future. Microgrid-based distribution network reconfiguration is analyzed in this research by taking demand response programs and power-sharing into account to optimize costs and reduce power losses. The suggested method determined the ideal distribution network configuration to fulfil the best scheduling goals. The ideal way of interconnecting switches between microgrids and the main grid was also identified. For each hour of operation, the ideal topology of microgrid-based distribution networks was determined using optimal power flow. The results were produced with and without the use of a demand response program and power-sharing in each microgrid. Different load profiles, such as residential, industrial, commercial, and academic, were taken into account and modified using appropriate demand response programs and power-sharing using the Artificial Bee Colony algorithm. Various scenarios were explored indep... [more]

To convert as much vibration energy as possible into electrical energy, the design of a high-performance piezoelectric vibration energy harvester (PVEH) has been studied widely in recent years. To overcome the low energy utilization of a traditional piezoelectric cantilever by inhomogeneous strain, a uniform stress distribution of bimorph by an ARC mechanical stopper structure has been designed for maximum piezoelectric vibration energy harvesting. Deflection equations and their simulation at the first-order modal of two classic bimorph cantilever beam models, with transverse tip force and with equal curvature, are derived based on the Euler−Bernoulli beam assumption. Piezoelectric energy from a beam model with equal curvature is four times that of a cantilever beam model with transverse tip force at the theoretical level. The nonlinear frequency response performance of bimorphs by an ARC mechanical stopper and point stopper model could be observed by the numerical simulations of the l... [more]

The high penetration of distributed renewable energy and the popularization of electric vehicles has led to voltage quality problems in distribution networks. Voltage problems, such as over-voltage, under-voltage, and voltage fluctuations, are increasingly becoming severe. Voltage regulation services play an essential role in improving the power supply quality of the distribution network. The development of information and communication technologies has promoted the upgrading of remote control technology. Air conditioners (ACs) can be easily remote controlled to change the power consumption for voltage regulation services. This study proposes a voltage control strategy by optimizing the limited regulation capacity of ACs. Firstly, a detailed thermal model is developed to analyze the room temperature and the regulation capacity of the ACs. Secondly, a successive voltage regulation algorithm is proposed to solve the voltage problems of the limited regulation capacity of ACs. In addition,... [more]

This article reports the conception and design of a mission critical microgrid to serve a critical infrastructure application, namely, the Alcântara Space Launch Center, a government military facility in Brazil. The assumptions, general characteristics, requirements and particularities arising from the application are established and discussed in detail. High resilience and energy security are required in critical periods of operation, demanding a power supply infrastructure composed of redundant and dispachable sources capable of supporting n−1 generation contingencies. Whereas, in the remaining time, economic and environmental aspects take place as main requests. Operation scenarios, on both grid-connected (on-grid) and isolated (off-grid) modes, are formulated as optimization problems and simulations have been performed to analyze these scenarios, which are reported and analyzed here. The off-grid operation, which is clearly more complex, is preferentially addressed, especially in s... [more]

Hydrogen technologies have been rapidly developing in the past few decades, pushed by governments’ road maps for sustainability and supported by a widespread need to decarbonize the global energy sector. Recent scientific progress has led to better performances and higher efficiencies of hydrogen-related technologies, so much so that their future economic viability is now rarely called into question. This article intends to study the integration of hydrogen systems in both gas and electric distribution networks. A preliminary analysis of hydrogen’s physical storage methods is given, considering both the advantages and disadvantages of each one. After examining the preeminent ways of physically storing hydrogen, this paper then contemplates two primary means of using it: integrating it in Power-to-Gas networks and utilizing it in Power-to-Power smart grids. In the former, the primary objective is the total replacement of natural gas with hydrogen through progressive blending procedures,... [more]

In IoT applications, energy supply, especially wireless power transfer (WPT), has attracted the most attention in the relevant literature. In this paper, we present a new approach to laser irradiance solar cell panels and predicting energy transfer efficiency. From the previous experimental datasets, it has been discovered that in the laser charging (LC) process, temperature has a great impact on the efficiency, which is highly correlated with the laser intensity. Then, based on artificial neural network (ANN), we set the above temperature and laser intensity as inputs, and the efficiency as output through back propagation (BP) algorithm, and use neural network and BP to train and modify the network parameters to approach the real efficiency value. We also propose the genetic algorithm (GA) to optimize the learning rate of the BP, which achieved slightly superior results. The results of the experiment indicate that the prediction method reaches a high accuracy of about 99.4%. The resea... [more]

Network reconfiguration is an effective way to avoid severe, large-scale power outages and to improve the resilience of active distribution networks (ADNs). Furthermore, the rapid development of distributed energy resources (DERs) provides new perspectives for network reconfiguration. In this paper, the effect of network reconfiguration and DER collaboration on ADN’s resilient restoration are studied. The applications of DERs are fully explored. In order to achieve a better resilient performance, a detailed multiperiod model considering both reconfiguration and multiple DERs is established. Some linearization techniques are used to simplify the proposed model. Then, we build a rolling horizon optimization framework to solve the model. The framework eliminates the adverse effect of prediction errors and speeds up the calculation. By introducing predictions into strategy determination, the framework achieves a better restoration effect than the traditional greedy method. The proposed fra... [more]

The UK has one of the least energy-efficient housing stocks in Europe. By 2030, the emissions from UK homes need to fall by at least 24% from 1990 levels to meet the UK’s ambitious goal, which is reaching net-zero emissions. The originality of this paper is to apply the building typology approach to predict energy savings of the UK housing stock under a step-by-step energy retrofit scenario, targeting the Passive House Standard for refurbishments of existing buildings, namely the EnerPHit “Quality-Approved Energy Retrofit with Passive House Components.” The typologies consist of twenty reference buildings, representative of five construction ages and four building sizes. The energy balance of the UK residential buildings was created and validated against statistical data. A building stock retrofit plan specifying the order in which to apply energy efficiency measures was elaborated, and energy savings were calculated. The predicted total energy demand for the UK residential building st... [more]

The low-voltage circuit breaker (LVCB) is commonly utilized in the distribution network. An accurate evaluation of its electrical life is related to the safety and reliability of electric energy output. The traditional arc erosion model only considers the effect of current on contact wear while ignoring the impact of operation conditions (supply voltage and power factor) on electrical life. As a result of the arc voltage, the original circuit topology changes, resulting in an early current zero. At 220−660 V AC supply voltages, arc voltage causes the distortion of the breaking current waveform, and the contact erosion amount (CEA) is smaller than that in the ideal case. This work investigates the effect of arc voltage on breaking current, develops an arc erosion model that includes arc voltage, and compares the CEA curves for various supply voltages and power factors. The electrical life of the LVCB is then simulated using the Monte Carlo approach to determine the distribution of elect... [more]

In the last years, the overall system inertia is decreasing due to the growing amount of energy resources connected to the grid by means of power inverters. As a consequence, reduced levels of inertia can affect the power system stability since slight variations of power generation or load may cause wider frequency deviations and higher rate of change of frequency (RoCoF) values. To mitigate this trouble, end-user distributed energy resources (DERs) interfaced through grid-following inverters, if opportunely controlled, can provide additional inertia. This paper investigated the possibility of improving the control law implemented by a low-cost controller on remotely controllable legacy DERs to provide synthetic inertia (SI) contributions. With this aim, power hardware-in-the-loop simulations were carried out to test the capability of the proposed controller to autonomously measure frequency and RoCoF and provide SI actions by controlling an actual battery energy storage system.

The water distribution system has deployed several low-power IoT devices on an uneven surface where battery power is a major concern. Therefore, this paper focuses on using a UAV-enabled wireless powered communication network capable of directing energy to a target location and using it for communication, thereby reducing battery issues. In this paper, a static optimization was applied to find the initial height values using 3D clustering and beamforming method and dynamic optimization using extremum seeking method was applied to find the optimized height. The optimized height values were calculated and Travelling Salesman Problem (TSP) was applied to create the trajectory of the UAV. The overall energy consumption of the UAV was minimized by integrating dynamic optimization and dome packing method, which can find an optimal position and trajectory where the UAV will be hovering to direct energy and collect data. Moreover, we also minimized the total flight time of the UAV.

In this empirical study, multifactor stochastic volatility models for the financial Nordic/Baltic power markets are developed, implemented, and analyzed. Stochastic volatility projections are the primary aim, followed by volatility forecasts and market repercussions. The research provides a functional variant of the conditional distribution (f(x|y)) based on conditional moments and a long-simulated state vector realization (MCMC-GMM) that is evaluated on observed data (a non-linear Kalman Filter) and applicable for step-forward volatility forecasts. For front year and quarter financial electricity contracts, the SV model creates two mean-reverting factors: one persistent and slowly moving component and one choppy, rapidly moving component. According to these factors, static volatility predictions with optimum and generous lags have a Theil covariance percentage of well over 97 percent for the front year contracts and 86 percent for the front quarter contracts. The volatility visibility... [more]

Since no solutions have been proposed in Colombia that seek to reduce the consumption of electricity at the residential level, this paper describes the design and implementation of a simple prototype of a low-cost home energy management system (HEMS). The objective of this platform is to monitor the energy consumption of typical household devices so that users can access the consumption of each device separately and then establish the strategy that allows them to reduce energy consumption at home. In order to demonstrate that our system is viable, the system has been evaluated by measuring weekly energy consumption with the on-line and off-line HEMS using a test bench with typical household devices in a Sincelejo typical household. The evaluation has shown that with the installation of this HEMS, consumption is reduced by 27%. This shows that it is possible to achieve a good reduction percentage with a low-cost system.

In this manuscript, we propose a single-phase UPC (universal power compensator) system to extensively tackle power quality issues (voltage and current) with an equal VAR (volt-ampere reactive) sharing approach between the series and shunt APF (active power filter) of a UPC system. The equal VAR sharing feature facilitates the series and shunt APF inverters to be of an equal rating. An SRF (synchronous reference frame)-based direct PA (power angle) calculation technique is implemented to realize equal VAR sharing between the APFs of the UPC. This PA estimation utilizes d and q axis current parameters derived for the reference signal generation of the shunt APF. An SRF-based method is highly useful for power estimations in distorted supply voltage conditions compared with other conventional methods, i.e., the PQ method. It comprises a reduced complexity and estimations with an easiness to retain two APF inverters of equal rating. A rigorous simulation analysis is performed with MATLAB/SI... [more]