With exposure to real-time market pricing structures, consumers would be incentivized to invest in electrical energy storage systems and smart predictive automation of their home energy systems. Smart home automation through optimizing HVAC (heating, ventilation, and air conditioning) temperature set points, along with distributed energy storage, could be utilized in the process of optimizing the operation of the electric grid. Using electricity prices as decision variables to leverage electrical energy storage and flexible loads can be a valuable tool to optimize the performance of the power grid and reduce electricity costs both on the supply and demand sides. Energy demand prediction is important for proper allocation and utilization of the available resources. Manipulating energy prices to leverage storage and flexible loads through these demand prediction models is a novel idea that needs to be studied. In this paper, different models for proactive prediction of the energy demand... [more]

To ensure the stability of park power supply systems and to promote the consumption of wind/photovoltaic generation, this paper proposes a dispatching optimization model for the park power supply system with power-to-gas (P2G) and peak regulation via gas-fired generators. Firstly, the structure of a park power system with P2G was built. Secondly, a dispatching optimization model for the park power supply system was constructed with a peak regulation compensation mechanism. Finally, the effectiveness of the model was verified by a case study. The case results show that with the integration of P2G and the marketized peak regulation compensation mechanism, preferential power energy storage followed by gas storage had the best effect on the park power supply system, which minimized the clean energy curtailment to 11.18% and the total cost by approximately $120.190 and maximized the net profit by approximately $152.005.

The United Arab Emirates (UAE) relies on groundwater as well as desalinated water which are very expensive and energy-concentrated. Despite the lack of water resources, only 54% of wastewater was recycled in the UAE in 2016. In this study, a Sustainable Farming Compartment (SFC) with an evaporative cooling system is investigated as an alternative to reusing wastewater and the optimal design is identified experimentally and numerically. First, the applicability of the SFC was examined to reduce the ambient temperature in the system. A prototype SFC was tested in the environmentally constrained laboratory and field site considering an extreme climate condition (with high temperature and humidity) in Abu Dhabi to evaluate the temperature drop and humidity change of the SFC. The experimental results showed that the temperature of the SFC significantly decreases by 7−15 °C when the initial relative humidity is 50%. For validation, an energy modeling using dynamic numerical simulations was p... [more]

Due to its spatio-temporal variability, the mismatch between the weather and demand patterns challenges the design of highly renewable energy systems. A principal component analysis is applied to a simplified networked European electricity system with a high share of wind and solar power generation. It reveals a small number of important mismatch patterns, which explain most of the system’s required backup and transmission infrastructure. Whereas the first principal component is already able to reproduce most of the temporal mismatch variability for a solar dominated system, a few more principal components are needed for a wind dominated system. Due to its monopole structure the first principal component causes most of the system’s backup infrastructure. The next few principal components have a dipole structure and dominate the transmission infrastructure of the renewable electricity network.

In a wireless sensor network (WSN), many applications have limited energy resources for data transmission. In order to accomplish a better green communication for WSN, a hybrid energy scheme can supply a more reliable energy source. In this article, hybrid energy utilization—which consists of constant energy source and solar harvested energy—is considered for WSN. To minimize constant energy usage from the hybrid source, a Markov decision process (MDP) is designed to find the optimal transmission policy. With a finite packet buffer and a finite battery size, an MDP model is presented to define the states, actions, state transition probabilities, and the cost function including the cost values for all actions. A weighted sum of constant energy source consumption and a packet dropping probability (PDP) are adopted as the cost value, enabling us to find the optimal solution for balancing the minimization of the constant energy source utilization and the PDP using a value iteration algorit... [more]

Electricity demand shifting and reduction still raise a huge interest for end-users at the household level, especially because of the ongoing design of a dynamic pricing approach. In particular, end-users must act as the starting point for decreasing their consumption during peak hours to prevent the need to extend the grid and thus save considerable costs. This article points out the relevance of a fuzzy logic algorithm to efficiently predict short term load consumption (STLC). This approach is the cornerstone of a new home energy management (HEM) algorithm which is able to optimize the cost of electricity consumption, while smoothing the peak demand. The fuzzy logic modeling involves a strong reliance on a complete database of real consumption data from many instrumented show houses. The proposed HEM algorithm enables any end-user to manage his electricity consumption with a high degree of flexibility and transparency, and “reshape” the load profile. For example, this can be mainly a... [more]

In this paper, a new virtual framework for load aggregation in the context of the liberalized energy market is proposed. Since aggregation is managed automatically through a dedicated platform, the purchase of energy can be carried out without intermediation as it happens in peer-to-peer energy transaction models. Differently from what was done before, in this new framework, individual customers can join a load aggregation program through the proposed aggregation platform. Through the platform, their features are evaluated and they are clustered according to their reliability and to the width of range of regulation allowed. The simulations show the deployment of an effective clustering and the possibility to meet the target power demand at a given hour according to each customer’s availability.

Climate change and fossil fuel depletion foster interest in improving energy efficiency in buildings. There are different methods to achieve improved efficiency; one of them is the use of additives, such as phase change materials (PCMs). To prove this method’s effectiveness, a building’s behaviour should be monitored and analysed. This paper describes an acquisition system developed for monitoring buildings based on Supervisory Control and Data Acquisition (SCADA) and with a 1-wire bus network as the communication system. The system is empirically tested to prove that it works properly. With this purpose, two experimental cubicles are made of self-compacting concrete panels, one of which has a PCM as an additive to improve its energy storage properties. Both cubicles have the same dimensions and orientation, and they are separated by six feet to avoid shadows. The behaviour of the PCM was observed with the acquisition system, achieving results that illustrate the differences between th... [more]

The microgrid containing a large amount of high frequency power switches and nonlinear components has put forward high requirements for power system real-time simulation technology. Multivalued coefficient prestorage can reduce the calculation steps in real-time simulation. In order to reduce the storage pressure of the multivalued coefficients, the whole network is divided into multiple subnetworks that can be simulated in parallel, and only the parameters for computing input variables and internal variables are prestored. The multiport hybrid equivalent is performed to reduce the number of simultaneous network equations. The input variables are tied to state variables of the circuit so that the iterative calculation is limited to the local network. The devised methodology is validated through simulation of a low-voltage microgrid on a field programmable gate array (FPGA)-based real-time digital simulation (FRTDS) platform at a 5 μs time step. Comparison with a power systems computer... [more]

This study presents a model for district-level electricity demand forecasting using a set of Artificial Neural Networks (ANNs) (parallel ANNs) based on current energy loads and social parameters such as occupancy. A comprehensive sensitivity analysis is conducted to select the inputs of the ANN by considering external weather conditions, occupancy type, main income providers’ employment status and related variables for the fuel poverty index. Moreover, a detailed parameter tuning is conducted using various configurations for each individual ANN. The study also demonstrates the strength of the parallel ANN models in different seasons of the years. In the proposed district level energy forecasting model, the training and testing stages of parallel ANNs utilise dataset of a group of six buildings. The aim of each individual ANN is to predict electricity consumption and the aggregated demand in sub-hourly time-steps. The inputs of each ANN are determined using Principal Component Analysis... [more]

The paper presents the concept of a hybrid power system with additional energy storage to support electric vehicles (EVs) charging stations. The aim is to verify the possibilities of mutual cooperation of individual elements of the system from the point of view of energy balances and to show possibilities of utilization of accumulation for these purposes using mathematical modeling. The description of the technical solution of the concept is described by a mathematical model in the Matlab Simulink programming environment. Individual elements of the assembled model are described in detail, together with the algorithm of the control logic of charging the supporting storage system. The resulting model was validated via an actual small-scale hybrid system (HS). Within the outputs of the mathematical model, two simulation scenarios are presented, with the aid of which the benefits of the concept presented were verified.

In the last few years, several investigations have been carried out in the field of optimal sizing of energy storage systems (ESSs) at both the transmission and distribution levels. Nevertheless, most of these works make important assumptions about key factors affecting ESS profitability such as efficiency and life cycles and especially about the specific costs of the ESS, without considering the uncertainty involved. In this context, this work aims to answer the question: what should be the costs of different ESS technologies in order to make a profit when considering peak shaving applications? The paper presents a comprehensive sensitivity analysis of the interaction between the profitability of an ESS project and some key parameters influencing the project performance. The proposed approach determines the break-even points for different ESSs considering a wide range of life cycles, efficiencies, energy prices, and power prices. To do this, an optimization algorithm for the sizing of... [more]

In this work, a practical methodology is proposed to analyze, before undertaking a large investment, an outdoor lighting installation renewal with light-emitting diode (LED) luminaires. The main problems found in many of the luminaires tested are associated with inrush peak currents in cold start (which may cause ignition problems with random shutdowns), the harmonic distortions caused by their AC/DC associated electronic nature driver, and their working and efficiency dependency on the ambient temperature. All these issues have been tested in the context of a large metal halide (MH) to LED luminaires lighting point renewal where six commercial LED projectors have been analyzed with the above considerations. This research has isolated a single-phase circuit powered with constant stabilized 230 VAC voltage source in a real public lighting installation. All of them have been sequentially installed and their main electrical and power-quality parameters measured and recorded. The results i... [more]

Buildings consume approximately ¾ of the total electricity generated in the United States, contributing significantly to fossil fuel emissions. Sustainable and renewable energy production can reduce fossil fuel use, but necessitates storage for energy reliability in order to compensate for the intermittency of renewable energy generation. Energy storage is critical for success in developing a sustainable energy grid because it facilitates higher renewable energy penetration by mitigating the gap between energy generation and demand. This review analyzes recent case studies—numerical and field experiments—seen by borehole thermal energy storage (BTES) in space heating and domestic hot water capacities, coupled with solar thermal energy. System design, model development, and working principle(s) are the primary focus of this analysis. A synopsis of the current efforts to effectively model BTES is presented as well. The literature review reveals that: (1) energy storage is most effective... [more]

An ultra-low voltage customized DC-DC booster circuit was developed using a LTC3108 converter, and used continuously on a flat-plate microbial fuel cell (FPM) system. The boost converter successfully stepped up the microbial fuel cell (MFC) voltage from ~0.5 V to 3.3 and 5.0 V of outputs. The designed circuit and system displayed the dynamic variations of the source FPM as well as the output voltage through the designed three connection points within the booster circuit. The source MFC voltage was interrelated with the booster circuit and its performance, and it adapted to the set points of the booster dynamically. The maximum output power density of the MFC with the DC-DC booster circuit was 8.16 W/m³ compared to the maximum source FPM input power of 14.27 W/m³ at 100 Ω, showing a conversion efficiency of 26⁻57%, but with a 10-fold higher output than that of the source voltage. The combined LTC3108 with FPM supplied power for electronic devices using synthetic and real domestic wastew... [more]

Smart meters for measuring electricity consumption are fast becoming prevalent in households. The meters measure consumption on a very fine scale, usually on a 15 min basis, and the data give unprecedented granularity of consumption patterns at household level. A multitude of papers have emerged utilizing smart meter data for deepening our knowledge of consumption patterns. This paper applies a modification of Okoli’s method for conducting structured literature reviews to generate an overview of research in electricity customer classification using smart meter data. The process assessed 2099 papers before identifying 34 significant papers, and highlights three key points: prominent methods, datasets and application. Three important findings are outlined. First, only a few papers contemplate future applications of the classification, rendering papers relevant only in a classification setting. Second; the encountered classification methods do not consider correlation or time series analy... [more]

China building energy consumption (BEC) has been gradually derived and also sparked attention. However, something worth discussing is estimating the BEC based on the definition of life cycle or building operation. In addition, there exists discrepancy in the previous studies and the real status of BEC has not been known well. In order to settle the disputes over the calculation of BEC, this paper establishes an appropriate accounting method of building energy to present the BEC situation in China and lays the foundation for policymakers to develop appropriate energy saving policies. Meanwhile, this study attempts to clarify the BEC to help policymakers assess the effect of environmental policies. Using the method in this document, we find that the energy consumption of buildings just accounts for 15%⁻16% of the final total energy consumption in China; by contrast, the previous studies usually have double accounting through a top-down approach if central heat supply of buildings was tak... [more]

With the expansion of smart meters, like the Advanced Metering Infrastructure (AMI), and the Internet of Things (IoT), each smart city is equipped with various kinds of electronic devices. Therefore, equipment and technologies enable us to be smarter and make various aspects of smart cities more accessible and applicable. The goal of the current paper is to provide an inclusive review on the concept of the smart city besides their different applications, benefits, and advantages. In addition, most of the possible IoT technologies are introduced, and their capabilities to merge into and apply to the different parts of smart cities are discussed. The potential application of smart cities with respect to technology development in the future provides another valuable discussion in this paper. Meanwhile, some practical experiences all across the world and the key barriers to its implementation are thoroughly expressed.

Direct current (DC) distribution systems and DC microgrids are becoming a reliable and efficient alternative energy system, compatible with the DC nature of most of the distributed energy resources (DERs), storage devices and loads. The challenging problem of redesigning an autonomous DC-grid system in view of using energy storage devices to balance the power produced and absorbed, by applying simple decentralized controllers on the electronic power interfaces, is investigated in this paper. To this end, a complete nonlinear DC-grid model has been deployed that includes different DC-DERs, two controlled parallel battery branches, and different varying DC loads. Since many loads in modern distribution systems are connected through power converters, both constant power loads and simple resistive loads are considered in parallel. Within this system, suitable cascaded controllers on the DC/DC power converter interfaces to the battery branches are proposed, in a manner that ensures stabilit... [more]

Energy management strategies (EMSs) are critical for the improvement of fuel economy of plug-in hybrid electric vehicles (PHEVs). However, conventional EMSs hardly consider the influence of uphill terrain on the fuel economy and battery life, leaving vehicles with insufficient battery power for continuous uphill terrains. Hence, in this study, an optimal control strategy for a PHEV based on the road grade information is proposed. The target state of charge (SOC) is estimated based on the road grade information as well as the predicted driving cycle on uphill road obtained from the GPS/GIS system. Furthermore, the trajectory of the SOC is preplanned to ensure sufficient electricity for the uphill terrain in the charge depleting (CD) and charge sustaining (CS) modes. The genetic algorithm is applied to optimize the parameters of the control strategy to maintain the SOC of battery in the CD mode. The pre-charge mode is designed to charge the battery in the CS mode from a reasonable distan... [more]

In this paper, we propose novel techniques to reduce total cost and peak load of factories from a customer point of view. We control energy storage system (ESS) to minimize the total electricity bill under the Korea commercial and industrial (KCI) tariff, which both considers peak load and time of use (ToU). Under the KCI tariff, the average peak load, which is the maximum among all average power consumptions measured every 15 min for the past 12 months, determines the monthly base cost, and thus peak load control is extremely critical. We aim to leverage ESS for both peak load reduction based on load prediction as well as energy arbitrage exploiting ToU. However, load prediction inevitably has uncertainty, which makes ESS operation challenging with KCI tariff. To tackle it, we apply robust optimization to minimize risk in a real environment. Our approach significantly reduces the peak load by 49.9% and the total cost by 10.8% compared to the case that does not consider load uncertaint... [more]

This paper describes the detailed analysis of a reactor application for a power plant to mitigate the voltage rise of a distribution line (DL) caused by the connection of distributed resources (DRs). The maximum capacity of renewable energy generators (REGs) that meets the acceptable voltage rise of a DL and the necessary capacity of the reactor to mitigate that voltage rise according to the different types of REGs are analyzed. The re-coordination of a protection relay and the loss of generation revenue as well as the installation location of a reactor are described. Finally, the ON/OFF conditions of the reactor, such as the magnitudes of the grid voltage and generator voltage, and the duration time of the voltage rise are analyzed. As the voltage rise is mitigated and self-limited in small power plants, it is confirmed that the capacity of the DRs connected to the DL can be increased through a field demonstration.

The reliability of the generating system adequacy is evaluated based on the ability of the system to satisfy the load demand. In this paper, a novel optimization technique named the disparity evolution genetic algorithm (DEGA) is proposed for reliability assessment of power generation. Disparity evolution is used to enhance the performance of the probability of mutation in a genetic algorithm (GA) by incorporating features from the paradigm into the disparity theory. The DEGA is based on metaheuristic searching for the truncated sampling of state-space for the reliability assessment of power generation system adequacy. Two reliability test systems (IEEE-RTS-79 and (IEEE-RTS-96) are used to demonstrate the effectiveness of the proposed algorithm. The simulation result shows the DEGA can generate a larger variety of the individuals in an early stage of the next population generation. It is also able to estimate the reliability indices accurately.

With the smart grid revolution, there is a growing interest in the use of power converters associated to LCL filters to interface between the main utility grid and loads or renewable energy sources. LCL filters are commonly used mainly due to their low cost and high filtering performances. To achieve these performances, it is necessary to meticulously pick out the LCL filter parameters, taking into account grid code requirements and grid configuration and/or conditions. Several methodologies for LCL filter design have been presented and discussed in the literature. The main goal of this paper is to propose a simple, robust and systematic design methodology for LCL filter parameter tuning. The considered design methodology is aimed to overcome the shortcomings of classical design methodologies, namely, stable operation under different grid configurations and conditions. Compared to previous works, the proposed design methodology allows the achievement of robust LCL filter design with re... [more]

This paper discusses the effect of load change on the Thevenin equivalent impedance of power systems. In this paper, the Thevenin equivalent impedance influenced by the derivative of active load with respect to reactive load (dP dQ) is analyzed. The Thevenin equivalent impedance forms a closed curve in a complex plane and shrinks to one point when voltage collapses. The magnitude of the Thevenin equivalent impedance at the collapse point is equal to the magnitude of the load impedance. Therefore, the impedance match theory still holds under the effect of the load change. These features are verified on a New England 39-bus system.