Search Results (25)

Electric vehicles (EVs) are essential for sustainable urban mobility, coordinating transportation demands with energy distribution networks. However, uncoordinated EV charging neglects trip chain continuity, inducing spatial–temporal congestion and overloading local charging capacities. Thus, effectively guiding EVs is a key problem in mitigating traffic emissions and preventing power grid-side stress. In this paper, a two-stage dynamic routing framework within a traffic–energy coordination architecture is proposed, integrating an AHP–Entropy–TOPSIS model for station selection and an Improved Ant Colony Optimization algorithm for trajectory execution. Using this framework, a series of macro–micro simulations on the Sioux Falls network was conducted alongside a congestion-driven dynamic pricing mechanism. The results indicate that the pricing strategy facilitates spatial load balancing through peak shaving at core nodes. Compared to conventional standard meta-heuristic baselines, this framework reduces average economic costs by 28.9% while ensuring battery safety and limiting indirect carbon emissions. The proposed framework provides a multi-objective navigation solution that prevents cross-layer decision fragmentation, supporting the sustainable development of smart city infrastructure. Full article

Multilevel inverters (MLI) have become the frontier in high-power medium voltage systems because of their unique property of generating sinusoidal voltage through smaller voltage increments. Although many MLI structures have been proposed over the years, most still rely on a large number of switches, which increases complexity and conduction losses. In this work, a reconfigurable, gable-shaped multilevel inverter module, capable of operating in both symmetric and asymmetric modes, is introduced for use in AC microgrid cluster environments. The design employs five DC sources and six semiconductor devices arranged in a gable layout, which helps shorten the conduction path while also reducing the total hardware count. As a result, the inverter becomes more compact, experiences lower switching losses, and proves more suitable for grid-connected operation. In symmetric mode, the inverter delivers an 11-level output, while the asymmetric arrangement produces 19 levels. The proposed concept is examined through MATLAB/Simulink (R2023a) studies, and its practicality is verified using a Hardware-in-the-Loop setup with an integrated data-acquisition system capable of delivering 10 kW of real power and handling up to 50% overload. These results confirm the suitability of the topology for real-time grid applications. Full article

The aim of this paper is to develop a self-adaptive control methodology capable of optimizing in real-time the operation of PV-powered microgrids by dynamically managing both the output powers of battery energy storage systems (BESSs) and power exchanges with the utility grid. Control actions are evaluated by solving a constrained multi-objective optimization problem that integrates the optimal state-of-charge (SoC) management of BESSs within a broader economic dispatch framework. In this way, the SoC is continuously optimized alongside other economic objectives, such as minimizing operating costs and maximizing revenues from energy sales to the grid, while maintaining the microgrid’s energy balance. This ensures that BESSs operate efficiently within their optimal ranges, preventing premature depletion or overload and thereby safeguarding overall microgrid performance. To enable real-time adaptability, the methodology employs a Lyapunov-based optimization algorithm combined with a sensitivity analysis, ensuring rapid convergence to optimal solutions, even under rapidly changing conditions. Computer simulations performed on a low-voltage PV-BESS-based microgrid under different operating conditions confirm the effectiveness of the proposed methodology in enhancing real-time economic performance, operational efficiency, and microgrid reliability. Full article

The Czech Republic and Poland are struggling with problems related to the development of photovoltaics. Both analyzed countries had periods of dynamic development of this renewable energy source (RES). However, neither the Czech Republic nor Poland have developed mechanisms that would lead to the stable development of photovoltaic installations in the long term. The analyses presented in this article demonstrate the implementation of extreme solutions by these countries, which led either to stagnation in the development of photovoltaics or to an excessive increase in the installed capacity, including RES, which then had to be stopped due to, for example, the failure of the power grids to match the increasing capacity. This article conducted research based on secondary data and using the Foresight method. The aim of this manuscript is to present the conditions related to the development of photovoltaics in the Czech Republic and Poland. This article also points to the barriers limiting the development of this type of RES and the potential of solutions related to, e.g., energy storage, which will allow for maintaining stable development of photovoltaics in the future and will prevent excessive overloading of power grids. The research results indicate that in the context of further development of photovoltaics in the study area, what is important are, e.g., changes in legal regulations and financial incentives that will enable the development of micro-installations within energy communities to a greater extent, including co-financing for energy storage. Other factors were also noted, including interconnection capacity within the energy systems of these countries, as well as externally. Full article

In response to the growing need for enhanced energy management in smart grids in sustainable smart cities, this study addresses the critical need for grid stability and efficient integration of renewable energy sources, utilizing advanced technologies like 6G IoT, AI, and blockchain. By deploying a suite of machine learning models like decision trees, XGBoost, support vector machines, and optimally tuned artificial neural networks, grid load fluctuations are predicted, especially during peak demand periods, to prevent overloads and ensure consistent power delivery. Additionally, long short-term memory recurrent neural networks analyze weather data to forecast solar energy production accurately, enabling better energy consumption planning. For microgrid management within individual buildings or clusters, deep Q reinforcement learning dynamically manages and optimizes photovoltaic energy usage, enhancing overall efficiency. The integration of a sophisticated visualization dashboard provides real-time updates and facilitates strategic planning by making complex data accessible. Lastly, the use of blockchain technology in verifying energy consumption readings and transactions promotes transparency and trust, which is crucial for the broader adoption of renewable resources. The combined approach not only stabilizes grid operations but also fosters the reliability and sustainability of energy systems, supporting a more robust adoption of renewable energies. Full article

The growing penetration of fast charging stations (FCSs) to electric vehicles (EVs) and distributed energy resources (DERs) in the electrical power system brings technical issue changes in the voltage profile throughout grid nodes and feeder current overload. The provision of ancillary services by DERs and FCSs arises as an appealing solution to reduce these adverse effects, enhancing the grid hosting capacity. The control of microgrids is essential for the coordinated implementation of these services. Although microgrid control is widely applied to DERs, few studies address the coordinated control of DERs and FCSs to obtain benefits for the electrical power system. This paper proposes a coordinated and simultaneous control of DERs and FCSs based on the power-based control (PBC) strategy, efficiently exploiting FCSs in a microgrid model previously unaddressed in the literature. The results show that, with the coordinated control of DERs and FCSs, the control of the power flow in a minigrid (MG) is achieved both in moments of high generation and in moments of high load, even with the maximum operation of DERs. This method allows for the maintenance of voltage levels within values considered acceptable by technical standards (above 0.93 pu). The maintenance of voltage levels is derived from reducing the overload on the point of common coupling (PCC) of the minigrid by 28%, performing the peak shaving ancillary service. Furthermore, the method allows for the control of zero power flow in the PCC of the minigrid with the upstream electric grid in periods of high generation, performing the ancillary service of valley filling. The method performs this control without compromising vehicle recharging and power dispatch by DERs. Full article

The growing penetration of electric vehicles (EVs) introduces both opportunities and challenges for power grid operators. Incentivization is considered a viable option to tempt EV owners to participate in supporting the grid during peak load intervals while receiving compensation for their services. Therefore, this study proposes a two-step incentive mechanism to reduce the peak load of the grid by enabling power trading among the microgrid, EVs and the utility grid. In the first step, an incentive price is determined for EVs considering the grid-loading conditions during different hours of the day. In the second step, a multi-objective optimization problem is formulated to optimize trading among different entities, such as EVs, the microgrid and the utility grid. The two objectives considered in this study are the operation cost of the microgrid and the revenue of EVs. Monte Carlo simulations are used to deal with uncertainties associated with EVs. Simulations are conducted to analyze the impact of different weight parameters on the energy-trading amount and operation cost of EVs and MG. In addition, a sensitivity analysis is conducted to analyze the impact of changes in the EV fleet size on the energy-trading amount and operation cost. Full article

Fuel cells have drawn a lot of interest in recent years as one of the most promising alternative green power sources in microgrid systems. The operating conditions and the integrated components greatly impact the quality of the fuel cell’s voltage. Energy management techniques are required in this regard to regulate the fuel cell’s power in a microgrid. The active/reactive power in the microgrid should be adjusted in line with US Energy Star’s regulations whereas the grid current needs to follow the standard set by IEEE 519 2014 to enhance the power quality of the electrical energy injected into the microgrid. Uncontrolled energy injection from the fuel cell can have serious impacts including superfluous energy demand, overloading, and power losses, especially in high power and medium voltage systems. Although fuel cells have many advantages, they cannot yet produce high voltages individually to compensate for the demand of a microgrid system. Due to these reasons, the fuel cell must be interfaced with a DC-DC converter. This research proposes a novel high voltage gain converter integrated 1.26 kW fuel cell for microgrid power management that can boost the fuel cell’s voltage up to 20 times. Due to this high voltage gain, the voltage and current ripple of the fuel cell is also reduced substantially. According to the analysis, the proposed converter demonstrated optimal performance when compared to the other converters due to its high voltage gain and extremely low voltage ripple. As a result, the harmonic profile of the microgrid current persists with a reduced THD of 3.22% and a very low voltage ripple of 4 V. To validate the converter’s performance, along with extensive simulation, a hardware prototype was also built. The voltage of the fuel cell is regulated using a simplified proportional integral controller. The operating principle of the converter integrated fuel cell along with its application in microgrid power management is demonstrated. A comparative analysis is also shown to verify how the proposed converter is improving the system’s performance when compared against other converters. Full article

Battery energy storage systems (BESSs) can control the power balance in DC microgrids through power injection or absorption. A BESS uses a bidirectional DC–DC converter to control the power flow to/from the grid. On the other hand, any fault occurrence in the power switches of the bidirectional converter may disturb the power balance and stability of the DC microgrid and, thus, the safe operation of the battery bank. This paper presents a fault-tolerant topology along with a fault diagnosis algorithm for a bidirectional DC–DC converter in a BESS. The proposed scheme can detect open circuit faults (OCFs) and reconfigure the topology to guarantee the safe and continuous operation of the system while it is connected to the DC microgrid. The proposed method can be extended to multi-phase structures of interleaved bidirectional DC–DC converters using only two power switches and n TRIACs to support the OCF occurrence on 2 × n switches of n legs. The proposed fault diagnosis algorithm detects OCFs only by observing the current of the inductors and does not require any sensor. Hence, the cost, weight, volume and complexity of the system is considerably reduced. Experimental results show that the reconfiguration of the converter, along with its fast fault detection, leads to fewer switches overloading and less DC voltage deviation. Full article

The area of a Microgrid (μG) is a very fast-growing and promising system for overcoming power barriers. This paper examines the impacts of a microgrid system considering Electric Vehicle Grid Integration (EVGI) based on stochastic metaheuristic methods. One of the biggest challenges to slowing down global climate change is the transition to sustainable mobility. Renewable Energy Sources (RESs) integrated with Evs are considered a solution for the power and environmental issues needed to achieve Sustainable Development Goal Seven (SDG7) and Climate Action Goal 13 (CAG13). The aforementioned goals can be achieved by coupling Evs with the utility grid and other RESs using Vehicle-to-Grid (V2G) technology to form a hybrid system. Overloading is a challenge due to the unknown number of loads (unknown number of Evs). Thus, this study helps to establish the system impact of the uncertainties (arrival and departure Evs) by proposing Stochastic Monte Carlo Method (SMCM) to be addressed. The main objective of this research is to size the system configurations using a metaheuristic algorithm and analyze the impact of an uncertain number of Evs on the distribution of residential power in Tripoli-Libya to gain a cost-effective, reliable, and renewable system. The Improved Antlion Optimization (IALO) algorithm is an optimization technique used for determining the optimal number of configurations of the hybrid system considering multiple sources, while the Rule-Based Energy Management Strategy (RB-EMS) controlling algorithm is used to control the flow of power in the electric power system. The sensitivity analysis of the effect parameters has been taken into account to assess the expected impact in the future. The results obtained from the sizing, controlling, and sensitivity analyses are discussed. Full article

In the new energy DC microgrid system, most of the new energy outputs DC power with a low voltage level and a large fluctuation range, which cannot be directly connected to the network. It needs to be boosted by a DC–DC converter, then connected to the power grid or supplied with a DC load. On the premise that the traditional DC–DC converter cannot meet the requirements of high-power applications, the interleaved dual boost converter (IDBC) has been widely used because of its low input current ripple, low device stress and high-power density. It is necessary to maintain the current balance of each phase of the converter during a heavy load and to improve the efficiency during a light load. This paper analyzes the working principle of the six-phase IDBC and reduces the high order model to the low order model according to the symmetry. Due to the current imbalance caused by the mismatch of the parasitic parameters of each phase, two current distribution strategies are designed for different operating. To balance the current of each phase when the converter is overloaded, the relationship between the phase current, parasitic parameters and duty cycle is analyzed based on the state space average method. The estimated parasitic parameters are used to obtain the duty cycle compensation of each phase to eliminate the current imbalance. In addition, to improve the overall efficiency of the converter when the converter connects with a light load, the optimal power distribution coefficient is obtained according to the parasitic parameters to achieve the optimization of the input power, so as to improve the efficiency of the converter. Finally, the simulation results verify the feasibility and effectiveness of the proposed control strategy. Full article

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 other users, e.g., for demand response or to trade energy in the electric market. This paper introduces a comprehensive theoretical approach of E-LAN control to achieve all the above operational goals while providing a high level of dynamic protection against faults or other events affecting the system functionality, e.g., overloads or fast transients. It shows that meshed microgrids are the necessary infrastructure to implement the desired functionalities. Full article

The two common mechanisms of load-shedding and renewable curtailment can prevent provisional overloading and excessive generation and the subsequent unacceptable voltage and frequency deviation in standalone microgrids (MGs), which makes MGs less resilient and reliable. However, instead of enabling load-shedding or renewable curtailment, such overloading or over-generation problems can be alleviated more efficiently and cost-effectively by provisionally interconnecting the neighboring MGs to exchange power amongst themselves. In such a scheme, the interconnected MGs can supply their local demand, as well as a portion of the demand of the adjacent MGs. In order to implement this strategy, a three-phase ac link can be used as the power exchange network, while each MG is coupled to the link through a back-to-back power electronics converter, in order to maintain the autonomy of each MG if they are eachoperated under different standards. This paper proposes a suitable decentralized power management strategy without a communication link between the MGs to achieve power-sharing amongst them and alleviate unacceptable voltage and frequency deviation along with the required control technique for the power electronic converters, which can be implemented at the primary level based on the measurement of the local parameters only. To this end, one of the converters should always regulate the dc link voltage while the other converter should operate in droop control mode when the MG is healthy and in constant PQ mode when overloaded or over-generating. Suitable status detection and mode transition algorithms and controllers were also developed and are proposed in this paper. The performance of the proposed power exchange and control mechanisms were evaluated and verified via PSIM^®-based numerical simulation studies. The stability and sensitivity of the proposed power exchange topology are also analyzed against several critical design and operational parameters. Full article

In isolated areas such as islands with small power grids, the BESS (Battery energy storage system) can supply the standard voltage and frequency to the power system to achieve 100% of renewable sharing. In addition, the installation of additional BESS may be required in the microgrid due to technical limitations such as redundant operation and manufacturer specifications. Thus, the BESSs in a microgrid can be split into main and sub BESSs which play a role as the main source and auxiliary services, respectively. Generally, the ratio of unbalance current in microgrid system tends to be high, because of inherently unbalanced single phase load distribution. However, because the capacity of BESS is calculated under balanced conditions, the PCS (Power conversion system) of BESS may stop protecting its switching device from a single phase overcurrent in actual operation. From this perspective, this paper proposes that the sub BESSs perform dual current control to supply the unbalanced current instead of the main BESS. In the simulation result of the proposed method, the current unbalance rate of the main ESS has been reduced by about 26%. Through the proposed control scheme, it is possible to prevent an unexpected single phase overload of the main BESS in the microgrid. Full article

Recently, the lift off point for the sales of electric vehicle (EV) was started with a significant increase. Therefore, convenient access to charging station infrastructure is required. The purpose of this work is to assess the role and benefits of photovoltaic (PV) for PV-powered charging infrastructures for EVs by a better energy management. This management is performed by a microgrid based on PV panels installed on roofs or car parking shades, EVs charging terminals, electrochemical stationary storage, and public grid connection. The aim is to define the economic aspects, feasibility and preliminary requirements for this system, in order to avoid overloading the power grid and guarantee a higher percentage of clean energy. The proposed methodology is presented through the modeling and development of a techno-economic tool for local stakeholders, allowing to manage and size EV charging stations, which is divided into three phases. The first phase informs local stakeholders on the necessary space and the maximum sizing as well as the generated cost to install a PV-powered charging station (PVCS). During the second phase, the total cost of the PVCS is adjusted according to the users’ budgets and needs. The third phase presents a detailed qualitative analysis of the user-defined configuration. In this phase, the main objective is to assess the performance of the PVCS, and then, to improve its sizing and its operating modes aiming at increasing the use of PV energy, while minimizing energy supplied by the power grid. In addition, it allows evaluating the PVCS performance by proposing an energy balance according to different charging scenarios (virtuous scenario, critical scenario, realistic scenario, and personalized scenario) and weather conditions. Moreover, this tool is reproducible in peri-urban area since it is able to handle any location. Full article