- 标题
- 摘要
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- 实验方案
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Energy Management and Coordinated Control Strategy of PV/HESS AC Microgrid during Islanded Operation
摘要： An energy management control strategy is proposed for an islanded AC microgrid with the hybrid energy storage system (HESS) including the battery and the supercapacitor (SC). According to the state of charge(SOC) of the battery, the photovoltaic (PV) system can work in either maximum power point tracking (MPPT) mode or load power tracking (LPT) mode to prevent the battery from over charging. Similarly, the load shedding control (LSC) is adopted to prevent the battery from over discharging. A virtual impedance control strategy is proposed to achieve effective power sharing in hybrid energy storage systems, where battery provides steady state power and SC only supports transient power fluctuations. The terminal voltage of SC can be restored to the initial value automatically by introducing a high pass filter in the voltage control loop. The AC bus voltage maintains constant using the voltage secondary controller to compensate the voltage droop caused by the virtual impedance control strategy. Simulation results under typical working conditions verify the correctness and effectiveness of the proposed control strategy.
关键词： hybrid energy storage system (HESS),energy management,state of charge (SOC),Coordinated control,voltage restoration,islanded operation,virtual impedance
更新于2025-09-23 15:23:52
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[Lecture Notes in Computer Science] Hybrid Metaheuristics Volume 11299 (11th International Workshop, HM 2019, Concepción, Chile, January 16–18, 2019, Proceedings) || Optimization of the Velocity Profile of a Solar Car Used in the Atacama Desert
摘要： Global energy demand has undergone a substantial increase in past decades because of the rapid increase of the global population and the energetic consumption of new production technologies. As a result, a change is necessary in the global energy generating matrix, in which the sources originate primarily from renewable energy sources. The main renewable energy source may be solar energy, and one of its applications is solar mobility. A world-class solar racing car exists that requires a rational use of velocity and energy to minimize the time spent in a race. A total of three search metaheuristics were tested to achieve an efficient velocity profile for this car in the Atacama 2018 Solar Race: Genetic Algorithm, Simulated Annealing and Iterated Local Search. The three methods provided similar results, with Simulated Annealing being the one that provided better solutions.
关键词： Metaheuristics,Energy management,Solar competition,Hybrid electric vehicle
更新于2025-09-23 15:23:52
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[IEEE 2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm) - Aalborg, Denmark (2018.10.29-2018.10.31)] 2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm) - Distributed Cooperative Energy Management in Smart Microgrids with Solar Energy Prediction
摘要： Smart Microgrid (SMG), integrated with renewable energy, energy storage system and advanced bidirectional communication network, has been envisioned to improve efficiency and reliability of power delivery. However, the stochastic nature of renewable energy and privacy concerns due to intensive bidirectional data exchange make the traditional energy management system (EMS) perform poorly. In order to improve operational efficiency and customers’ satisfaction, we propose a distributed cooperative energy management system (DCEMS). We adopt recurrent neural network with long short-term memory to predict the solar energy generation with high accuracy. We then solve the underlying economic dispatch problem with distributed scalable Alternating Direction Method of Multipliers (ADMM) algorithm to avoid single point of failure problem and preserve customers’ privacy. In the first stage, each SMG optimizes its operation decision vector in a centralized manner based on one-day ahead solar energy generation prediction. In the second stage, all SMGs share their energy exchange information with directly connected neighboring SMGs to cooperatively optimize the global operation cost. The proposed DCEMS is deployed in our distributed SMGs emulation platform and its performance is compared with other approaches. The results show that the proposed DCEMS outperforms heuristic rule-based EMS by more than 30%. It can also protect customers’ privacy and avoid single point of failure without degrading performance too much compared to centralized EMS.
关键词： Information prediction,Microgrid emulation platform,Distributed algorithms,Energy management system,Demand-side management
更新于2025-09-23 15:22:29
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[IEEE 2018 IEEE Energy Conversion Congress and Exposition (ECCE) - Portland, OR, USA (2018.9.23-2018.9.27)] 2018 IEEE Energy Conversion Congress and Exposition (ECCE) - Net Zero Energy Houses with Dispatchable Solar PV Power Supported by Electric Water Heater and Battery Energy Storage
摘要： Over a year, net zero energy (NZE) houses produce and feed zero net metered electrical energy to the grid. Technical challenges, notably the 'duck curve' arise due to the fact that peak solar generation and load demand are seldom coincident. Common approaches to mitigate this limitation include the curtailment of solar power, and the use of storage. Surplus solar energy may be stored in a battery, which can subsequently be discharged to supply the home electricity needs when demand is in excess. In addition to batteries, less expensive electric water heaters, which are ubiquitous, can be modified as energy storage systems, functioning as 'uni-directional batteries' by virtue of their high thermal mass. This paper proposes the use of a hybrid energy storage system including both batteries and variable power electric water heaters in NZE residences. It is demonstrated that the hybrid energy storage system along with solar PV generation coordinated and virtual power plant (VPP) controls would reduce the required battery size and ratings while still harvesting the maximum solar energy potential. The proposed control strategy enables the NZE homes to produce dispatchable power or behave like controllable loads, and benefits at the utility level are demonstrated by interconnection of NZE homes with an IEEE 13 node test feeder system. The technology has the potential to mitigate all issues related to solar power variability.
关键词： Net Zero Energy (NZE) Residences,Home Energy Management (HEM),Electrical Water Heater (EWH),Virtual Power Plant (VPP),Battery Energy Storage System (BESS)
更新于2025-09-23 15:22:29
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Planning Solar in Energy-Managed Cellular Networks
摘要： Recently, there has been a lot of interest on the energy efficiency and environmental impact of wireless networks. Given that the base stations are the network elements that use most of this energy, much research has dealt with ways to reduce the energy used by the base stations by turning them off during periods of low load. In addition to this, installing a solar harvesting system made up of solar panels, batteries, charge controllers, and inverters is another way to further reduce the network environmental impact, and some research has been dealing with this for individual base stations. In this paper, we show that both techniques are tightly coupled. We propose a mathematical model that captures the synergy between solar installation over a network and the dynamic operation of energy-managed base stations. We study the interactions between the two methods for networks of hundreds of base stations and show that the order in which each method is introduced into the system does make a difference in terms of cost and performance. We also show that installing solar is not always the best solution even when the unit cost of the solar energy is smaller than the grid cost. We conclude that planning the solar installation and energy management of the base stations has to be done jointly.
关键词： Cellular networks,solar power,energy management,sleep mode
更新于2025-09-23 15:22:29
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Energy scheduling of a smart microgrid with shared photovoltaic panels and storage: The case of the Ballen marina in Sams??
摘要： This paper focuses on the Model Predictive Control (MPC) based energy scheduling of a smart microgrid equipped with non-controllable (i.e., with fixed power profile) and controllable (i.e., with flexible and programmable operation) electrical appliances, as well as photovoltaic (PV) panels, and a battery energy storage system (BESS). The proposed control strategy aims at a simultaneous optimal planning of the controllable loads, the shared resources (i.e., the storage system charge/discharge and renewable energy usage), and the energy exchange with the grid. The control scheme relies on an iterative finite horizon on-line optimization, implementing a mixed integer linear programming energy scheduling algorithm to maximize the self-supply with solar energy and/or minimize the daily cost of energy bought from the grid under time-varying energy pricing. At each time step, the resulting optimization problem is solved providing the optimal operations of controllable loads, the optimal amount of energy to be bought/sold from/to the grid, and the optimal charging/discharging profile for the BESS. The proposed energy scheduling approach is applied to the demand side management control of the marina of Ballen, Sams? (Denmark), where a smart microgrid is currently being implemented as a demonstrator in the Horizon2020 European research project SMILE. Simulations considering the marina electric consumption (340 boat sockets, a service building equipped with a sauna and a wastewater pumping station, and the harbour master’s office equipped with a heat pump), PV production (60kWp), and the BESS (237 kWh capacity) based on a public real dataset are carried out on a one year time series with a 1 h resolution. Simulations indicate that the proposed approach allows 90% exploitation of the production of the PV plant. Furthermore, results are compared to a na?ve control approach. The MPC based energy scheduling improves the self-supply by 1.6% compared to the na?ve control. Optimization of the business economy using the MPC approach, instead, yields to 8.2% savings in the yearly energy cost with respect to the na?ve approach.
关键词： Energy management,Renewable energy,On-line scheduling,Microgrid,Optimization algorithm,Demand side management,Model predictive control,Energy storage
更新于2025-09-23 15:21:01
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Photovoltaic Potential Assessment and Dust Impacts on Photovoltaic Systems in Iran: Review Paper
摘要： Smart-fabric interactive-textile systems offer exciting new possibilities, provided that they exhibit sufficient robustness and autonomy to be reliably deployed in critical applications. Textile multiantenna systems, unobtrusively integrated in a professional garment, are key components of such systems, as they set up energy-efficient and stable wireless body-centric communication links. Yet, their functionality may be further extended by exploiting their surface as energy-harvesting platform. Different state-of-the-art energy harvesters are suitable for compact integration onto a textile antenna. We demonstrate this by integrating a power management system, together with multiple diverse scavenging transducers and a storage module, on a well-chosen textile antenna topology. We provide guidelines to ensure that the additional hardware does not affect the textile antenna’s performance. Simultaneous scavenging from different energy sources significantly increases the autonomy of a wearable system, in the meanwhile reducing battery size.
关键词： energy management,energy storage,Energy harvesting,interactive textiles,textile antenna,wearable antenna,smart fabrics
更新于2025-09-23 15:21:01
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Design, Simulation and Fabrication of a High Gain Low Sidelobe Level Waveguide Slot Array Antenna at X-band with Zero Beam Tilts in Both Azimuth and Elevation Directions
摘要： This paper presents the development of an intelligent dynamic energy management system (I-DEMS) for a smart microgrid. An evolutionary adaptive dynamic programming and reinforcement learning framework is introduced for evolving the I-DEMS online. The I-DEMS is an optimal or near-optimal DEMS capable of performing grid-connected and islanded microgrid operations. The primary sources of energy are sustainable, green, and environmentally friendly renewable energy systems (RESs), e.g., wind and solar; however, these forms of energy are uncertain and nondispatchable. Backup battery energy storage and thermal generation were used to overcome these challenges. Using the I-DEMS to schedule dispatches allowed the RESs and energy storage devices to be utilized to their maximum in order to supply the critical load at all times. Based on the microgrid’s system states, the I-DEMS generates energy dispatch control signals, while a forward-looking network evaluates the dispatched control signals over time. Typical results are presented for varying generation and load profiles, and the performance of I-DEMS is compared with that of a decision tree approach-based DEMS (D-DEMS). The robust performance of the I-DEMS was illustrated by examining microgrid operations under different battery energy storage conditions.
关键词： microgrid,Adaptive dynamic programming,reinforcement learning,evolutionary computing,dynamic energy management system (DEMS),renewable energy,neural networks
更新于2025-09-23 15:21:01
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Smart charging of electric vehicles considering photovoltaic power production and electricity consumption: a review
摘要： Photovoltaics (PV) and electric vehicles (EVs) are two emerging technologies often considered as cornerstones in the energy and transportation systems of future sustainable cities. They both have to be integrated into the power systems and be operated together with already existing loads and generators and, often, into buildings, where they potentially impact the overall energy performance of the buildings. Thus, a high penetration of both PV and EVs poses new challenges for cities. With a potentially large increase in PV and EV penetration, understanding of the synergies between PV, EVs and existing electricity consumption is required. Thus, a high penetration of both PV and EVs poses new challenges. Understanding of the synergies between PV, EVs and existing electricity consumption is therefore required. Recent research has shown that smart charging of EVs could improve the synergy between PV, EVs and electricity consumption, leading to both technical and economic advantages. Considering the growing interest in this field, this review paper summarizes state-of-the-art studies of smart charging considering PV power production and electricity consumption. The main aspects of smart charging reviewed are objectives, configurations, algorithms and mathematical models. In order to achieve certain objectives, smart charging schemes can be based on optimization or rule based algorithms. The smart charging schemes also vary in terms of control configuration, i.e., centralized and distributed, and depend on spatial configuration, i.e., houses, workplaces and charging stations. Various charging objectives, such as increasing PV utilization and reducing peak loads and charging cost, are reviewed in this paper. The different charging control configurations, i.e., centralized and distributed, along with various spatial configurations, e.g., houses and workplaces, are also discussed. After that, the commonly employed optimization techniques and rule-based algorithms for smart charging are reviewed. Further research should focus on finding optimal trade-offs between simplicity and performance of smart charging schemes in terms of control configuration, charging algorithms, as well as the inclusion of PV power and load forecast in order to make the schemes suitable for practical implementations.
关键词： electric vehicles,Photovoltaics,energy management system,smart charging,charging optimization,electricity consumption
更新于2025-09-23 15:21:01
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[Advances in Intelligent Systems and Computing] Applications of Artificial Intelligence Techniques in Engineering Volume 698 (SIGMA 2018, Volume 1) || Predictive Control of Energy Management System for Fuel Cell Assisted Photo Voltaic Hybrid Power System
摘要： Distributed generation systems also known as hybrid power systems which involve renewable energy sources are extensively used due to their ef?ciency and green interface. Considering the varying environmental conditions, these systems are prone to many disadvantages and limitations. In order to overcome these constraints, intelligent techniques which can achieve steady process and power balance are to be implemented. This paper provides an intelligent control using fuzzy inference system and energy management algorithm for Fuel cell assisted PV Battery system. The supervisory control was implemented to achieve utmost feasible ef?- ciency despite varying conditions such as irradiance and Hydrogen levels. With Lev- elized cost being adapted, an ef?cient energy management system attributes for even power distribution throughout the day can be implemented. Our thought process was demonstrated, and ?nal software interface was simulated using MATLAB/Simulink to obtain results which con?rm the effectiveness of the developed system.
关键词： MPPT,Inference systems,Fuzzy logic controller,Energy management,Fuel cell,PVFC hybrid system
更新于2025-09-23 15:21:01