Power Management Control Research Articles

Bidirectional Power Sharing for DC Microgrid Enabled by Dual Active Bridge DC-DC Converter

Currently, high-performance power conversion requirements are of increasing interest in microgrid applications. In fact, isolated bidirectional dc-dc converters are widely used in modern dc distribution systems. The dual active bridge (DAB) dc-dc converter is identified as one of the most promising converter topology for the mentioned applications, due to its benefits of high power density, electrical isolation, bidirectional power flow, zero-voltage switching, and symmetrical structure. This study presents a power management control scheme in order to ensure the power balance of a dc microgrid in stand-alone operation, where the renewable energy source (RES) and the battery energy storage (BES) unit are interfaced by DAB converters. The power management algorithm, as introduced in this work, selects the proper operation of the RES system and BES system, based on load/generation power and state-of-charge of the battery conditions. Moreover, a nonlinear robust control strategy is proposed when the DAB converters are in voltage-mode-control in order to enhance the dynamic performance and robustness of the common dc-bus voltage, in addition to overcoming the instability problems that are caused by constant power loads and the dynamic interactions of power electronic converters. The simulation platform is developed in MATLAB/Simulink, where a photovoltaic system and battery system are selected as the typical RES and BES, respectively. Assessments on the performance of the proposed control scheme are conducted. Comparisons with the other control method are also provided.

RETRACTED: A smart grid incorporated with ML and IoT for a secure management system

The economy, national safety, and health care are tremendously dependent on the faithful supply of power. The communication technology integration and sensors in power systems have been authorized as a smart grid (SG) that is revolutionizing the model of power generation, distribution, monitoring, and control. To know the Smart Grid compatibility, many problems are required to be directed. The safety of the smart grid is the most challenging function and very crucial difficulties. This paper proposed, a safe demand-side management machine deploying machine learning for the Internet of Things authorized phase is recommended. The propounded demand-side management (DSM) machine protects the effective energy use based on their preferences. A particular flexibility sample was proposed to manage incursion into the smart grid. Anelastic agent prognosticates swindling companies, the ML classifiers are utilized. Promoted power management and intermediate control companies are recommended for processing power data to improve energy usage. The proposed project's effective simulation is implemented to examine the efficiency. The outcome of the analysis discloses that the planned demand-side management (DSM) machine is less susceptible to the incursion and it is sufficient to decrease the smart grid's energy consumption.

Power Management, Voltage Control and Grid Synchronization of Microgrids in Real Time

This paper presents an efficient power management, voltage balancing and grid synchronization control strategy to increase the stability and reliability of distributed energy resources (DERs)-based microgrid. The microgrid is composed of Photovoltaic, Double Fed Induction Generator-based wind and diesel generator with critical and non-critical loads. The system model and the control strategy have been developed in Real Time Digital Simulator. The coordination and power management of the DERs in both grid connected and island operation modes is implemented. One distinct challenge of microgrid operation in island mode is the stable control of frequency. A controller is proposed and implemented in the island mode for the diesel generator equipped with the required inertia to maintain the microgrid rated frequency by operating in the isochronous mode. To restore the microgrid back to the utility, the voltage, frequency and phase angle of the islanded microgrid should match with that of the grid network within specified limits to avoid transient instability. Switched capacitor banks are connected at the point of common coupling to balance the voltage for microgrid synchronization. The CIGRE medium voltage test bench system is used to implement the DERs and their controller. The proposed control approach has potential applications for the complete operation of microgrids by properly controlling the power, voltage and frequency in both grid and island modes. The real time digital simulator results verify the effectiveness and superiority of the proposed control scheme in grid connected, island and grid resynchronization scenarios.

Modified iterative learning controller for efficient power management of hybrid AC/DC microgrid

Modified iterative learning controller for efficient power management of hybrid AC/DC microgrid

Modified iterative learning controller for efficient power management of hybrid AC/DC microgrid

In this paper, modified ILC is proposed for maintaining stable voltage, frequency and for efficient power management in a hybrid micro grid (HMG). The system is modelled with solar, battery, DC loads at DC bus, wind turbine, utility grid and AC loads at AC bus. An interlinking converter (IC) is connected between the AC and DC bus to facilitate bidirectional power flow. The control of voltage at AC/DC bus and management of power are obtained in the modelled hybrid micro grid with set point weighting iterative learning controller (SPW-ILC) by controlling the interlinking converter both in autonomous and grid connected mode of operation. To minimise the error signal to the controller, the classical optimisation method of sequential quadratic programming (SQP) has been employed to improve the performance of the controller. The simulation results show that the proposed controller have better performance than other controllers under variable source and load conditions.

Seawater Battery-Based Wireless Marine Buoy System With Battery Degradation Prediction and Multiple Power Optimization Capabilities

This paper presents a wireless marine buoy system based on the seawater battery (SWB), providing self-powered operation, power-efficient management, and degradation prediction and fault detection. Since conventional open circuit voltage (OCV) methods cannot be applied due to inherent cell characteristics of SWB, the coulomb counting (CC) method is adopted for the state of charge (SOC) monitoring. For the state of health (SOH), a variance-based detection scheme is proposed to provide degradation prediction and fault detection of the SWB. The self-powered operation is augmented by two proposed power optimization schemes such as multiple power management and three-step LED light control. A wireless buoy system prototype is manufactured, and its functional feasibility is experimentally verified, where its location and SOC are periodically monitored in a smartphone-based wireless platform.

TokenSmart: Distributed, Scalable Power Management in the Many-Core Era

Centralized power management control systems are hitting a scalability limit. In particular, enforcing a power cap in a many-core system in a performance-friendly manner is quite challenging. Today’s on-chip controller reduces the clock speed of compute domains in response to local or global power limit alerts. However, this is transparent to the operating system (OS), which continues to request higher clock frequency based on the workload characteristics acting against the centralized on chip controller. To address these issues, we introduce TokenSmart, which implements a scalable distributed frequency control heuristics within the OS, using a novel token-based mechanism. The compute units are connected in a ring-topology allowing minimal meta-data to be passed along with the token value for regulating power budget. We explore different heuristics to assign tokens smartly across the units. This results in efficient power regulation and sustenance of turbo frequencies over a longer duration. The methodology is implemented within the Linux kernel of a real IBM POWER9 many-core system. The experimental results show a considerable boost of about 4 percent in throughput of PostgreSQL benchmark with a tangible 18 percent decrease in power consumption.

A Voltage-Zone Based Power Management Scheme With Seamless Power Transfer Between PV-Battery for OFF-Grid Stand-Alone System

There is a requirement for a simple solution that provides seamless power management control and eliminates the issue of toggling between different operating modes in the stand-alone photovoltaic (PV) battery based hybrid system. The solution for the same is given in this article that uses a simple voltage control strategy. The given solution uses a voltage band technique for eliminating the toggling between charging and discharging modes. Further, the toggling between intermediate PV mode with charging and discharging mode is eliminated using the inner voltage band. Thus, the proposed control strategy provides a smooth and seamless control between different modes based on load voltage information. It avoids the overlap of charging and discharging modes within the switching cycle to improve the life-span of the battery. Also, the given control strategy does not require the power information and complex computations like division, etc., for its operation. The given solution can be easily implemented on any PV-battery-based hybrid system having independent control for charging and discharging of the battery with maximum power point tracking (MPPT). A simulation was done to verify the operation in various modes using seamless control. The simulation results are further justified with experimental results from the developed lab prototype.

Distributed optimization model and algorithms for virtual energy storage systems using dynamic price

Abstract Virtual energy storage systems (VESS) are important new equipment for distribution networks, consisting of battery energy storage systems (BESS) or flexible loads (FL), that improve peak shaving, frequency regulation and energy management. This paper focuses on power management and real-time control for multiple virtual energy storage systems (MVESS). To enhance renewable energy penetration using competing objective functions in MVESS, a distributed multi-objective power management scheme is proposed, where a Nash Bargaining Solution (NBS) is used to find optimal, unique and fair solutions. A distributed integral optimization algorithm, with fast convergence, is designed to solve the NBS-based problem, containing equality and inequality constraints. Distributed real time control for MVESS is proposed to increase system efficiency and control State of Energy (SoE) and proportional power sharing between BESS and FL. The mathematical analysis guarantees optimality and convergence for the two proposed algorithms. To evaluate the performance of the strategy, three different case studies were executed on a real time digital simulator (OPAL-RT OP5600). Finally, the simulation results demonstrate that system power was shared optimally between VESS, with proportional power sharing among BESS and FL and SoE synchronization.

Power Management Controller for Microgrid Integration of Hybrid PV/Fuel Cell System Based on Artificial Deep Neural Network

Nowadays, the power demand is increasing day by day due to the growth of the population and industries. The conventional power plant alone is incompetent to meet the consumer demand due to environmental concerns. In this present situation, the essential thing is to be find an alternate way to meet the consumer demand. In present days most of the developed countries concentrate to develop alternative resources and invest huge money for its research and development activities. Most renewable energy sources are naturally friendly sources such as wind, solar, fuel cell, and hydro/water sources. The results of power generation using renewable energy sources only depend on the availability of the resources. The availability of renewable energy sources throughout the day is variable due to fluctuations in the natural resources. This research work discusses two major renewable energy power generating sources: photovoltaic (PV) cell and fuel cell. Both of them provide foundations for power generation, so they are very popular because of their impressive performance mechanisms. The mentioned renewable energy-based power generating systems are static devices, so the power losses are generally ignorable as compared to line losses in the main grid. The PV and fuel cell (FC) power systems need a controller for maximum power generation during fluctuations in the input resources. Based on the investigation report, an algorithm is proposed for an advanced maximum power point tracking (MPPT) controller. This paper proposes a deep neural network- (DNN-) based MPPT algorithm, which has been simulated using MATLAB both for PV and for FC. The main purpose behind this paper has been to develop the latest DNN controller for improving the output power quality that is generated using a hybrid PV and fuel cell system. After developing and simulating the proposed system, we performed the analysis in different possible operating conditions. Finally, we evaluated the simulation outcomes based on IEEE 1547 and 519 standards to prove the system’s effectiveness.

A Modulized Three-Port Interlinking Converter for Hybrid AC/DC/DS Microgrids Featured With a Decentralized Power Management Strategy

A compact interlinking converter modular (ICM) for hybrid ac/dc microgrids with a distributed storage (DS) bus for storage integration is proposed in this article. The advanced ICM for hybrid ac/dc/ds microgrids involves the nine-switch topology with compact configuration and decreased number of active operating switches, which structurally equivalents to afford a dc interconnection port for dc subgrid, an ac interconnection port for ac subgrid, a ds interconnection port for ds subgrid, and two dc–dc converters for the interconnection ports for parallel DSs. In addition to the popular advantage of component elements saving, the suggested ICM, aggregating various interlinking converter cells (ICCs) into an ICM, is also proficient of participating computations from all ICC sensors to enhance the overall modular performance without building extra communication connection links between ICCs. With this in mind, a decentralized power management control strategy is realized by employing a coordination power control methodology to systematically handle various distributed generations (DGs), DSs, and ICM in a decentralized manner with improved communication fault ride-through capability. The controller hardware-in-the-loop experiments on a real-time digital simulator platform validates the achievement of the advanced ICM application in hybrid ac/dc/ds microgrids and the effectiveness of the associated decentralized power management scheme.

Multiple parallel‐connected DAB‐based solid‐state transformer for hybrid DC/AC microgrid system

To cater unceasing supply to the modern AC and DC loads, renewable energy resources integrated hybrid DC/AC microgrid (HMG) are considered as a viable technological solution. In this study, a multiple parallel-connected bidirectional converter (MPBC) topology has been proposed to enhance the solid-state transformer (SST) power handling capability with flexible control of the HMG. To improve the high-frequency AC-link power quality and to control the power transfer through the SST in each dual active bridge a split-step phase shift (SSPS) control technique has been used. A power management control strategy has also been proposed for efficient power transfer between the sources and loads of the HMG. The proposed MPBC-based SST is suitable for interconnecting multiple utility feeders. Multiple redundant utility feeders ensure stiff bus voltages and omit the power supply reliability issues. The operation of the proposed MPBC-SST converter system with corresponding control algorithm is verified through the simulation results in both grid feeding and grid fetching operating modes. Furthermore, experimental results are presented to validate the performance of the proposed MPBC-SST converter along with its proposed controller strategy.

Collaborative Voltage Unbalance Elimination in Grid-Connected AC Microgrids With Grid-Feeding Inverters

The control flexibility of the power inverters that interface distributed generation can be exploited to incorporate power quality enhancement features in addition to the usual power management control. This article presents a novel control scheme that achieves voltage balance at any node of an ac microgrid regardless of the impedance value of the power network. The collaborative strategy is devoted to set a specific sharing of the balancing currents, thus avoiding the adverse effects of the unbalance compensation by a single inverter. The control scheme uses a complex form of a proportional resonant controller and a communication link. The article presents the stability and sensitivity analysis and the design guidelines for the control parameters. The performance of the control proposal has been tested successfully in a laboratory microgrid setup. Selected experimental results are presented.

Limited Power Point Tracking for a Small-Scale Wind Turbine Intended to Be Integrated in a DC Microgrid

Limited power point tracking (LPPT) is emerging as a new technology for power management controllers for small-scale wind turbines (SSWTs) thanks to its advantages in terms of operation flexibility, economy and system security. LPPT operates in such a way that power requested by the user can be extracted from the wind turbine while respecting constraints. However, operating in LPPT mode still requires a deep understanding to obtain a compromise between minimizing power oscillations and transient response. For that, three LPPT power control strategies for an SSWT intended to be integrated in a direct current (DC) urban microgrid are investigated. These methods concern perturb and observe (P&O) with fixed step size, P&O based on Newton’s method and P&O based on the fuzzy logic (FL) technique. The experimental results highlight that all methods function correctly and reach the limited power point (LPP). The FL method improves dynamic performances with more steady oscillations around LPP compared to fixed step size and Newton’s methods. The sudden variation of wind velocity and power lead us to conclude that the FL method ensures a good balance between reducing oscillation of wind turbine (WT) output power around the operating point and convergence of rising time toward LPP.

Decentralised coordinated energy management for hybrid AC/DC microgrid by using fuzzy control strategy

The islanded hybrid AC/DC microgrid consisting of battery energy storage (BES) systems, photovoltaic (PV) generators, and bidirectional power converter (BPC) possesses the advantages of flexibility and extendibility. To ensure the safety and stability of operation, the power of BES and BPC needs to be restrained within their designed limits regardless of the power fluctuation in the hybrid microgrid. Besides, the over-charge and over-discharge of BES should be prohibited. In this study, a decentralised generation-storage-subgrid coordination control for power management is proposed to assure the power limitation and state of charge (SOC) protection. In the control strategy of BES, a modified droop method is adopted to deliver the storage's both SOC and output power signals without communication links. Meanwhile, a fuzzy logic controller is adopted in BPC, which can prevent the overuse of BESs in both subgrids and limit the maximum output power of BPC. In addition, a modified P&O strategy is applied in PV systems as a supplement of overuse protection. Finally, the effectiveness of the proposed control strategy is verified on RT-Lab experimental platform.

Off-Grid System Configurations for Coordinated Control of Renewable Energy Sources

Configurations, coordinated controller design and applications of various off-grid systems with distributed energy resources (DERs) for an uninterrupted supply, are presented in this paper. The performances for the optimal operation of a diesel generator (DG) in the presence of nonlinear loads, fuel-savings, voltage and frequency regulation, a soft and secure transition among different operating modes, an optimization, and power management control, are validated through simulated results and test results on the prototype to demonstrate the suitability of these configurations with natural energy resources (NERs) for continuous development in remote as well as in isolated locations.

Low power consumption and reliability of wireless communication network in intelligent parking system

With the rapid increase in the number of vehicles in our country, parking and parking management are becoming more and more difficult. Use information technology to improve the use of parking spaces and improve the efficiency of parking management, it is an effective way to alleviate the parking problem. In 2015, the research on "Internet + parking" accelerated rapidly in China. And various intelligent parking system models are introduced. Firstly, the parking conditions at home and abroad are studied, and the existing parking systems are analyzed. It is found that the current parking system can hardly be used in public parking areas such as residential areas, roadside and square. In order to solve the core part of intelligent parking system in public parking IoT Low energy consumption parking space control. Using new detection technology, parking lock control technology, wireless sensor network technology, solar charging technology, power management technology. Parking space detection module, parking lock control module and wireless sensor network module and power control management module with additional solar charging are designed. There are three problems specifically for intelligent parking in public parking lots: parking detection and automatic control, low-energy wireless signal transmission, efficient power management, effectively improve the performance of intelligent parking system and reduce energy consumption. This paper uses advanced wireless technology to construct and design intelligent parking system. Through the research on the development and management characteristics and application examples of intelligent transportation in developed countries such as Europe and America, based on China's basic national conditions and advanced wireless communication technology, radio frequency technology and computer technology research, establish an integrated system. Finally, the performance and power consumption of the intelligent parking system are tested, to ensure the feasibility of the system, this kind of system has certain application value in the scenario of resource sharing and intelligent management of public parking spaces.

An integrated rule-based power management and dynamic feed-forward low voltage ride through scheme for a grid-connected hybrid energy system

Power generation from a grid-integrated renewable energy generator embedded with backup sources to form a hybrid energy system possesses convincing features of high efficiency and zero emissions. Control for felicitating apt power sharing and for providing ancillary services such as low voltage ride through (LVRT) is necessary for the compliance of grid codes. However, the simultaneous control coordination for meeting these control objectives is challenging due to the dynamic nature of renewable generators and utility grid. Hence, this paper proposes an integrated power management strategy (PMS) and LVRT control scheme for such systems. A wind energy conversion system backed up by a battery energy storage system, proton exchange fuel cell, and electrolyzer is considered in this work. A reduced rule-based power management control scheme is proposed for the considered system where the request made by the grid operator is kept in priority. Further, a dynamic current feed-forward based LVRT control scheme based on negative sequence current minimization is presented for the grid-interfaced inverter. The inverter control is coupled with an inherent mode selection capability between the grid feeding mode and LVRT mode in order to realize the proposed integrated control objectives. The validation of the proposed PMS and LVRT control is justified by detailing relevant mathematical control models and also by realizing practical case scenarios such as variable wind speed, load demand, grid power request, and occurrences of balanced and unbalanced voltage sag. The obtained simulation results show the cordial response of the system with the proposed control strategies.

Research on Deep Belief Network of Wind Power Control Management Unit Based on Attack Identification

With the continuous improvement of the level of economic development and the increasingly serious environmental problems, countries around the world are focusing more on renewable energy. Wind energy is an important category of renewable energy because of its advantages. However, wind power is very dependent on the climate environment. It operates in an open operating environment, and its communication depends on the network interaction method. With the proposal of the Internet of Everything, the power grid is developing in the direction of information and intelligence. There are more and more attacks, and the security and stability of wind power interface devices have been threatened. As the power grid involves many areas and households, once the power outage occurs, the economic losses will be huge and even cause major security accidents. This paper proposes a deep belief network research of wind power control management unit based on attack recognition to improve the safety and operational reliability of wind power generation.

Wave impact energy harvesting through water-dielectric triboelectrification with single-electrode triboelectric nanogenerators for battery-less systems

This paper evaluates the effect of water-dielectric interfaces for wave impact energy harvesting at low frequencies (0.7 Hz–3 Hz) on the output performance of Water-Dielectric Single Electrode Mode Triboelectric Nanogenerators (WDSE-TENG). The triboelectric effect is generated between water (with a net positive charge) and a hydrophobic dielectric layer (with a net negative charge). Different WDSE-TENG configurations were tested using distinct hydrophobic materials. The water-fluorinated ethylene propylene (FEP) combination resulted in the best output performance. On the contrary, an output performance reduction by a factor of 3.53 was measured with seawater-dielectric interfaces. This can be compensated by increasing the contact area, with the best performance obtained using silicone rubber compound (Acetoxy, Elastomer) utilizing a WDSE-TENG with two-dielectric layer configuration. Employing seawater as a triboelectric material, the highest electrical output power and power density of 79.18 mW and 0.344 mW/cm2 was generated with a grid of WDSE-TENG, comprising five devices connected in parallel. The output voltage, current, transferred charge, stored energy and energy conversion efficiency (ECE) values of the grid of connected WDSE-TENG devices were compared against a single device. Such energy harvesters were able to power an ultrasonic range sensor and a one-way wireless transmitter for motion detection, distance measurement, and monitoring weather conditions. The stored energy and generated power were ~5.96 mJ and ~5.18 mW, respectively. Furthermore, the integration of the grid of WDSE-TENG with a power management control circuit (PMCC) is able to increase the output power and hence offer the potential to power up electronic devices with power consumption requirements between 1 mW and 100 mW. The results demonstrate that the grid of WDSE-TENG offers an innovative energy harvesting approach using water as a triboelectric material. The device can be used as an energy source for smart battery-less wireless sensing systems at water-structure interfaces in aquaculture (e.g. for fish detection or water level measurement) and weather condition monitoring.