System-level Control Research Articles

Starch: A Flexible, Adaptable Carbon Store Coupled to Plant Growth.

Research in the past decade has uncovered new and surprising information about the pathways of starch synthesis and degradation. This includes the discovery of previously unsuspected protein families required both for processes and for the long-sought mechanism of initiation of starch granules. There is also growing recognition of the central role of leaf starch turnover in making carbon available for growth across the day-night cycle. Sophisticated systems-level control mechanisms involving the circadian clock set rates of nighttime starch mobilization that maintain a steady supply of carbon until dawn and modulate partitioning of photosynthate into starch in the light, optimizing the fraction of assimilated carbon that can be used for growth. These discoveries also uncover complexities: Results from experiments with Arabidopsis leaves in conventional controlled environments are not necessarily applicable to other organs or species or to growth in natural, fluctuating environments.

Research on restraining low voltage of distribution power network using STATCOM

In order to solve the problem of low voltage in distribution power network, this paper proposes a novel static synchronous compensator (STATCOM) based on modular multilevel converter. When the bus voltage of distribution power network changes rapidly, The MMC-STATCOM can quickly provide reactive voltage support and maintain the stability of bus voltage. Firstly, this paper introduces the operating principle of the MMC-STATCOM, and then propose three-level control strategies including device-level-, converter-level- and system level-control. Finally, based on the data of a power station in the distribution network, Simulation is carried out in the power system analysis and synthesis program (PSASP). The simulation results show that the MMC-STATCOM control function is reasonable and can respond quickly to the system reactive power change. It can effectively realize the voltage support and ensure the safe and stable operation of the power network.

Distributed OPF Algorithm for System-Level Control of Active Multi-Terminal DC Distribution Grids

This paper presents a distributed optimal power flow (OPF) algorithm for the system-level control of multi-terminal DC (MTDC) distribution grids with distributed energy resources (DER). At each control period, the algorithm updates the nominal voltage and power set-points of the DER-interfacing converters, which operate according to active network management (ANM) concepts. To achieve this, the OPF problem, in its nodal formulation, includes power dispatch strategies for diverse DER according to their technical characteristics, which change during the system operation. This multi-objective OPF-for-ANM problem is solved by distributed control units (DCUs) according to the distributed algorithm for the alternating direction method of multipliers (ADMM). All DCUs have identical roles in the distributed control structure and thus the distributed OPF-for-ANM algorithm is highly modular. Simulation results in different IEEE standard systems and various scenarios demonstrate that the algorithm is fast and scalable, irrespective of the number and location of integrated DER, as well as the operating condition of the system. The convergence speed of the algorithm is analysed considering the computation and communication time needed for its execution. The online application in a computers cluster demonstrates the fast execution of the developed algorithm in a physically-distributed implementation. Through the proposed OPF-for-ANM algorithm, the system-level control can dispatch fast diverse DER in different coordination approaches in a distributed manner.

System Level Modeling and Control Design of hTetrakis–A Polyiamond Inspired Self-Reconfigurable Floor Tiling Robot

Fixed morphology cleaning robots mostly face significant challenges in cleaning the narrow spaces in the environment. To overcome this, a new class of self-reconfigurable floor cleaning robot, hTetrakis, made of four triangular blocks, is built. This paper focuses on the modeling and controller design of the locomotion and reconfiguration mechanism of the platform. The locomotion of the platform with respect to the velocity of the wheels is formulated based on the kinematic analysis. By modeling the system in Simscape multibody toolbox of Matlab, the maneuverability of the platform is studied. The reconfiguration of the platform is studied based on the dynamics of individual block about the hinged joint. The control architecture of this platform has two distinct Proportional-Integral-Derivative (PID) controllers to eliminate the position error during reconfiguration, and to maintain the platform’s velocity. The coverage path planning of the platform is based on the classical Travelling Salesman Problem which finds the optimal sequence of waypoints as per the minimal energy consumption. Real time experiments are carried out to validate the effectiveness of the proposed control schemes in terms of eliminating the velocity errors, and maintaining the desired trajectory.

Optimal design of a nuclear power plant condenser control system based on multi-objective optimization algorithm

A condenser control system of a nuclear power plant consists of a pressure control system, a condensate water sub-cooling degree control system and a water level control system. The existing control optimization methods can hardly take into account all the performance indices of the three control systems at the same time. To solve this problem, this paper presents a control optimization method based on a multi-objective optimization algorithm. This method takes control parameters as optimization objects, and takes the performance of step response as optimization objectives. The multi-objective particle swarm optimization algorithm based on Pareto dominance concept is used to solve the optimization problem. This enables obtaining of high-quality control parameters. Simulation results confirm the feasibility and effectiveness of this control optimization method.

Reduced-order modeling and dynamic stability mechanism analysis of MTDC system in DC voltage control timescale

An equivalent source-load MTDC system including DC voltage control units, power control units and interconnected DC lines is considered in this paper, which can be regarded as a generic structure of low-voltage DC microgrids, mediumvoltage DC distribution systems or HVDC transmission systems with a common DC bus. A reduced-order model is proposed with a circuit structure of a resistor, inductor and capacitor in parallel for dynamic stability analysis of the system in DC voltage control timescale. The relationship between control parameters and physical parameters of the equivalent circuit can be found, which provides an intuitive insight into the physical meaning of control parameters. Employing this model, a second-order characteristic equation is further derived to investigate system dynamic stability mechanisms in an analytical approach. As a result, the system oscillation frequency and damping are characterized in a straight forward manner, and the role of electrical and control parameters and different system-level control strategies in system dynamic stability in DC voltage control timescale is defined. The effectiveness of the proposed reduced-order model and the correctness of the theoretical analysis are verified by simulation based on PSCAD/EMTDC and an experiment based on a hardware low-voltage MTDC system platform.

Heterogeneous Real-Time Co-Emulation for Communication-Enabled Global Control of AC/DC Grid Integrated With Renewable Energy

The information, and communication technologies (ICTs) are increasingly merging with the conventional power systems. For the design, and development of modern AC/DC grids with integrated renewable energy sources, the system-level control schemes with ICTs involved should be evaluated in a co-simulation framework. In this work, a heterogeneous hardware real-time co-emulator composed of FPGAs, many-core GPU, and multi-core CPU devices is proposed to study the communication-enabled global control schemes of hybrid AC/DC networks. The electromagnetic transient (EMT) power system emulation is conducted on the Xilinx FPGA boards to provide nearly continuous instantaneous waveforms for cyber layer sampling; the communication layer is simulated on the ARM CPU cores of the embedded NVIDIA Jetson platform for flexible computing, and programming;, and the control functions for modular multi-level converters are executed on GPU cores of the Jetson platform for parallel calculation. The data exchange between FPGAs, and Jetson is achieved via the PCI express interface, which simulates the sampling operation of the AC phasor measurement unit (PMU), and DC merging unit (DC-MU). The power overflow, and DC fault cases are investigated to demonstrate the validity, and effectiveness of the proposed co-emulation hardware architecture, and global control schemes.

Hierarchical and Droop Method for DC Micro-grid Bus Voltage under Isolated operation

Nowadays, distributed generation technology is of great help to the efficient utilization of new energy. If the distributed power supply is connected to the DC micro-grid, it will be more secure and reliable. Therefore, it is necessary to control the voltage stability of the DC bus and ensure the balance of the source charge power of system to ensure the power supply quality and safety of the DC micro-grid. There are two operation modes of DC micro-grid: connected operation and isolated operation, and isolated operation control is the foundation and key of system-level control of DC micro-grid. To solve the problem of bus voltage fluctuation in isolated dc micro-grid, this study proposes a voltage hierarchical-droop control strategy for DC micro-grid, which can effectively improve the stability of the DC bus voltage. Last, this study builds the simulation model of DC micro-grid in the MATLAB/Simulink platform to verify the validity and feasibility of the proposed control strategy.

Applying power margin tracking droop control to flexible operation of renewables generation multi-terminal DC collector system

An emerging multi-terminal looped dc (MTDC) collector system is now advocated for collecting and transferring large-scale renewables generation. However, it remains an open question as to improving the cooperative control capability of looped converter stations for flexible and robust response to renewable grid-connection fluctuation. This paper addresses this problem with a novel Power Margin Tracking (PMT) droop control and its corresponding system-level control strategy from the perspective of optimal dispatch of the power system. By introducing a power margin correction factor into the droop coefficient, the converter station can make self-adaptive regulation according to its actual available power margin. For operation verification, a multi-period optimal operation model and a four-terminal simulation model is built to provide optimal control parameters and real-time operation states of converter stations, where power flow model of the looped MTDC grid with renewables generation is considered. The cases results prove that the proposed control strategy can improve the cooperative operation capability of multiple converter stations, mitigating grid-connected power fluctuation. It can effectively reduce the dc voltage deviation to enhance the operation stability of MTDC grid. The operation robustness of the proposed control strategy under N-1 fault cases is verified as well.

IoT Applications in Wind Energy Conversion Systems

Abstract Renewable energy reliability has been the main agenda nowadays, where the internet of things (IoT) is a crucial research direction with a lot of opportunities for improvement and challenging work. Data obtained from IoT is converted into actionable information to improve wind turbine performance, driving wind energy cost down and reducing risk. However, the implementation in IoT is a challenging task because the wind turbine system level and component level need real-time control. So, this paper is dedicated to investigating wind resource assessment and lifetime estimation of wind power modules using IoT. To illustrate this issue, a model is built with sub-models of an aerodynamic rotor connected directly to a multi-pole variable speed permanent magnet synchronous generator (PMSG) with variable speed control, pitch angle control and full-scale converter connected to the grid. Besides, a large number of various sensors for measurement of wind parameters are integrated with IoT. Simulations are constructed with Matlab/Simulink and IoT ’Thingspeak’ Mathworks web service. IoT has proved to increase the reliability of measurement strategies, monitoring accuracy, and quality assurance.

Research on Controllable Information Network Framework

The current single, isolated network security technologies make it hard to deal with diversity, hidden network attacks, the existing network security architectures are facing various challenges. According to the network control theory, the basic closed-loop structure can be adopted to the network architecture, so that the whole network system can work in a stable and self-running form. The concepts of system-level feedback and component-level feedback are firstly proposed. The component-level feedback control loop includes security function units, and system-level feedback control loop mainly includes security controllers. Furthermore, the vertical expansion structure and the lateral expansion structure are proposed. Finally, a novel controllable information network framework is proposed, which combines multi-level feedback and coordinated control. This provides a novel way to solve the problem of network security and design the future network framework.

Thermal Stress Based Power Routing of Smart Transformer With CHB and DAB Converters

The smart transformer (ST) is a potential solution for an upgrade of the electric distribution grid, which enables to provide services to the grid and dc connectivity. However, the power electronics within the system are challenged by high reliability requirements. One possible solution to increase the reliability is to employ prognosis to predict the failures and avoid down times of the system. Traditional maintenance scheduling is based on the remaining useful lifetime (RUL) of the individual components or the forecasted failure probability. For a further increase of the time to the next maintenance, it is desired to have similar wear out of all components, which need to be maintained or exchanged. In this article, it is proposed to route the power internally in a modular power converter consisting of a cascaded H-bridge connected to dual active bridges in order to influence the RUL of its building blocks. Therefore, a thermal stress based wear-out control is designed for addressing the processed power dependent failures of the devices in the building blocks of the ST. Compared to the conventional power routing methods, the impact of the proposed system-level control considering electrical and thermal parameter variations is demonstrated using Monte Carlo analysis.

Human-interactive drone system remotely controlled by printed strain/pressure sensors consisting of carbon-based nanocomposites

We demonstrate human-interactive drone remote control system consisting of high-performance printed strain/pressure sensors with carbon-based nanocomposites, fabricated by all-solution-process at 80 °C. The armband-type drone remote control system was designed by a main control operation module, a sensing module and a signal processing module at an overall size of 12 cm × 7 cm x 1.5 cm (width x length x height). Rapid and accurate sensing properties of the sensing module were realized by the structural integration of nanocomposites on flexible/stretchable substrates attached to the human body. Furthermore, simultaneous visualization of processed data on the user's smartphone with an Android application by detecting the movements of human-body in real-time can open up new routes for the upcoming internet of things platform based on nanocomposition in industries. Notably, it is the feasible demonstration of a system-level drone remote controller operated by signal processing in real-time from highly sensitive printed strain/pressure sensors with carbon-based nanocomposites, exhibiting important functionality of waterproof and electric-isolation for human-interactive electronics.

Thermal Control Strategies for Reliable and Energy-Efficient Data Centers

Two self-developed control schemes, ON/OFF and supervisory control and data acquisition (SCADA), were applied on a hybrid evaporative and direct expansion (DX)-based model data center cooling system to assess the impact of controls on reliability and energy efficiency. These control schemes can be applied independently or collectively, thereby saving the energy spent on mechanical refrigeration by using airside economization and/or evaporative cooling. Various combinations of system-level controls and component-level controls are compared to a baseline no-controls case. The results show that reliability is consistently met by employing only sophisticated component-level controls. However, the recommended conditions are met approximately 50% of the simulated time by employing system-level controls only (i.e., SCADA) but with a reduction in data center cooling system power usage effectiveness (PUE) values from 3.76 to 1.42. Moreover, the recommended conditions are met at all averaged times with an even lower cooling system PUE of 1.13 by combining system-level controls only (SCADA and ON/OFF controls). Thus, the study introduces a simple method to compare control schemes for reliable and energy-efficient data center operation. The work also highlights a potential source of capital expenses and operating expenses savings for data center owners by switching from expensive built-in component-based controls to inexpensive, yet effective, system-based controls that can easily be imbedded into existing data center infrastructure systems management.

A Reconfigurable Solar Photovoltaic Grid-Tied Inverter Architecture for Enhanced Energy Access in Backup Power Applications

In this paper, a photovoltaic (PV) reconfigurable grid-tied inverter (RGTI) scheme is proposed. Unlike a conventional GTI that ceases operation during a power outage, the RGTI is designed to act as a regular GTI in the on-grid mode but it is reconfigured to function as a DC-DC charge-controller that continues operation during a grid outage. During this period, the RGTI is tied to the battery-bank of an external UPS based backup power system to augment it with solar power. Such an operation in off-grid mode without employing communication with the UPS is challenging, as the control of RGTI must not conflict with the battery management system of the UPS. The hardware and control design aspects of this requirement are discussed in this paper. A battery emulation control scheme is proposed for the RGTI that facilitates seamless functioning of the RGTI in parallel with the physical UPS battery to reduce its discharge current. A system-level control scheme for overall operation and power management is presented to handle the dynamic variations in solar irradiation and UPS loads during the day, such that the battery discharge burden is minimized. The design and operation of the proposed RGTI system are independent of the external UPS and can be integrated with an UPS supplied by any manufacturer. Experimental results on a 4~kVA hardware setup validate the proposed RGTI concept, its operation and control.

Synergistic substrate cofeeding stimulates reductive metabolism.

Advanced bioproduct synthesis via reductive metabolism requires coordinating carbons, ATP and reducing agents, which are generated with varying efficiencies depending on metabolic pathways. Substrate mixtures with direct access to multiple pathways may optimally satisfy these biosynthetic requirements. However, native regulation favouring preferential use precludes cells from co-metabolizing multiple substrates. Here we explore mixed substrate metabolism and tailor pathway usage to synergistically stimulate carbon reduction. By controlled cofeeding of superior ATP and NADPH generators as 'dopant' substrates to cells primarily using inferior substrates, we circumvent catabolite repression and drive synergy in two divergent organisms. Glucose doping in Moorella thermoacetica stimulates CO2 reduction (2.3 g gCDW-1 h-1) into acetate by augmenting ATP synthesis via pyruvate kinase. Gluconate doping in Yarrowia lipolytica accelerates acetate-driven lipogenesis (0.046 g gCDW-1 h-1) by obligatory NADPH synthesis through the pentose cycle. Together, synergistic cofeeding produces CO2-derived lipids with 38% energy yield and demonstrates the potential to convert CO2 into advanced bioproducts. This work advances the systems-level control of metabolic networks and CO2 use, the most pressing and difficult reduction challenge.

Decentralised resilient autonomous control architecture for dynamic microgrids

Microgrids serve as an integral part of future power distribution systems. Typically, microgrids are managed by centralised controllers. There are two major concerns about using a single centralised controller. The controller can become a performance and reliability bottleneck for the entire system, where its failure can bring the entire system down. Excessive communication delays can also degrade the system performance. As a solution, a true decentralised control architecture for microgrids is proposed, designed, developed, and tested here. Distributing the controls to local agents decreases the possibility of network congestion to occur. Decentralisation will also enhance the reliability of the system since the single point of failure is replaced by a distributed architecture. The proof-of-concept of true decentralisation of microgrid control architecture is implemented using Hardware-in-the-Loop Platform. Device level and system level controller and interaction models are defined for a self-coordination. Also, microgrid energy management system (EMS) and control case scenarios are demonstrated. The experimental results show the robustness of the proposed architecture.

Development of a Fuzzy-Logic-Based Energy Management System for a Multiport Multioperation Mode Residential Smart Microgrid

In this paper, a grid-tied residential smart microgrid topology is proposed, which integrates energies of a photo-voltaic (PV), a fuel cell, and a battery bank to supply the local loads through a combination of electric and magnetic buses. In contrast to multiple-converter-based microgrids with a common electric bus, using a multiport converter with a common magnetic bus can effectively reduce the number of voltage conversion stages, size, and cost of the renewable energy system and isolates the conversion ports. The resultant topology utilizes a centralized system level control that leads to a faster and more flexible energy management. The proposed microgrid is able to operate in multiple grid-connected and off-grid operation modes. A fuzzy controlled energy management unit (EMU) is designed to select the appropriate operation mode considering both real-time and long-term predicted data of the energy generation and consumption. A mode transition process is designed to smooth the mode variation by using a state transition diagram and bridging modes. To improve the microgrid operation performance, appropriate control techniques, such as synchronized bus-voltage balance, are used. A prototype of the proposed microgrid and the EMU are developed and experimentally tested for three different energy management scenarios. Energy distribution and energy cost analysis are performed for each scenario to validate the proposed control method.

Three-Step Switching Frequency Selection Criteria for the Generalized CLLC-Type DC Transformer in Hybrid AC–DC Microgrid

For hybrid ac–dc microgrids, the widely applied high-frequency dc transformer (DCT) is usually scheduled to operate at resonant frequency with 50% duty-cycle-based semiregulated control to ensure the power transmission (PT), improve its power-density, and simplify the system-level control. However, for a real DCT, it may exist more than one resonant frequency that exhibit totally different features, which may seriously degrade the PT ability if the inappropriate switching frequency is selected. Meanwhile, the actual values of the DCT inductances and capacitances are also changing with the power, temperature, etc., which may lead to the practical resonant frequency's variation. Thus, how to select the suitable switching frequency to guarantee the PT ability against the parameter variation becomes a challenge. In this paper, three-step switching frequency selection criteria (SFSC) are proposed. A generalized CLLC -type DCT (GCLLC-DCT) model is extracted to make the proposed approach available for the LLC -, CLL -, symmetric CLLC -, and asymmetric CLLC -type topologies. For convenience, the definition of the active power transmission ratio (APTR) is introduced to help evaluate the PT ability. First, the number, value, and impact variables of the resonant frequency are derived and analyzed in Step I as the preliminary. Afterward, the optimum resonant frequency is confirmed for the GCLLC-DCT as the criterion based on the APTR in Step II. At last, the criterion in Step III is given to finally determine the switching frequency against the parameter variations. The proposed SFSC method is also validated by the experiments.

Review of Differential Power Processing Converter Techniques for Photovoltaic Applications

Differential power processing (DPP) converters are utilized in photovoltaic (PV) power systems to achieve high-efficiency power output, even under uneven lighting or mismatched PV cell situations. Since this DPP concept has been introduced for PV systems, various topologies and control algorithms have been proposed and validated, showing the benefits of DPP converters systems over existing series string and full power processing converter solutions. However, DPP systems are highly coupled and can be challenging to control. Various architectures, topologies, and control strategies for both series and parallel DPP architectures are reviewed and compared. Tradeoffs of different DPP converters and topologies are discussed. Also, the power curve for the PV connected to bus, PV to PV, and PV to independent port series DPP architectures are evaluated in terms of inverter interaction. To date, the PV to PV series DPP systems have been most widely implemented and robust system-level control for all architectures has been a major research focus. Furthermore, research and development is still needed, particularly for commercialization and parallel DPP approaches for emerging PV applications.