An Adaptive Wireless Power Sharing Control for Multiterminal HVDC

Power sharing among multiterminal high voltage direct current terminals(MT-HVDC)is mainly developed based on a priority or sequential manners,which uses to prevent the problem of overloading due to a predefined controller coefficient.Furthermore,fixed power sharing control also suffers from an inability to identify power availability at a rectification station.There is a need for a controller that ensures an efficient power sharing among the MT-HVDC terminals,prevents the possibility of overloading,and utilizes the available power sharing.A new adaptive wireless control for active power sharing among multiterminal(MT-HVDC)systems,including power availability and power management policy,is proposed in this paper.The proposed control strategy solves these issues and,this proposed controller strategy is a generic method that can be applied for unlimited number of converter stations.The rational of this proposed controller is to increase the system reliability by avoiding the necessity of fast communication links.The test system in this paper consists of four converter stations based on three phase-two AC voltage levels.The proposed control strategy for a multiterminal HVDC system is conducted in the power systems computer aided design/electromagnetic transient design and control(PSCAD/EMTDC)simulation environment.The simulation results significantly show the flexibility and usefulness of the proposed power sharing control provided by the new adaptive wireless method.

ADMM-based Distributed Active and Reactive Power Control for Regional AC Power Grid with Wind Farms

A distributed active and reactive power control(DARPC)strategy based on the alternating direction method of multipliers(ADMM)is proposed for regional AC transmission system(TS)with wind farms(WFs).The proposed DARPC strategy optimizes the power distribution among the WFs to minimize the power losses of the AC TS while tracking the active power reference from the transmission system operator(TSO),and minimizes the voltage deviation of the buses inside the WF from the rated voltage as well as the power losses of the WF collection system.The optimal power flow(OPF)of the TS is relaxed by using the semidefinite programming(SDP)relaxation while the branch flow model is used to model the WF collection system.In the DARPC strategy,the large-scale strongly-coupled optimization problem is decomposed by using the ADMM,which is solved in the regional TS controller and WF controllers in parallel without loss of the global optimality.The boundary information is exchanged between the regional TS controller and WF controllers.Compared with the conventional OPF method of the TS with WFs,the optimality and accuracy of the system operation can be improved.Moreover,the proposed strategy efficiently reduces the computation burden of the TS controller and eliminates the need of a central controller.The protection of the information privacy can be enhanced.A modified IEEE 9-bus system with two WFs consisting of 64 wind turbines(WTs)is used to validate the proposed DARPC strategy.

PASSIVE-ACTIVE CONTROL OF A FLEXIBLE ISOLATION SYSTEM

Passive-active control of a flexible isolation system is investigated from the viewpoint of power flow. Dynamic transfer equations of the system are deduced based on a matrix method which uses mobility or impedance representations of three substructures: the source of vibration, the receiver and the mounting system which connects the source to the receiver. The cancellation of axial input forces to the receiver is considered as the active control strategy and its effects are discussed. The results of the study show that the strategy adopted herein can effectively reduce the power transmitted to the receiver.

Wireless Sensor Networks Based Control Strategies for the Enhancement of Reliability in Smart Grids

The rapid increase in the demand for electricity necessitates the power quality improvement for achieving better reliability in smart grids. Wireless Sensor Networks (WSN) is the proven technology for reliable monitoring. This paper proposes a system model for the development and implementation of WSN based communication system for the monitoring of distributed generation, loads and transmission lines in the electrical grid and a controller system for automated control on the electrical grid. This work also aims to reduce the carbon footprints by reducing the dependency of electrical grid through the enhancement of distributed generation and grid sharing for avoiding voltage rise problem. To achieve this, a smarter electrical grid has been developed for the validation of smart grid considering a generation substation, a transmission substation and a distributed generation with loads. The occurrence of power quality issue and voltage rise has been controlled by active power control strategy. The communication network and controller has been modeled and tested for the performance of monitoring system and data communication capability on smart grid.

Optimal Active Power Dispatching of Microgrid and Distribution Network Based on Model Predictive Control

First, a three-tier coordinated scheduling system consisting of a distribution network dispatch layer, a microgrid centralized control layer, and local control layer in the energy internet is proposed. The multi-time scale optimal scheduling of the microgrid based on Model Predictive Control（MPC） is then studied, and the optimized genetic algorithm and the microgrid multi-time rolling optimization strategy are used to optimize the datahead scheduling phase and the intra-day optimization phase. Next, based on the three-tier coordinated scheduling architecture, the operation loss model of the distribution network is solved using the improved branch current forward-generation method and the genetic algorithm. The optimal scheduling of the distribution network layer is then completed. Finally, the simulation examples are used to compare and verify the validity of the method.

Smart Boilers: Grid Support Services from Non-Critical Loads

The aim of this paper is to present the concept of a simple and cheap upgrade for electric water boilers, allowing them to provide power quality services to the distribution grid. The upgrade requires only minimum additional hardware and it is easily installable. “Smart Boilers”, as the upgraded boilers are named, perform precise active and reactive power control, but most significantly mitigate line current harmonics. Αctive and reactive power control is implemented by appropriate regulation of the modulation sinewave amplitude and phase, respectively. This type of control is easily customizable in order to accommodate a variety of power quality targets, depending on the required level of services and available grid monitoring equipment. The method used for line current harmonic compensation is based on the injection of mirror harmonics created at the modulation stage of the converter. It is indifferent of harmonic source: it is equally successful at mitigating harmonics caused by the power electronic converter of the Smart Boiler, other sources of current harmonics or loads. The achieved grid services are clearly beyond the “on/off” operation of electric boilers, currently implemented by Demand Side Management (DSM) in order to shift load away from peak hours. It has been demonstrated through simulations, that Smart Boilers can assist voltage regulation at terminal buses, compensate reactive power and suppress harmonic currents at lines.

Active Power Correction Strategies Based on Deep Reinforcement Learning Part I:A Simulation-driven Solution for Robustness

Employing the novel Deep Reinforcement Learning approach,this paper addresses the active power corrective control in modern power systems.Seeking to minimize the joint effect engendered by operation cost and blackout penalty,this correction strategy focuses on evaluating the robustness and adaptability aspects of the control agent.In Part I of this paper,where robustness is the primary focus,the agent is developed to handle unexpected incidents and guide the stable operation of power grids A Simulation-driven Graph Attention Reinforcement Learning method is proposed to perform robust active power corrective control.The aim of the graph attention networks is to determine the representation of power system states considering the topological features.Monte Carlo tree search is adopted to select the best suitable action set out of the large action space,including generator redispatch and topology control actions.Finally,driven by simulation,a guided training mechanism along with a long-short-term action deployment strategy are designed to help the agent better evaluate the action set while training and to operate more stably when deployed.The efficacy of the proposed method has been demonstrated in the“2020 I earning to Run a Power Network.Neurips Track 1”global competition and the associated cases.Part II of this paper deals with the adaptability case,where the agent is equipped to better adapt to a grid that has an increasing share of renewable energies through the years.

Recent advancement on technical requirements for grid integration of wind power

The installation of wind energy has experienced rapid development during recent years.As a result,the operation of power system can be greatly affected.Therefore,the operators of different countries have formulated the grid codes which reinforce technical requirements for wind power plants.In this paper,recent grid codes published in different countries have been carefully reviewed.The basic requirements of active power control and reactive power compensation,both of which have particular influence on wind power plants operation,are focused on.Based on this review,it is understood that with the increasing integration of wind energy,there is a worldwide trend to regulate the performance of wind power plants so that they can contribute to the stability and reliability of power system.

Rapid transaction to load variations of active filter supplied by PV system

This paper deals with the analysis and control of a photovoltaic （PV） system connected to the main supply through a Boost converter and shunt active filter supplied by a PV system providing continuous supply of nonlinear load in variation. A robust control of a PV system connected to the grid while feeding a variable nonlinear load is developed and highlighted. This development is based on the control of the Boost converter to extract the maximum power from the PV system using the Perturb and Observe （P and O） algorithm in the presence of temperature and illumination. The proposed modeling and control strategy provide power to the variable nonlinear load and facilitates the transfer of power from solar panel to the grid while improving the quality of energy （harmonic currents compensation, power factor compensation and dc bus voltage regulation）. Validation of the developed model and control strategy is conducted using power system simulator Sim-Power System Blockset Matlab/Simulink. To demonstrate the effectiveness of the shunt active filter to load changes, the method of instantaneous power （pq theory） is used to identify harmonic currents. The obtained results show an accurate extraction of harmonic currents and perfect compensation of both reactive power and harmonic currents with a lower THD and in accordance with the IEEE-519 standard.

Pulse Combustors - Performance and Control

Limited resources of fossil energy require the search for new energy conversion processes and the increase of the efficiency of power plants to ensure the energy household in the future. Basically, changing the combustion mode from steady to pulse combustion makes an enormous reduction of fuel consumption possible. Active control systems for pulse combustors installed into the inlet further improve the efficiency and extend the operating range considerably. The control algorithm including fuel rate- air rate -pressure characteristics and control strategies as well are presented.

A Possible Configuration with Motor-generator Pair for Renewable Energy Integration

High penetration rates of renewable energy will bring stability problems for the future power grid.One of the critical issues is lack of inertia.In this paper,a synchronous motor-generator pair(MGP)system is proposed as a possible solution for renewable energy integration to enhance inertia and improve grid stability.First,feasibility studies of MGP on inertia,damping,efficiency,and cost are presented.Second,an analytical model is established based on its rotor angle relation.An active power control scheme based on voltage phase difference between renewable energy source and grid is then proposed,and state equations of MGP are derived for small signal stability.Next,two experiments are designed and implemented to verify stable operation and active power regulation of the MGP system.A single-machine infinite bus system is tested to investigate small signal stability and frequency response of MGP.The results show that the MGP system has a solid base in physics and is a feasible solution for providing enough inertia and improving small signal performance in the power grid with high penetration of renewable energy.The paper concludes with a discussion on future research directions to gain a better understanding of MGP.

Key technologies and the implementation of wind,PV and storage co-generation monitoring system

The coordinated control of multiple-sources including wind,photovoltaic(PV)and storage brings new challenges to traditional dispatch and control technologies.This paper firstly introduces a framework of wind,PV and storage co-generation monitoring system.Then,key technologies of co-generation monitoring system including day-ahead optimal dispatching,active power coordinated control and reactive power and voltage control are proposed.The framework and the techniques described in this paper have been applied in the National Wind,Photovoltaic,Storage and Transmission Demonstration Project of China,and their validity have been tested and verified.

High-voltage Ride Through Strategy for DFIG Considering Converter Blocking of HVDC System

This paper presents a P-Q coordination based highvoltage ride through(HVRT) control strategy for doubly fed induction generators(DFIGs) based on a combined Q-V control and P-V de-loading control. The active/reactive power injection effect of DFIG on transient overvoltage is firstly analyzed and the reactive power capacity evaluation of DFIG considering its de-loading operation is then conducted. In the proposed strategy, the reactive power limit of DFIG can be flexibly extended during the transient process in coordination with its active power adjustment. As a result, the transient overvoltage caused by DC bipolar block can be effectively suppressed. Moreover, key outer loop parameters such as Q-V control coefficient and deloading coefficient can be determined based on the voltage level of point of common coupling(PCC) and the available power capacity of DFIG. Finally, case studies based on MATLAB/Simulink simulation are used to verify the effectiveness of the proposed control strategy.