Control Strategy For System Research Articles

Frequency Coordination Control Strategy for Large-Scale Wind Power Transmission Systems Based on Hybrid DC Transmission Technology with Deep Q Network Assistance

Wind power is currently the most mature representative of sustainable energy generation technology, which has been developed and utilized on a large scale worldwide. The random and fluctuating nature of wind power output poses a threat to the secure and stable operation of the system. Consequently, the transmission of wind power has garnered considerable attention as a crucial factor in mitigating the challenges associated with wind power integration. In this paper, an artificial-intelligence-aided frequency coordination control strategy applicable to wind power transmission systems based on hybrid DC transmission technology is proposed. The line commutated converter (LCC) station at the sending end implements the strategy of auxiliary frequency control (AFC) and automatic generation control (AGC) to cooperate with each other in order to assist the system frequency regulation. The AFC controller is designed based on the variable forgetting factor recursive least squares (VFF-RLS) algorithm for system identification. First, the VFF-RLS algorithm is used to identify the open-loop transfer function of the system. Then, the AFC controller is designed based on the root locus method to achieve precise control of the system frequency. The DC line power modulation quantity is introduced in the AGC to automatically track the active power fluctuation and frequency deviation of the system. The AGC utilizes the classical proportional-integral (PI) control. By selecting the integrated time absolute error (ITAE) performance index to construct the reward function, and using a deep Q-network (DQN) for controller parameter optimization, it achieves improved regulation performance for the AGC. The voltage source converter (VSC) station at the receiving end implements an adaptive DC voltage droop control (ADC)strategy. Finally, the effectiveness and robustness of the proposed frequency control strategy are verified through simulation experiments.

Short-Term Load Forecasting Method Based on Bidirectional Long Short-Term Memory Model with Stochastic Weight Averaging Algorithm

To accommodate the rapid development of the distribution network of China, it is essential to research load forecasting methods with higher accuracy and stronger generalization capabilities in order to optimize distribution system control strategies, ensure the efficient and reliable operation of the power system, and provide a stable power supply to users. In this paper, a short-term load forecasting method is proposed for low-voltage distribution substations based on the bidirectional long short-term memory (BiLSTM) model. First, principal component analysis (PCA) and the fuzzy C-means method based on a genetic algorithm (GA-FCM) are used to extract the main influencing factors and classify different types of user electricity consumption behaviors. Then, the BiLSTM forecasting model utilizing the stochastic weight averaging (SWA) algorithm to enhance generalization capability is constructed. Finally, the load data from a low-voltage distribution substation in China over recent years are selected as a case study. Compared with conventional LSTM and BiLSTM prediction models, the annual electricity load curves for various user types forecasted by the PCA-BiLSTM model are more closely aligned with actual data curves. The proposed BiLSTM forecasting model exhibits higher accuracy and can forecast user electricity consumption data that more accurately reflect real-life usage.

A Systematic Literature Review on AC Microgrids

The objective of this work is to analyze and compare AC microgrid (ACMG) solutions to introduce the topic to new researchers. The methodology used to achieve this goal is a systematic literature review using five questions: (1) How have ACMGs evolved in five years? (2) What are the standards for ACMGs? (3) What are the different schemes for connecting MGs to the utility grid? (4) What are the different control schemes in ACMGs? (5) What is an appropriate way to compare results when working with ACMGs? The articles were published in Q1/Q2 journals as based on either the Scimago Journal Rank (SJR) and/or the Journal Citation Report (JCR) between 2018 and 2022 and were from three databases: (1) Web of Science (WoS), (2) Scopus, and (3) IEEE Xplore. Publications not describing pure ACMGs, review papers, publications not related to the questions, and papers describing work that did not meet a quality assessment were excluded, resulting in 34 articles being included in this review. Results show: (1) the energy sources and AC bus nature of microgrids over five years, (2) the identification and quantification of cited standards for microgrids, (3) the pros and cons of different schemes for connecting an AC microgrid to the main grid, (4) the control schemes, classified in a hierarchical control structure, and (5) the simulation tools and experimental benches used in microgrids. Most studies considered a generic energy source and a low-voltage three-phase AC bus, 16 standards were found, and the most cited standard was IEEE Standard 1547. The most common connection scheme to the utility grid was a direct connection, most of the works proposed a modification to a hierarchical control system scheme, and the most common simulation tool was MATLAB. The preferred experimental setup consisted of parallel inverters for testing a control scheme, a prototype when proposing a power electronic system, and a laboratory microgrid for testing fault detection methods.

Experimental study on dynamic characteristics of organic Rankine cycle coupled vapor compression refrigeration system with a zeotropic mixture

The organic Rankine cycle coupled vapor compression refrigeration system is an attractive refrigeration technology that converts low-grade thermal energy into cooling capacity to improve waste heat utilization efficiency. Due to the inevitable change in ambient temperature and cooling demand, the dynamic characteristics of the combined system are worth studying. In this paper, a small experimental apparatus with a common condenser is designed and developed. The dynamic characteristic experiments under different disturbances are carried out to understand the response characteristics of operating parameters and the variation of system performance. The results show that the maximum response time of the system under different disturbances ranges from 493 s to 694 s. The impact of throttle opening on the response characteristics of refrigeration subsystem parameters is significantly higher than that of the organic Rankine cycle. The mass flow rate of organic Rankine cycle has the fastest response to pump frequency, while the compressor inlet temperature changes rapidly with the cooling water temperature. Under a step cooling water temperature, it is important to control the compressor inlet temperature to avoid liquid droplets in its inlet. In addition, the mass flow rate of organic Rankine cycle should be controlled reasonably to achieve the maximum coefficient of system performance. The cooling capacity of the system is mainly affected by the cooling water temperature and the throttle valve opening. During the experiment, the maximum cooling capacity and performance coefficient of the system are 3.75 kW and 0.275, respectively. This work can provide guidance for the design of the control strategy of the combined system.

Detection of minimal extended driver nodes in energetic costs reduction.

Structures of complex networks are fundamental to system dynamics, where node state and connectivity patterns determine the cost of a control system, a key aspect in unraveling complexity. However, minimizing the energy required to control a system with the fewest input nodes remains an open problem. This study investigates the relationship between the structure of closed-connected function modules and control energy. We discovered that small structural adjustments, such as adding a few extended driver nodes, can significantly reduce control energy. Thus, we propose MInimal extended driver nodes in Energetic costs Reduction (MIER). Next, we transform the detection of MIER into a multi-objective optimization problem and choose an NSGA-II algorithm to solve it. Compared with the baseline methods, NSGA-II can approximate the optimal solution to the greatest extent. Through experiments using synthetic and real data, we validate that MIER can exponentially decrease control energy. Furthermore, random perturbation tests confirm the stability of MIER. Subsequently, we applied MIER to three representative scenarios: regulation of differential expression genes affected by cancer mutations in the human protein-protein interaction network, trade relations among developed countries in the world trade network, and regulation of body-wall muscle cells by motor neurons in Caenorhabditis elegans nervous network. The results reveal that the involvement of MIER significantly reduces control energy required for these original modules from a topological perspective. Additionally, MIER nodes enhance functionality, supplement key nodes, and uncover potential mechanisms. Overall, our work provides practical computational tools for understanding and presenting control strategies in biological, social, and neural systems.

Optimization of such strategy as frequency modulation for grid-side energy storage control-terminal in response to frequency fluctuations in the new power system grid

Abstract This paper focuses on the refinement of the control strategy for grid-side energy storage systems as they engage in primary and secondary frequency modulation within an emerging smart grid. To attain an optimal outcome, traditional frequency modulation methods, which often require high-precision operations and extended adjustment periods, fall short of the stringent demands posed by modern power systems for swift and responsive frequency modulation. Under such circumstances, the grid-side energy storage control-terminal system presents a viable solution for managing energy storage, thereby providing rapid and precise assistance to the power system’s frequency modulation. By implementing a control mechanism that can adaptively switch between ARR signal-based and ACE signal-based frequency adjustments, a segmented parallel control approach ensures that the energy storage system can promptly and effectively modify the power within the grid system, facilitating swift frequency modulation.

Energy Consumption Optimization for the Cold Source System of a Hospital in Shanghai - Part II: Operation Control Strategy Using EnergyPlus

Background: Energy consumption is a common problem in hospital buildings, which consume twice that of other public buildings. Therefore, it is of great significance to study the control strategy for the efficient operation of the cold source system. Objective: The study aimed to explore an efficient operation control strategy for cold source system, and new technologies and patents have emerged for the same. This work, utilizing EnergyPlus, modelled and analyzed the cold source system in a Shanghai hospital to optimize its operation. Methods: The accuracy of the simulation was verified by comparing it with experimental data. Based on the simulation results, the factors influencing the energy efficiency of the cold source system were analyzed, and then the operation control strategy of the cold source system was obtained. The XGBoost was used to fit the simulation results, and the operation strategy under full operating conditions was obtained. Results: The simulated results indicated the average energy saving rates during the summer season of the chillers, the chilled water pumps, the cooling water pumps, and the cooling towers to be 6.5%, -4.0%, 38.3%, and 5.4%, respectively, under the optimal operation control strategy. The average system Coefficient of Performance (COP) of the cold source system was 5.9, and the total energy consumption was 957016.3 kW·h, which was 7.1 % energy saving compared to that under the original operation. Conclusion: The conclusions of this study could provide references for the hospital buildings’ cold source system and group control method. This study has important practical significance for the efficient control strategy of cold source systems.

Characterization and verification of the optimal feedback gain of a satellite magnetorquer-based attitude control system

In spacecraft mission planning and operation, the attitude determination and control subsystem (ADCS) of a satellite provides information about the orientation of the satellite in the inertial reference frame. Furthermore, this subsystem produces the control actions required to adjust the orientation of the satellite, especially in the low-Earth orbit (LEO) regime. This paper focuses on the satellite’s three-axis attitude control problem within the context of active and passive control, which includes detumbling control, pointing control, magnetic control, and attitude stabilization after solar panel wing deployment using magnetorquers as the primary actuators. The objective is to stabilize and reduce the angular rate while orienting the satellite to the desired attitude. The proposed satellite attitude control system (ACS) strategies are designed, developed, characterized, and verified. These strategies encompass the B-dot control algorithm for detumbling control along with pointing control and attitude stabilization after solar panel wing deployment. hardware-in-the-loop simulation (HiLs) tests are conducted to assess the performance of the satellite magnetorquer-based ACS in the presence of noise. These tests involve a relative Earth’s magnetic field (EMF) generator in conjunction with SGP-4-based satellite orbital propagator high-level control software. Additionally, cascade proportional-integral-derivative (PID) and state-dependent Riccati equation (SDRE) controllers are implemented to generate sufficient torque using three-axis magnetorquers on a frictionless air-bearing platform. The platform is balanced to closely simulate the dynamic motion of a spacecraft in space. The testing includes a single initial condition and three inertia conditions for stabilization after solar panel wing deployment. Finally, the effectiveness of the cosimulation as a primary experiment through an integrated HiLs process is validated. This comprehensive approach confirms the control system’s performance and its ability to meet mission requirements.

Optimizing virtual energy sharing in renewable energy communities of residential users for incentives maximization

Renewable energy communities (RECs) are considered a promising tool for putting the citizens at the center of the energy transition, while also promoting self-sufficiency coming from local resources and decarbonization through high penetration of renewables. A key challenge when operating RECs is represented by the number of decision variables to consider depending on the number and type of community participants and distributed technologies, while also considering the associated uncertainties. Moreover, the monetarization of energy shared in the community for benefitting residential users is crucial. The contribution of this paper is to present an innovative stochastic linear programming model for optimizing the energy sharing in RECs to maximize revenues associated with the incentives for the energy shared as established by the Italian regulation. The REC under study consists of a condominium with a PV plant installed on the rooftop, and air conditioning and battery storage systems installed in each apartment. The problem is to find the optimal control strategies for air conditioning systems and batteries with a 15-minute time-step, which maximize the expected revenue from energy sharing while meeting the users’ comfort requirements and preventing users’ bills from increasing. Numerical results demonstrate the effectiveness of the optimization model to maximize the energy shared and the related revenues through the optimal control of installed assets. The combined optimized strategies of both air conditioning and batteries allow for finding the best performance of the REC in terms of maximization of the energy shared. In this latter case, the expected total revenue for users for the energy sharing increases by 59.7 %, 38.7 % and 12.6 % as compared to the baseline case with no optimal control, the case with control of air conditioning only, and the case with control of batteries only, respectively.

A wild horse-assisted decentralized control strategy for a PV-battery energy storage system in a DC microgrid

A wild horse-assisted decentralized control strategy for a PV-battery energy storage system in a DC microgrid

Mortality Surveillance for the COVID-19 Pandemic: Review of the Centers for Disease Control and Prevention's Multiple System Strategy.

Mortality surveillance systems can have limitations, including reporting delays, incomplete reporting, missing data, and insufficient detail on important risk or sociodemographic factors that can impact the accuracy of estimates of current trends, disease severity, and related disparities across subpopulations. The Centers for Disease Control and Prevention used multiple data systems during the COVID-19 emergency response-line-level case‒death surveillance, aggregate death surveillance, and the National Vital Statistics System-to collectively provide more comprehensive and timely information on COVID-19‒associated mortality necessary for informed decisions. This article will review in detail the line-level, aggregate, and National Vital Statistics System surveillance systems and the purpose and use of each. This retrospective review of the hybrid surveillance systems strategy may serve as an example for adaptive informational approaches needed over the course of future public health emergencies. (Am J Public Health. Published online ahead of print July 25, 2024:e1-e10. https://doi.org/10.2105/AJPH.2024.307743).

AC fault ride-through control strategy of MMC-UHVDC system with hierarchical connection mode

The ultra-high voltage direct current (UHVDC) transmission composed of modular multilevel converters (MMC) is an important technology for large-scale centralized transmission of renewable energy. In UHVDC system, temporary faults in the AC power grid system are a high probability fault, and the fault control strategy affects the safety and reliability of system operation. This paper studies on the condition of AC power grid faults occurring at the receiving converter station. Firstly, study the system characteristics after the occurrence of AC faults, and use theoretical analysis to derive the trend of DC voltage changes of each converter valve. Then, an AC fault ride-through control strategy with high power transmission capability is proposed with hierarchical connection structure, the strategy controls the system to synchronously reduce DC voltage and AC active power after a fault, maximizing the retention of the system’s transmission capacity during the occurrence of faults, thereby reduce power shock in the system. Finally, a simulation model of the dual ended system has built based on the PSCAD simulation platform. The simulation results show that when a single-phase ground fault and a three-phase ground fault occur in the high valve group at the receiving station, the system can retain about 83% and 50% of the transmission capacity during the fault period, respectively. Meanwhile, there is no serious overvoltage or overcurrent phenomenon in the system. The simulation results verified the effectiveness of the proposed control strategy.

Hybrid optimized evolutionary control strategy for microgrid power system

Hybrid optimized evolutionary control strategy for microgrid power system

Pemberdayaan Masyarakat Melalui Sistem Pemasaran Warkop Kopi Kampus (KOKAM) di Universitas Muhammadiyah Parepare

The purpose of this service is to find out how and how much influence the use of the management control system (SPM) and marketing strategies implemented at the Campus Coffee Shop has to improve quality so that it can survive in the competition of similar coffee shop businesses. Marketing development strategy for campus coffee shops (KOKAM). Several approaches that can help coffee shops around campus increase their attractiveness and business success include understanding the target market, strong branding, menu variations, special promotions for students, collaboration with student organizations, a comfortable and instagrammable atmosphere, promotions on Social Media. Conclusion Warkop campus coffee (KOKAM) is growing and attracting more customers, prioritizing the quality of the products sold, warkop is a comfortable place with affordable coffee prices with the aroma and taste of coffee being the main attraction, by creating a variety of different coffee flavors, take advantage of social media platforms to introducing warkop.

Study on thermal control decoupling and pre-regulating enhancement of battery direct cooling integrated thermal management system

The battery direct cooling thermal management system (TMS) is affected in its application due to the coupling interference with the air conditioner system. In this paper, decoupling of both refrigeration and control is realized through the design of structure and control method. The results show that the refrigeration decoupling make TMS is able to realize the regulation on the cooling capacity of the two branches, and control decoupling make TMS achieved better performance, and saved about 54.81 % of the energy consumption under the defined dirving cycle. Next, to mitigate the negative impact of large thermal inertia on the TMS, this paper designs a Pre-regulating framework in the background of the continuous development of vehicle informatization, while through the analyze on the effects and characteristics of control components and intervention times, achieved performance enhancement using the multi-component coordinated control. Based on the Pre-regulating framework and its performance enhancement, an overall system control strategy was designed and validated. The results show that the designed control strategy is able to reduce the battery temperature rise and the cabin temperature fluctuation by 81.7%–86.9 % and 2.84%–4.29 % with 2.22%–3.08 % energy efficiency improvement.

Study of Low-Temperature Energy Consumption Optimization of Battery Electric Vehicle Air Conditioning Systems Considering Blower Efficiency

Battery electric vehicle (BEV) air conditioning systems often use positive temperature coefficient (PTC) heaters to heat the passenger compartment. The heating process consumes a lot of energy in low-temperature environments, which seriously affects the driving range and user experience. This study aims to reduce the low-temperature energy consumption of the air conditioning system and improve energy efficiency through an innovative optimization method. In this study, the energy consumption composition of the air conditioning system was analyzed, and the goal of minimizing the sum of the total power consumption of the PTC heater and the blower was determined, while the efficiency characteristic of the blower was considered at the same time. The relationship between the average temperature of the passenger compartment measurement points and the PTC power and airflow rate was studied by combining experiments and numerical simulations, and the alternative operating conditions that met the temperature requirement were determined. On this basis, the total power consumption of the air conditioning system was analyzed and optimized. The results show that PTC power, airflow rate, and blower efficiency all have an important influence on the total power consumption of the air conditioning system. The optimized scheme could reduce the theoretical total power from 1315.32 W of the original scheme to 1246.83 W, and the actual total power from 1350.05 W of the original scheme to 1326.56 W, with reductions of 5.21% and 1.74%, respectively. The low-temperature energy consumption optimization method for the BEV air conditioning systems proposed in this study is instructive for the selection of blowers and the design of control strategies for air conditioning systems.

Load Frequency Control Strategy of Interconnected Power System Based on Tube DMPC

Solar thermal power generation shares technical characteristics with traditional thermal power generation. This enables rapid adjustment of turbine generator output to meet the demands of the power grid load for frequency modulation. However, fluctuations in light intensity lead to variations in interconnected power system parameters, posing challenges for load frequency control (LFC). In this study, we propose a Robust Distributed Model Predictive Control (RDMPC) method. This method achieves system trajectory tracking by solving the nominal system optimization problem. It also flexibly adjusts the weights of different Tube models to determine the optimal control law using the standard Tube online combination with various gain values. Additionally, we incorporate the states of adjacent areas into the feedback control law to achieve effective coordination between these areas. Using MATLAB/Simulink, we simulated the power system in two areas. Compared to standard Tube DMPC, our proposed algorithm effectively mitigates the impact of light intensity, enhances adjustment speed, reduces frequency fluctuation, and demonstrates superior control effectiveness.

Energy management in gyms microgrid: Nonlinear control of stationary bikes and treadmills with parallel rectifiers and AC/DC conversion

This article presents the complete design of a nonlinear control system for multiple stationary bikes connected to a mechanical energy conversion system equipped with squirrel cage induction generators (SIGs) linked to AC/DC converters. The primary objective of this study is to investigate the feasibility of powering multiple treadmills using the DC bus via DC/AC converters. The novelty of our approach lies in the integration of a new strategy of control system to achieve multiple control objectives within a gym microgrid environment, and an energy management algorithm to ensure the energy flow between intermittent generation and the considered, somewhat random, demand. The system is composed of several subsystems: i) stationary bikes connected to the DC bus via inverters acting as intermittent power sources; ii) a Li-ion battery-based energy storage system interfaced through a Buck-Boost converter; iii) electromechanical loads, including treadmills, powered by DC/AC converters, in addition to other DC loads. The main control objectives are as follows: a) each stationary bike extracts energy from the DC network by regulating the torque applied by the athlete, ensuring that the torque follows the reference torque; b) the treadmill’s speed must follow the reference generated based on the athlete’s condition; c) ensuring the protection of the energy storage system by monitoring its current and voltage; d) all mentioned objectives are achieved while maintaining the DC bus voltage at a reference value. To achieve these objectives, a nonlinear control approach based on Lyapunov theory is used to design the controllers. A formal analysis is conducted to assess the performance of the studied system. The system’s performance is demonstrated using the MATLAB/Simulink environment. Numerous simulations demonstrate that every control objective is achieved. Specifically, the system maintained the DC bus voltage at 500 V with a maximum deviation of 1 V, and the treadmill speed followed the reference within a margin of 0.1 m/s.

Biodegradability index (BDI) as an indicator for effluents quality measurement; a case study based on different industry sectors in Matara District, Sri Lanka

ABSTRACT This study addresses the crucial need for appropriate indicators to characterize aquatic pollution, given the challenges posed by unrestricted effluent discharge globally. Focusing on wastewater from hotel and tourism industries and vehicle service stations in Matara District, Sri Lanka, we explored the relationship between biological oxygen demand (BOD) and chemical oxygen demand (COD) through the biodegradability index (BDI). Monthly water samples were collected from January 2019 to December 2022, analyzed using standard methods, and statistically evaluated. Results revealed a significant spatial variation in BDI among industry sites, with a modest temporal change. The BOD:COD ratio exhibited a slight increasing trend over time, suggesting factors beyond temporal influence. BDI correlated significantly with temperature, alkalinity, and total suspended solids (TSS), emphasizing its potential as an indicator. The study underscores the importance of complementing the BOD:COD ratio with other indicators for a comprehensive assessment of industrial effluent quality. This research contributes valuable insights into understanding wastewater characteristics, facilitating informed pollution reduction and control strategies in aquatic systems.

Control Strategy of Flywheel Energy Storage System for Improved Model Reference Adaptive System Based on Tent-Sparrow Search Algorithm

This study addresses speed sensor aging and electrical parameter variations caused by prolonged operation and environmental factors in flywheel energy storage systems (FESSs). A model reference adaptive system (MRAS) flywheel speed observer with parameter identification capabilities is proposed to replace traditional speed sensors. The proposed method uses reference and adjustable models to identify the stator resistance and permanent magnet flux (PM Flux) to mitigate the adverse effects of electrical parameter changes on control performance. The Tent chaotic mapping-improved Sparrow Search Algorithm (SSA) optimizes the Proportional-Integral (PI) controller parameters for the dual closed-loop and MRAS speed adaptation laws of the flywheel motor. Moreover, a self-switching parameter identification (SSPI) scheme, which constructs a cost function based on the current, parameter identification, and speed errors, is proposed to prevent inaccuracies in parameter identification. The MRAS observer selects the appropriate PI adaptive mechanism based on the error values, thereby enhancing identification accuracy. Simulink simulations show significant improvements in the rapidity and accuracy of the Tent-SSA optimized MRAS flywheel speed observer, enhancing the stability and robustness of the flywheel rotor. Experimental validation on a constructed FESS platform confirms the feasibility of this method.