Load Control Strategy Research Articles

Integration of a solid oxide electrolysis system with solar thermal and electrical energy: A testing campaign for operation and control strategy definition

AbstractThe EU project PROMETEO has the scope of testing a 25 kW solid oxide electrolysis system integrated with a concentrated solar power plant via thermal energy storage in a relevant environment. Given the plant layout and the hydrogen demand characteristics, this work aims to identify how to operate the system effectively when renewable electricity is unavailable and how to modulate the load during hydrogen generation, thus defining the system's operation modes and control strategy. A 5 kWe stack has been tested at the FBK facility. The hot standby tests show that feeding a reducing gas at the negative electrode and air at the positive electrode, without polarizing the stack, effectively keeps the stack hot at 750°C and prevents degradation. Conversely, the electric protection approach leads to significant stack degradation (15% voltage drop in 200 h for one cluster). Regarding modulation of hydrogen generation, with low steam flowrates, the stack current and the flow rate of produced hydrogen mainly depend on the steam flow rate, while it is not affected by the stack temperature; conversely, with high steam flowrates, the current depends only on the stack temperature (from 25 A at 670°C to 65 A at 760°C). Based on the results, two hot standby modes and two load control strategies to be implemented and tested in the PROMETEO prototype are proposed.

Part-load performance analysis of a modular biomass boiler with a combined heat and power industrial Rankine cycle and supplementary sCO2 Brayton cycle

Abstract The addition of a supplementary high efficiency cycle integrated with an existing steam power cycle may increase energy efficiency and net generation. In this paper, part load performance and operation of a modular biomass boiler with an existing industrial Rankine steam heat and power cycle and supplementary supercritical CO2 (sCO2) Brayton cycle is analysed. The aim is to leverage the high efficiency of the sCO2 cycle by retrofitting sCO2 heaters in the existing biomass boiler, increasing net power output and thermal efficiency. With nominal load performance previously investigated, understanding part-load performance and operation is vital to determine cycle feasibility. A quasi-steady-state one dimensional thermofluid network model was used to simulate the integrated cycle performance for loads ranging from 100% to 60%. The model solves the mass, energy, momentum, and species balance equations, capturing detailed component characteristics. Two control methodologies are explored for the sCO2 Brayton cycle, namely inventory control and inventory control combined with throttling valve control. Inventory control is selected as the better performing control strategy for load following, maintaining high thermal efficiency across partial loads. At 60% load, the sCO2 compressor operates near the pseudo-critical point, leading to a sharp decrease in sCO2 cycle capacity, which requires careful management of inventory control. Two sCO2 heater configurations are investigated, namely a single convective-dominant heater, and a dual heater configuration with a radiative and a convective heater. The single heater configuration is preferred to minimise adverse impacts on the Rankine cycle superheaters.

A review of the application development and key technologies of rotary engines under the background of carbon neutrality

Rotary engines possess advantages such as light weight, high power density, and strong fuel adaptability, which are essential for powertrain systems. They hold great potential in the field of power machinery. However, the development of rotary engines has been constrained by increasingly stringent emission regulations. Despite this, numerous scholars and institutions continue to optimize rotary engines, leading to a proliferation of related research. It is necessary to synthesize these findings to guide future promotion and application efforts. This review examines the current applications and development status of rotary engines globally. It summarizes the development of key technologies such as sealing techniques, rotor configurations, and ignition devices, which have achieved lower energy consumption and emissions. The suitability of rotary engines for automotive and unmanned aerial vehicle applications has also been reported. To further reduce carbon emissions, researchers have explored zero-carbon fuel rotary engines. Hydrogen-fueled rotary engines have demonstrated higher combustion efficiency. By integrating EGR, load control strategies, and ignition system layouts, they have addressed issues such as NOx emissions, knock, and leakage. The development of ammonia-hydrogen hybrid fuels is also a potential effective solution. Continuous innovative research indicates that, with their inherent advantages and the integration of alternative fuels and advanced ignition technologies, rotary engines have the potential to meet future energy and environmental requirements. This positions them as strong contenders in future diversified power systems.

A novel boiler partial flow arrangement and partial load control strategies of a S-CO2 coal-fired power generation system

This work aims to address the technical issue of continuously decreasing reheat temperature in the S-CO2 coal-fired power system under partial-load operation. A novel partial flow arrangement of heating surfaces that uses part of the cooling walls in the furnace chamber as reheating surfaces was proposed. The steady-state model of a 300 MW S-CO2 coal-fired power system was developed to predict the partial-load operating characteristics. It is found that the proposed partial flow arrangement can effectively alleviate reheat temperature deviation. For the deviation of 10 °C, the present boiler operating load can be reduced to as low as 40 % whereas at least an 80 % load ratio for the traditional arrangement. According to the effects of four regulation measures, the comprehensive control sequence is suggested as 1) flue gas damper angle, 2) split ratio of the stream to FGC, 3) burner angle, and 4) split ratio of the stream to recompressor. This strategy can stabilize the reheat temperature at 620 °C for the load ratio decreasing from 100 % to 37 %, and achieve the higher system thermal efficiency. For load ratios from 37 % to 20 %, the reheat temperature cannot remain stable, and adjusting the reheat temperature will decrease the thermal efficiency.

Demand response strategies for air-conditioning systems based on direct load control: Considering envelope structures

In recent years, the surge in rural air-conditioning (AC) electricity consumption has led to an overall increase in peak loads in both winter and summer, presenting a major challenge to the reliability and stability of low-voltage distribution networks. Demand response (DR) strategy not only relieves the peak load, but also reduces the energy consumption and achieves the purpose of energy saving and emission reduction. Among the many DR strategies, direct load control (DLC) stands out as an effective way to quickly reduce building AC loads. Meanwhile, the building envelope is also one of the important factors affecting the AC load. A typical rural house in the Xi’an area of Shaanxi Province was used as a case study. A ground source heat pump system was developed, installed and used as an experimental platform in order to aid the study. Therefore, in this study, the combination of external envelope and DLC strategies was investigated to establish a simulation model of energy consumption in rural building complexes. Two DLC load control strategies were implemented under different external envelope conditions for annual AC energy simulation. The results show that the thickness of the external insulation layer has the greatest impact on the AC load of the building compared to the window-wall ratio and orientation. With a thickness of 0 mm–75 mm insulation, the DCCM strategy can effectively reduce AC energy consumption by 16%–18%; With a thickness of 0 mm–75 mm insulation, the TSCM strategy can effectively reduce AC energy consumption by 5%–8%.

Optimization scheduling of microgrid comprehensive demand response load considering user satisfaction

The original load control model of microgrid based on demand response lacks the factors of incentive demand response, the overall satisfaction of users is low, the degree of demand response is low, the Time Of Use (TOU) price of peak-valley filling capacity is weak, and the peak-valley difference of load curve is large. Regarding the limitations of the current microgrid demand response model, this study further optimizes the flexible load control strategy and proposes a two-objective optimization model based on price and incentive. Meanwhile, the model is solved using an improved chaotic particle group algorithm. Finally, the microgrid load data were selected for simulation analysis. The simulation results showed that the comprehensive demand response of flexible control model proposed increased the overall satisfaction of users by 9.51%, the overall operating cost of microgrid suppliers decreased by 12.975/ten thousand yuan, the peak valley difference decreased by 4.61%, and the user demand response increased by 27.24%. The model effectively improves the overall profit of the supply side of the microgrid, improves the user satisfaction, and maximizes the linkage benefits of the supply and demand of the micro grid. In addition, the model effectively reduces the phenomenon of distributed power supply in the microgrid, and realizes the supply and demand matching of the whole load in the microgrid.

Enhancing the performance of syngas-diesel dual-fuel engines by optimizing injection regimes: From comparative analysis to control strategy proposal

This study introduced an innovative technology of syngas direct injection through the twinning injector system. This technology can simultaneously adjust the equivalence ratio and the mass of fresh gas, for a syngas-diesel dual-fuel engine converted from a conventional diesel engine. The current work was carried out in two stages, in which the evaluation of engine performance and mixture formation under two various syngas injection strategies such as the port-premixed mixture method and the direct injection method were examined in the first stage. In the second stage, the load control strategy of the syngas-diesel dual-fuel engine, which aims to attain low greenhouse gas emissions and maintain output power, was thoroughly presented. The results revealed that the syngas direct-injection strategy significantly influences the power derating of the dual-fuel engine at a fixed pilot diesel injection. Indeed, when the stop injection angle was held constant at 270°CA, the power derating of the dual-fuel engine increased from 3.78 % to 22.74 % as the start injection angle was increased from 60 °CA to 100°CA, implying that this injection strategy could be suitable for dual-fuel engines with a minor variation in their loading regime. Nonetheless, when the start injection angle was fixed at 60 °CA, the derating power of the dual-fuel engine increased from 7.41 % to 27.84 % as the stop injection angle was advanced from 280 °CA to 220 °CA, showing that this injection strategy was better suited for dual-fuel engines that experienced larger variations in their loading regime. Direct injection of syngas using the twinning injector system at an injection pressure of 6 bar, in conjunction with a suitable start/stop injector strategy, constitutes an appropriate solution for maintaining power derating in syngas-diesel dual-fuel engines below an acceptable threshold of 10 %.

Effectiveness of vaccination, travel load, and facemask use control strategies for controlling COVID Delta variant: the case of Sydney Metropolitan Area

AbstractThe Delta variant of SARS-CoV-2, specifically identified as B.1.617.2, is responsible for the severe outbreaks witnessed globally, including in various countries and cities, with Sydney Greater Metropolitan Area (Sydney GMA) being no exception. According to scientific studies, the Delta strain exhibits increased contagion and leads to a higher incidence of vaccine breakthrough cases, posing significant challenges to pandemic control efforts. In this study, we explore the efficacy of three fundamental control strategies—namely, vaccination rates, adherence to facemask usage, and the management of travel loads—in mitigating the spread of the disease and, consequently, eliminating the Delta variant pandemic in Sydney GMA. We employ an agent-based disease spread model to thoroughly investigate these strategies. Moreover, factorial MANOVA is utilised to assess the significance of variations in the impact of diverse compliance levels with the aforementioned control strategies on various attributes of the pandemic. As complete lockdowns and stringent travel regulations have the potential to induce physical and mental distress in individuals and economic crises for countries, our study examines the interactive effects of implementing control strategies to mitigate the necessity for a full lockdown. The simulation results suggest that suppressing a pandemic with similar characteristics to Delta variant of COVID is feasible with a vaccination rate of 80% or higher, as long as travel load and activity participation are maintained at pre-COVID levels. Alternatively, a more realistic and attainable combination of control measures—a vaccination rate of 60%, a facemask usage level of 60%, and a 50% compliance level for social distancing—demonstrates comparable efficacy, leading to effective pandemic control. Notably, the vaccination rate emerges as a more potent control strategy compared to others in the elimination of the disease within society.

Automatic Fault Detection Method of Rotating Machinery Bearing Based on Complexity Analysis

In order to improve the working condition stability of rotating machinery bearings, an automatic fault detection method of rotating machinery bearings based on complexity analysis is proposed. The parameters of rotating machinery bearings are detected by using discrete sensor detection method, and the fault characteristics of rotating machinery bearings are extracted by fault type parameter extraction method. The complexity of rotating machinery bearings is detected by wavelet transform and fuzzy logic analysis. Considering the load mutation, noise disturbance, control strategy and other factors of rotating machinery bearings, the fault diagnosis and feature analysis model of rotating machinery bearings is established. The clustering and feature detection of rotating machinery bearings’ fault types are realized by the method of discrete complexity fusion clustering. Based on adaptive feedback compensation and parameter estimation, the output diagnostic error is taken as the fault detection index parameter, and the feature estimation in normal state and fault state is realized by harmonic level detection, so as to realize automatic fault detection of rotating machinery bearings. The simulation results show that this method has high accuracy and small deviation in fault detection of rotating machinery bearings, which improves the ability of automatic fault diagnosis.

Two-stage decision-dependent demand response driven by TCLs for distribution system resilience enhancement

Service restoration is a critical function of the self-healing distribution system to cope with extreme events. Cold load pickup (CLPU) caused by thermostatically controlled loads (TCLs) requires extra generation power to retore loads, slowing down the distribution system restoration process. Meanwhile, increasing renewable energy brings the supply-demand imbalance because of the power variability and may cause voltage or current violations. Accordingly, a two-stage decision-dependent demand response (DR) methodology is proposed to address the two barriers to distribution system resilience enhancement. Specifically, two load control strategies are developed in the first-stage DR to regulate TCLs for CLPU mitigation, which reduces the additional power requirement when re-energized. In the second-stage DR, the restored TCLs that can be controlled to provide flexibility are characterized as virtual energy storage (VES) for managing renewable energy variability. In this way, the required power generation is reduced, and the power fluctuation problem caused by renewable energy can be well addressed. It helps to speed up the load restoration and keep the distribution system operating securely. Moreover, the load profiles with CLPU mitigation control, VES parameters and VES availability time, depend on the re-energization time. In other words, load restoration decisions determine the two-stage DR. This is the most important finding of this paper and explicitly formulated in the load restoration model for accurate load characterization. The load restoration model is described by a mixed integer second-order cone programming (MISOCP) problem and solved using MATLAB 2021 with Gurobi solver. Case studies show that the proposed methodology can significantly mitigate CLPU and restore more loads. The decision-dependent behaviors of the two-stage DR are also validated.

Optimal operation of electric–freshwater energy system considering load regulation strategy of individual hydrogen electrolyzer

AbstractIn view of the existing literature, only the optimization operation of hydrogen energy–wind/light new energy is considered, and the research problems such as comprehensive utilization of water resources and load control strategies are ignored. Based on the analysis of load characteristics of offshore wind power, this paper has established an optimal operation model of power‐fresh water energy system based on “wind‐hydrogen‐water‐electricity” interaction. Meanwhile, an electrolytic hydrogen individual load control strategy is proposed to match wind power fluctuations from the perspective of internal load regulation of electrolytic hydrogen system. From the economic characteristics, operation characteristics, accommodation situation and other simulation analysis, it can reduce the total operating cost by about 3.1%, improve the utilization rate of electrolytic cell capacity, and meet the water demand of coastal users. It shows that the individual control strategy and optimal operation model have advantages, which is of great significance for realizing low‐carbon, safe, and economical operation of power grid in the future.

Direct Load Control Scheme for Flexible Loads under Automated Demand Response Program for Peak Demand Management, Loss Minimization, Asset Management, and Sustainable Development

Background: Nowadays implementation of Demand Response (DR) programs in the distribution grid is a necessary planning criterion for distribution utility. Implemented DR programs should be automated, intelligent, well-educated, and more competent than the conventional augmentation techniques to resolve Distribution Network (DN) constraints. Peak demand causes DN to approach its maximum capacities. Peak demand also exceeds the sustainable limit of the DN resulting disruption in electric supply, failures of various assets like transformers, feeders, etc. Objective: In this paper, a Direct Load Control (DLC) scheme for Flexible Loads (FLs) is modeled & implemented under Automated Demand Response (ADR) program and tested on real 54-bus DN. Methods: This ADR program is implemented through Demand Response Aggregator (DRA) and ADR Technology Solution Enablers (ADRTSE) to curtail the peak demand on the DN ADR is a recent technology that may put off new generation (conventional- and non-conventional both). Results: It also enables the distribution utility to curtail the peak demand & its period ensuring reliability of supply without restructuring, augmentation of existing infrastructure, and development of new infrastructure. Conclusion: The result validates the effectiveness of ADR program for peak demand curtailment, asset management, distribution network losses minimization, and for sustainable development of environment.

Emergency Control Strategy for Electrolytic Aluminum Load Considering the Load's Transient Overcurrent Characteristics and Transient Voltage Stability Constraints

Emergency Control Strategy for Electrolytic Aluminum Load Considering the Load's Transient Overcurrent Characteristics and Transient Voltage Stability Constraints

Thermal-hydraulic and load following performance analysis of a heat pipe cooled reactor

Heat pipe cooled reactors have gained attention as a potential solution for nuclear power generation in space and deep sea applications because of their simple design, scalability, safety and reliability. However, under complex operating conditions, a control strategy for variable load operation is necessary. This paper presents a two-dimensional transient characteristics analysis program for a heat pipe cooled reactor and proposes a variable load control strategy using the recuperator bypass (CSURB). The program was verified against previous studies, and steady-state and step-load operating conditions were calculated. For normal operating condition, the predicted temperature distribution with constant heat pipe temperature boundary conditions agrees well with the literature, with a maximum temperature difference of 0.4 K. With the implementation of the control strategy using the recuperator bypass (CSURB) proposed in this paper, it becomes feasible to achieve variable load operation and return the system to a steady state solely through the self-regulation of the reactor, without the need to operate the control drum. The average temperature difference of the fuel does not exceed 1 % at the four power levels of 70 %,80 %, 90 % and 100 % Full power. The output power of the turbine can match the load change process, and the temperature difference between the inlet and outlet of the turbine increases as the power decreases.

A Load Control Strategy for Stable Operation of Free-Piston Electromechanical Hybrid Power System

Abstract The free-piston electromechanical hybrid power system (FEHS) affords the advantages of a simple construction and high thermal efficiency due to the removal of the crankshaft. However, the unrestricted trajectory of the piston linkage assembly (PLA) also gives rise to challenges for stable operation during the process of startup or operation. In order to realize the stable operation of free-piston electromechanical hybrid power system, this paper proposed a load control strategy. First, a dynamic model is established through thermodynamic and electromagnetic theory, and its effectiveness is verified by experiment and simulation. On this basis, a coupling load control model based on linear active disturbance rejection control (ADRC) is developed. The reliability of the proposed load control strategy is validated under different interference fluctuations. The simulation results demonstrate that no matter whether the interference occurs during the startup process or the operation process, the proposed control strategy exerts effective limiting function over the piston linkage assembly and maintain its stable operation. Moreover, compared with the proportion integral differential (PID) control strategy, the proposed strategy exhibits faster response times and a smoother startup process. The compression ratio fluctuation range was reduced from 0.1 to 0.001, and the control accuracy has been greatly improved.

Enhanced food waste anaerobic digestion by simultaneously controlling sludge loads and iron oxide addition

The influence of the combination of sludge load control and iron oxide (IO) addition strategies on food waste anaerobic digestion (AD) was explored. The results showed that low sludge loads or IO addition could significantly enhance AD performance. Low sludge loads promoted substrate hydrolysis and volatile fatty acids degradation, which enhanced the biochemical methane potential (BMP) and production rate, respectively. IO addition promoted the CH4 yield and maximum CH4 production rate (Rm) by 65.50% and 206.79%, respectively, by promoting hydrolysis and interspecies electron transfer among syntrophic microbes. Moreover, although the presence of IO could prevent the failure of AD in extremely high sludge load conditions, it could not ensure complete BMP recovery. In an IO-assisted reactor, low sludge loads decreased the methanogenic lag phase by 53.15% and increased the BMP and Rm by 49.93% and 120.11%, respectively. Although adequate IO dosage could effectively improve the digester performance, excessive dosage may limit the economic benefits. Overall, the AD performance could be optimized by simultaneously controlling the sludge load and IO addition.

Energy Performance Analysis of Photovoltaic Integrated with Microgrid Data Analysis Using Deep Learning Feature Selection and Classification Techniques

Microgrids are an essential element of smart grids, which contain distributed renewable energy sources (RESs), energy storage devices, and load control strategies. Models built based on machine learning (ML) and deep learning (DL) offer hope for anticipating consumer demands and energy production from RESs. This study suggests an innovative approach for energy analysis based on the feature extraction and classification of microgrid photovoltaic cell data using deep learning algorithms. The energy optimization of a microgrid was carried out using a photovoltaic energy system with distributed power generation. The data analysis has been carried out for feature analysis and classification using a Gaussian radial Boltzmann with Markov encoder model. Based on microgrid energy optimization and data analysis, an experimental analysis of power analysis, energy efficiency, quality of service (QoS), accuracy, precision, and recall has been conducted. The proposed technique attained power analysis of 88%, energy efficiency of 95%, QoS of 77%, accuracy of 93%, precision of 85%, and recall of 77%.

Optimal guidance strategy for flexible load based on hybrid direct load control and time of use

The time-of-use (TOU) strategy can effectively improve the energy consumption mode of customers, reduce the peak-valley difference of load curve, and optimize the allocation of energy resources. This study presents an Optimal guidance mechanism of the flexible load based on strategies of direct load control and time-of-use. First, this study proposes a period partitioning model, which is based on a moving boundary technique with constraint factors, and the Dunn Validity Index (DVI) is used as the objective to solve the period partitioning. Second, a control strategy for the curtailable flexible load is investigated, and a TOU strategy is utilized for further modifying load curve. Third, a price demand response strategy for adjusting transferable load is proposed in this paper. Finally, through the case study analysis of typical daily flexible load curve, the efficiency and correctness of the proposed method and model are validated and proved.

Adaptive Power Line Communication for Low-Data-Rate Control and Sensing

Unreliable and range-limited communication restricts the effectiveness of many demand-side management schemes. For electrical loads with infrequent switching needs, untapped opportunities still exist to facilitate the reliable deployment of power line communication (PLC) for demand-side management applications. Inexpensive low-data-rate PLC, typically robust against power-line attenuation, can enable reliable load control in a building or facility. Yet, effective low-data-rate PLC schemes are susceptible to harmful and time-varying power-line noise levels. This paper presents approaches for adapting low-data-rate PLC to short-term and long-term noise variations often present in PLC channels. The proposed approaches enhance low-data-rate PLC performance, and further improve the reliability of load-control schemes that only require low data rates. Field demonstrations in a 24-floor apartment building with challenging conditions validate the proposed schemes.

Economic analysis based on saline water treatment using renewable energy system and microgrid architecture

Abstract Reverse osmosis desalination facilities operating on microgrids (MGs) powered by renewable energy are becoming more significant. A leader-follower structured optimization method underlies the suggested algorithm. The desalination plant is divided into components, each of which can be operated separately as needed. MGs are becoming an important part of smart grids, which incorporate distributed renewable energy sources (RESs), energy storage devices, and load control strategies. This research proposes novel techniques in economic saline water treatment based on MG architecture integrated with a renewable energy systems. This study offers an optimization framework to simultaneously optimize saline as well as freshwater water sources, decentralized renewable and conventional energy sources to operate water-energy systems economically and efficiently. The radial Boltzmann basis machine is used to analyse the salinity of water. Data on water salinity were used to conduct the experimental analysis, which was evaluated for accuracy, precision, recall, and specificity as well as computational cost and kappa coefficient. The proposed method achieved 88% accuracy, 65% precision, 59% recall, 65% specificity, 59% computational cost, and 51% kappa coefficient.