Research on the Prediction of Load Regulation Capacity for Supercritical Thermal Power Unit

Both the modeling and the load regulation capacity prediction of a supercritical power plant are investigated in this paper. Firstly, an indirect identification method based on subspace identification method is proposed. The obtained identification model is verified by the actual operation data and the dynamic characteristics of the system are well reproduced. Secondly, the model is used to predict the load regulation capacity of thermal power unit. The power, main steam pressure, main steam temperature and other parameters are simulated respectively when the unit load is going up and down. Under the actual constraints, the load regulation capacity of thermal power unit can be predicted quickly.

Hierarchical Control Strategy for Load Regulation Based on Stackelberg Game Theory Considering Randomness

Demand response has been recognized as a valuable functionality of power systems for mitigating power imbalances.This paper proposes a hierarchical control strategy among the distribution system operator(DSO),load aggregators(LAs),and thermostatically controlled loads(TCLs);the strategy includes a scheduling layer and an executive layer to provide load regulation.In the scheduling layer,the DSO(leader)offers compensation price(CP)strategies,and the LAs(followers)respond to CP strategies with available regulation power(ARP)strategies.Profits of the DSO and LAs are modeled according to their behaviors during the load regulation process.Stackelberg game is adopted to capture interactions among the players and leader and to obtain the optimal strategy for each participant to achieve utility.Moreover,considering inevitable random factors in practice,e.g.,renewable generation and behavior of users,two different stochastic models based on sample average approximation(SAA)and parameter modification are formulated with improved scheduling accuracy.In the executive layer,distributed TCLs are triggered based on strategies determined in the scheduling layer.A self-triggering method that does not violate user privacy is presented,where TCLs receive external signals from the LA and independently determine whether to alter their operation statuses.Numerical simulations are performed on the modified IEEE-24 bus system to verify effectiveness of the proposed strategy.

Cross-level steam load smoothing and optimization in industrial parks using data-driven approaches

This study focuses on the integrated energy production system in industrial parks, addressing the problem of stable load dispatch of equipment under demand fluctuations. A cross-level method for steam load smoothing and optimization is proposed, aiming to achieve stable production and optimal economic performance through three levels of integration: load forecasting, load dispatch, and load regulation. Unlike traditional methods that directly use load forecasting values, heat network elasticity is presented as a buffer between demand and supply. Constraints for minimal changes in equipment load and operational parameters are established for smooth regulation. Industrial cases demonstrate that the load forecasting model has mean absolute percentage errors of 2.44% and 1.68% for medium-pressure and low-pressure steam, respectively, meeting accuracy requirements. The modified supply-side load smoothness is effectively improved by considering heat network elasticity. The method increases boiler efficiency by 1.92%, reducing average coal consumption by 0.92 t/h. Compared to manual operation, the proposed model leads to an average increase of 5.69 MW in power generation and an average reduction of 10.81% in coal-to-electricity ratio. This study verifies the importance of smooth integration across different levels and analyzes the effective response of the proposed method to the uncertainty in load forecasting. The method demonstrates the enormous potential of data-driven methods in achieving safe, economical, and sustainable production in industrial parks.

Analysis and Design of a High-Stability,High-Accuracy,Low-Dropout Voltage Regulator

A high-accuracy,low-dropout （LDO） voltage regulator is presented. Using the slow-rolloff frequency compensation scheme, the LDO effectively overcomes the stability problem, facilitates the use of a ceramic capacitor, and improves the output voltage accuracy, which is critical for powering high-performance analog circuitry. The slow-rolloff compensation scheme is realized by introducing three pole-zero pairs, including the proposed polezero pair and sense zero. The post-layout simulation results demonstrate that this LDO has robust system stability, a high open-loop gain, and a high unit-gain frequency,which lead to excellent regulation and transient response performance. The line and load regulation are 27μV/V and 3.78μV/mA, and the overshoots of the output voltage are less than 30mV,while the dropout voltage is 120mV for a 150mA load current.

Generic load regulation strategy for enhancing energy efficiency of chiller plants

In many chiller plants,high coefficient of performance(COP)is only achieved at a few favorable part load ratios(PLRs),while the COP is low at many other non-favorable PLRs.To address this issue,this study proposes a generic load regulation strategy that aims to maintain chiller plants operating at high COP,particularly under non-favorable PLRs.This is achieved by incorporating thermal energy storage(TES)units and timely optimizing the charging and discharging power of the integrated TES units.The optimal charging and discharging power is determined by solving a dynamic optimization problem,taking into account the performance constraints of the TES units and the chiller plants.To provide an overview of the energy-saving potential of the proposed strategy,a comprehensive analysis was conducted,considering factors such as building load profiles,COP/PLR curves of chillers,and attributes of the TES units.The analysis revealed that the proposed load regulation strategy has the potential to achieve energy savings ranging from 5.7%to 10.8%for chiller plants with poor COPs under unfavorable PLRs,particularly in buildings with significant load variations.