Optimal Start-up Research Articles

Dynamic characteristic analysis and startup optimization design of an intermediate drive belt conveyor with non-uniform load.

As an important transportation equipment, belt conveyor plays an important role in underground coal mine production and is an indispensable component. In this article, taking the intermediate drive belt conveyor of Shanxi Tongmei Group Tongxin Mine as an example, the continuous dynamic method is adopted to comprehensively consider the non-uniform load distribution of the belt conveyor, and mathematical modeling of the intermediate drive belt conveyor is performed. The dynamic characteristics of the conveyor belt are analyzed. The MATLAB software is used to analyze the change of the conveyor belt tension under different starting accelerations. Based on the analysis results, the starting acceleration is optimized, and the new combined parabolic acceleration curve presented here is more suitable for the actual working condition of the belt conveyor. In this article, the startup timing of the head and middle motors of the belt conveyor is also discussed in depth. The start timing design of the belt conveyor is described, which provides a reference for the design of the belt conveyor with an intermediate drive.

Optimal Start-up Policies for a Nanofluid-Based Solar Thermal Power Plant

Parabolic trough solar thermal power plants use a fluid to transfer thermal energy from captured solar radiation to a Rankine cycle to drive a turbine that, coupled to an electrical generator, produces electricity. Continuous improvement on their performance will lead these technologies to truly compete with either conventional or other forms of renewable energy systems. Nanofluids have been proposed as a way to improve heat transfer rates in thermal solar plants. Hence, nanofluid thermal solar plants coupled to dynamic optimal operating policies should render improved heat transfer characteristics as well as power production. The main objective of this work is to obtain optimal start-up policies of such plants using diverse nanofluids (Al2O3-water and TiO2-water) compared against pure water as base fluid, focused on power delivery and the time required for the system to reach target conditions. For the analysis, the deterministic dynamic mathematical model of a previously proposed solar thermal power fac...

Modeling and Optimization of Soft Start-Up for Hydroviscous Drive Applied to Scraper Conveyor

To improve the soft start-up performance of a scraper conveyor under different working conditions, the mathematical model of the torque for controllable starting transmission was established. The influences of start-up time, load values, and moment of inertia on the soft start-up characteristics of a scraper conveyor are analyzed. Based on the analytic hierarchy process (AHP), the new evaluation system of soft start-up optimization for hydroviscous drive applied to a scraper conveyor is proposed. Through the joint simulation platform of MATLAB and Isight, the two-parameter control model for soft start-up time is established using the method of experimental design and simulated annealing algorithm. The optimal start-up time under different conditions is determined, and soft start-up is optimized. The results show that with increasing start-up time, the objective function value of soft start-up performance decreases first and then increases. Under different flywheel inertia and load conditions, there is an optimal start-up time that minimizes the objective function for better soft start-up performance. The optimal start-up time decreases with increasing load, and the optimal start-up time decreases monotonically with the input flywheel inertia. This research provides a new method and theoretical basis for the modeling and performance optimization of soft start-up for hydroviscous drive applied to a scraper conveyor.

Development of a program to simulate the dynamic behavior of heavy-duty gas turbines during the entire start-up operation including very early part

This study presents a simulation tool for the dynamic behavior during the start-up of heavy-duty gas turbines. The simulation was implemented in MATLAB and can accurately predict the full start-up procedure from zero speed to idling. Each component of the system was modeled as a single control volume or multiple control volumes to which mass and energy balances were applied. The governing equations are solved numerically by the multi-variable Newton Raphson method. The compressor and turbine are divided into several groups for the bleeding and turbine cooling model. The program can simulate the early part of the start-up process from zero rpm to ignition by using the starter module in the cranking process, which can be hard to simulate using commercial software. A heat transfer model was applied to each control volume of the major components to consider the heat soakage effect accurately. The full start-up process of an industrial gas turbine was simulated, and the results were compared with actual operating data for validation. The program is expected to be used for various purposes, especially for estimating an adequate starter capacity and scheduling an optimal start-up procedure of heavy-duty gas turbines.

Optimization of Pump Start-Up Depth in Drainage Pumping Station Based on SWMM and PSO

The pumps in multistage drainage pumping stations are often subject to frequent start-up and shutoffs during operation because of unreasonable start-up depths of the pumps; this will reduce the service lives of the pumps. To solve this problem, an optimization method for minimizing pump start-up and shutoff times is proposed. In this method, the operation of pumps in pumping station was optimized by constructing a mathematical optimization model. The storm water management model (SWMM) and particle swarm optimization (PSO) method were used to solve the problem and the optimal start-up depth of each pump is obtained. Nine pumping stations in Beijing were selected as a case study and this method was applied for multistage pumping station optimization and single pumping station optimization in the case study. Results from the case study demonstrate that the multistage pumping station optimization acquired a small number of pump start-up/shutoff times, which were from 8 to 114 in different rainfall scenarios. Compared with the multistage pumping station optimization, the single pumping station optimization had a bigger number of pump start-up/shutoff times, which were from 1 to 133 times, and the pump operating time was also longer, from 72 min to 7542 min. Therefore, the multistage pumping station optimization method was more suitable to reduce the frequency of pump start-up/shutoffs.

An Online Generator Start-Up Algorithm for Transmission System Self-Healing Based on MCTS and Sparse Autoencoder

Generator start-up is a pivotal step of transmission system self-healing after large-scale blackouts. Considering the uncertainty of initial power system situation after blackouts and line restoration during power system restoration, an online generator start-up algorithm based on Monte Carlo tree search (MCTS) and sparse autoencoder (SAE) is proposed for real-time decision making. First, an online decision support system and a generator start-up efficiency indicator involving the total generation capability and number of restored lines are proposed. Then, the SAE is deployed to learn the data relevant to generator start-up offline to establish a value network, which is used to rapidly estimate the optimal generator start-up efficiency indicator. Next, MCTS used for the online generator start-up is improved by the modified upper confidence bound apply to tree algorithm, move pruning technique, and value network. It is used to search the next line to be restored based on real-time situation. Finally, root parallelization computation is adopted and a decision-making method is proposed to improve the reliability of decision making. Simulation results of the New England 10-unit 39-bus power system and Western Shandong Power Grid of China demonstrate that the proposed algorithm can accomplish generator start-up step by step reliably.

Optimal successive start-up strategy of two hydraulic coupling pumped storage units based on multi-objective control

This paper aims to study the optimal successive start-up strategy of two hydraulic coupling pumped storage units (PSUs) based on multi-objective control. Firstly, a successive start-up model of a pumped storage power station (PSPS) with two PSUs is established. Secondly, the analysis of the impact of successive time interval ΔT is carried out. Thirdly, a novel optimization scheme multi-objective with two PSUs owning different parameters (MODP) is proposed for start-up optimization. For comparison, three optimization schemes named single objective with two PSUs sharing the same parameters (SOSP), single objective with two PSUs owning different parameters (SODP) and multi-objective with two PSUs sharing the same parameters (MOSP) are also tested. Finally, according to the four optimization schemes, i.e. SOSP, SODP, MOSP and MODP, the optimization model is established and performed separately in MATLAB 9.1 based on a real case. The results indicate that the change of ΔT has a great effect on the transient process of 1# PSU, but less effect on the transient process of 2# PSU. ΔT should be chosen as a decision variable in the successive start-up optimization. For the successive start-up of a PSPS with two PSUs, the multi-objective scheme is superior to the single-objective scheme. The scheme of different parameters is superior to the scheme of sharing parameters. Among four schemes, MODP scheme is the best. The MODP scheme can obtain the Pareto Set that provides more choices for decision makers, which is flexible in engineering applications. MODP is a general method for successive start-up strategy optimization.

Central composite rotatable design for startup optimization of anaerobic sequencing batch reactor treating biodiesel production wastewater

Biodiesel is an important source of renewable energy, whose production generates wastewater (BWW) comprised mainly of glycerol as the source of organic matter (COD). Anaerobic digestion of BWW is a promising technique for the remediation of this environmental hazard. Anaerobic biodegradation of glycerol present in BWW is influenced by parameters such as reaction time, amount of biomass inoculum and operating temperature. The objective of this work was the optimization and mathematical modeling of these parameters to maximize the performance of an anaerobic sequencing batch reactor (AnSBR) for treating BWW. The amount of biomass inoculum had the greatest influence on COD removal efficiency. Temperature and reaction time had greater influence on behavior of the parameters responsible for AnSBR buffering, including total volatile acids and total, partial, intermediate and bicarbonate alkalinities. Even when operated under loading rates above the values reported in the literature, the AnSBR presented satisfactory performance. The mathematical model generated in this work can be used for forecasting, process control and reactor scaleup.

Sensorless Startup Strategy for a 315-kW High-Speed Brushless DC Motor With Small Inductance and Nonideal Back EMF

This paper presents a novel sensorless startup strategy for a 315-kW high-speed magnetic suspension brushless dc (BLDC) motor with small inductance and nonideal back electromotive force (EMF). Two key strategies on the sensorless startup strategy of the BLDC motor are presented: First, small current startup strategy for the high-speed BLDC motor with small inductance; and second, self-adaption control strategy to compensate the commutation error for the BLDC motor with nonideal back EMF in the startup stage. A hybrid pulsewidth modulation strategy based on the load torque is proposed to limit the startup current. An optimal motor startup curve based on the system parameters is presented, and a self-adaption control strategy is proposed to solve the synchronous switching problem. The effectiveness and feasibility of the proposed method is verified by a series of experiments on the 315 kW, 20 000 r/min magnetic suspension blower platform.

Optimization and Implementation of the Proportional-Resonant Controller for Grid-Connected Inverter With Significant Computation Delay

This paper describes the tuning process of the proportional-resonant controller, taking into account the significant computational delay from the digital control system. Different structures of the controller and related contradicting results are discussed. Particular attention is paid to the stability domain and its dependence on different parameters of the proportional-resonant controller. The main outcome of this paper consists in the tuning approach guidelines for selection of controller parameters in case of significant digital system delay. An optimal controller structure and start-up current optimization are proposed. All results are confirmed by simulation and experimental setup.

Operating strategy for successful start-up in self-humidified polymer electrolyte membrane fuel-cell system

A parametric study on the current distribution of a polymer electrolyte membrane fuel cell in dry conditions was conducted to suggest an optimal start-up strategy to achieve stable and successful operation. We used a segmented cell to measure the current distribution on the fuel cell depending on operating parameters. First, we examined the effect of the operating parameters on the current distribution. When the mass flow rate was high, the flow could easily remove flooding at the exit; however, it easily dehydrated the membrane at the inlet. Therefore, the maximum value of the local current was 1.2 A and 1.15 A for low and high flow rate, respectively. When the pressure was high, the current was distributed uniformly. The difference between the maximum and minimum current values was 0.55 A for 1 bar and 0.45 A for 3 bar. This is because the membrane was easily hydrated when the partial pressure of the vapor was high. Moreover, when high-temperature gas entered the fuel cell, the membrane was dehydrated; therefore, only a small amount of current was generated. According to this analysis, we suggested an optimal dry start-up process. The proposed procedure ensures successful start-up and reduces the start-up time.

Real Options Analysis of the Flexible Operation of an Enhanced Gas-Fired Power Plant

The promotion of electricity from renewable energies in Germany causes difficulties in the profitable operation of many modern conventional power plants. Nevertheless, fluctuating availability of power from renewable energy sources requires flexible conventional plants, i.e. power plants which are able to react fast to these fluctuations and whose start-up and shut-down optimization will help to reduce their running costs. In this paper, we describe various possibilities of enhancing the flexibility of conventional combined cycle gas-fired turbine (CCGT) power plants, which can be achieved by investing in additional technical components or by the upgrading of existing components. The irreversible character of these investments justifies the use of a real options approach. To this end, we present a real options model for the flexible operation of existing gas-fired power plants, taking into account both technical and economic aspects. The proposed model adopts and extends the approach of Deng and Oren (Prob Eng Info Sci, 2003, pp.155-181) to the gas-fired power plant regarding its different operation stages. Moreover, both the electricity price and the spark spread are used as a profitability indicator and source of uncertainty. The simplified definition of the power plant's operation strategy complements the presented model. In a case study, we consider several technical options to improve the minimum load and part-load efficiency by retrofitting a gas-fired power plant. The proposed procedure can help to assess the future role of conventional power plants and supports the decision-making process regarding both reinvestments and optimal operation of power plants. The introduced model can also be easily adapted to other power generation technologies, not only gas-fired power plants.

Optimal startup operation of a pressure swing adsorption

Abstract Pressure swing adsorption (PSA) is a gas separation and purification technology for high purity and small throughput. There exists literature on simulation and optimization of PSA operation; however most of it is based on cyclic steady state (CSS) conditions. There is scant literature on simulations of startup operation. We present the problem formulations of optimal startup in PSA for separating H2-CO2 in this work. Two formulations were considered for the startup, one with the consideration of only the CSS conditions in the objective function and the other one by considering both, the transient and CSS conditions in the objective function. The performance of both the operations was measured in terms of the number of cycles to attain the CSS (NCSS). The consideration of transient conditions demand optimizing the transient profile (until the CSS is achieved) of the manipulated variable, which requires large computational expense, however providing greater benefits in terms of reduced NCSS.

Start-Up Optimization of a CCGT Power Station Using Model-Based Gas Turbine Control

The rapid growth of renewable generation and its intermittent nature has modified the role of combined cycle power stations in the energy industry, and the key feature for the operational excellence is now flexibility. Especially, the capability to start an installation quickly and efficiently after a shutdown period leads to lower operational cost and a higher capacity factor. However, most of existing thermal power stations worldwide are designed for continuous operation, with no special focus on an efficient start-up process. In most current start-up procedures, the gas turbine controls ensure maximum heat flow to the heat recovery steam generator, without feedback from the steam cycle. The steam cycle start-up controls work independently with as main control parameter the limitation of the thermal stresses in the steam turbine rotor. In this paper, a novel start-up procedure of an existing combined cycle power station is presented, and it uses a feedback loop between the steam turbine, the boiler and the gas turbine start-up controls. This feedback loop ensures that the steam turbine can be started up with a significant reduction in stresses. To devise and assess this start-up methodology, a flexible and accurate dynamic model was implemented in the Simulink environment. It contains >100 component blocks (heat exchangers, valves, meters and sensors, turbines, controls, etc.), and the mathematical component submodels are based on physical models and experimental correlations. This makes the model generally applicable to other power plant installations. The model was validated against process data related to the three start-up types (cold start, warm start, hot start). On this basis, the optimization model is implemented with feedback loops that control, for example, the exit temperature of the gas turbine based on the actual steam turbine housing temperature, resulting in a smoother heating up of the steam turbine. The optimization model was used to define the optimal inlet guide vanes position and gas turbine power output curves for the three types of start-up. These curves were used during real power station start-ups, leading to, for cold and warm starts, reductions in the start-up time of, respectively, 32.5% and 31.8%, and reductions in the fuel consumption of, respectively, 47.0% and 32.4%. A reduction of the thermal stress in the steam turbines is also achieved, thanks to the new start-up strategy.

A Model Predictive Control Based Generator Start-Up Optimization Strategy for Restoration With Microgrids as Black-Start Resources

Microgrids (MGs) can operate in an islanded mode and serve as black-start resources for power system restoration (PSR). In this work, a model predictive control (MPC) based generator start-up optimization strategy for PSR is proposed utilizing MGs as black-start resources. First, the generator start-up sequence (GSUS) optimization is formulated as a mixed integer linear programming. Then, the uncertainties of MG black-start resources (MBSRs) are modeled by discretizing the probability distribution of the forecast errors, and representative scenarios for MBSRs extracted by formulating the probability mass transportation problem. Third, the generator start-up optimization strategy considering MBSRs is proposed utilizing the MPC technique, in which the optimization objective is to maximize the energy capability of the power systems and minimize the load curtailment of the MGs in each looking-ahead interval. Simulations on the IEEE 118 bus system with MGs and Zhejiang provincial power system in China verify that the proposed strategy for PSR can successfully restore the power system and effectively determine the optimal GSUS.

Engine start-up optimal control for a compound power-split hybrid powertrain

Abstract Engine start-up is the key for the control of mode transition from electric drive mode to electronic-Continuously Variable Transmission (e-CVT) mode for a compound power-split hybrid electric vehicle (HEV). With the engine shaft directly connected to the powertrain through a torsional damper spring (TDS), the engine ripple torque (ERT) before ignition is amplified by the powertrain and transmitted to the wheel, which has a significant impact on the vehicle. To improve the ride comfort of the mode transition process, an engine start-up control strategy is proposed. First, the ERT model and the dynamic model of power-split powertrain were built, and the mode transition process was analyzed. Second, an optimal crank track of engine speed was designed based on the dynamic programming aiming at ride comfort. Third, the engine reference acceleration curve was calculated according to the optimal speed track, and an optimal engine start-up control strategy was proposed. Finally, through simulations of the dynamic programming the influence factors for engine start-up were examined, and the experiment results indicate that the proposed engine start-up optimal control can effectively improve the ride comfort during mode transition.

Optimal start-up operating strategies for gas-boosted parabolic trough solar power plants

Concentrating solar power plants are taking an increasing share in the renewable energy generation market. Parabolic trough is one of such technologies and the most commercially mature. However, this technology still suffers from technical challenges that need to be addressed. As these power plants experience daily start-up procedures, the optimal performance in transient operation needs to be considered. This paper presents a performance based modelling tool for a gas-boosted parabolic trough power plant. The objective of the paper is to define an optimal operational strategy of the power plant start-up procedure with the aim of minimizing its fuel consumption while at the same time maximizing its electric energy output, taking into account all the thermo-mechanical constraints involved in the procedure. Heating rate constraints of the steam generator and the booster heater, and the steam turbine start-up schedule were considered. The simulation model was developed based on a power plant located near Abu Dhabi, and was validated against real operational data with a maximum integral relative deviation of 4.3% for gross electric energy production. A multi-objective optimization was performed for a typical operating week during winter and spring weather conditions. The results suggest that in order to minimize the fuel consumption and at the same time maximize the electric energy production, an evaporator heating rate of 6 K/min is an optimal value both for winter and spring conditions.

Start-Up Optimization of Combined Cycle Power Plants: A Field Test in a Commercial Power Plant

Requirements for the start-up operations of gas turbine combined cycle (GTCC) power plants have become more diverse and now include such items as reduced start-up time, life consumption, and fuel gas consumption. In this paper, an optimization method is developed to solve these multi-objective problems. The method obtains optimized start-up curves by iterating the search for the optimal combination of the start-up parameter values and the evaluation of multiple objective functions. The start-up curves generated by this method were found to converge near the Pareto-front representing the best trade-off between the fuel gas consumption of the gas turbine (GT) and thermal stress in the steam turbine (ST) rotor which are defined as the objective functions. To demonstrate the effectiveness of the developed method, field tests were performed in a commercial power plant. As a result, the fuel gas consumption of HOT start-up was reduced by 22.8% compared with the past operation data. From this result, the developed method was shown to be capable of optimizing the start-up process for GTCC power plants.

Optimal generation units start-up sequence during restoration of power system considering network reliability using bi-level optimization

During recent years power systems are operated near the nominal capacity of system equipment with low stability margin. Operation of power systems in this condition is extremelyrisky and power systems lose their stability with any intense failure of system equipment. In bulk power system, it is more critical and may cause a partial or overall blackout. The capability of black start to bring back system to a normal condition in the case of partial or overall shut down is very important in each power system. When a shutdown occurs, power plants with black start capability supply cranking power for non-black start power plants, pick up critical loads and energize required transmission lines. These actions should be done in minimum time interval to maximize system provided energy during the restoration process. Most important decision making during restoration process is the determination of start-up sequence of generation units. During the restoration process, units with black start capability (BS units) start at the beginning of the process to provide cranking power for non-black start units (NBS units). Hence the determination of NBS units is decision variable in the restoration problem. In this paper, this problem has been described as a bi-level optimization problem which in upper level determines the optimal start-up sequence of NBS units by using a Teaching-Learning Based Optimization algorithm and in lower level determines the optimal transmission path with minimum number of switching and maximum reliability between any two necessary buses using the searching path graph-based algorithm. The proposed approach has been implemented successfully on IEEE 24-bus RTS and IEEE 118-bus test systems.

Effect of Purging Time during Distillation Column Startups

This work evaluates the relationship between the purging start time and its effects during the startup of an extractive distillation system. According to the literature, only a few papers have considered the purging step during the system startup. The objective of this paper is to report the effects of purging start time as a startup optimization variable, contributing to a more realistic dynamic approach. The extractive distillation process to produce anhydrous ethanol using ethylene glycol as solvent was chosen as a case study due to its complexity. In order to evaluate the effect of the purging step during the column startup, the opening of the purge valve was varied in different scenarios. It was verified that an increase in the purge step runtime favors the time undertaken for the extractive column. However, this same increase did not favor the time spent for the recovery column, contributing to a greater amount of time spent overall. The results also showed that an increase in time to execute the pu...