Set Of Operating Points Research Articles

Distributed plantwide control based on differential dissipativity

SummaryModern chemical plants are becoming very complex, often consisting of a number of nonlinear process units (subsystems) with strong interactions due to material recycle and energy integration. The operation setpoint may need to be adjusted from time to time based on the market demand. To address the aforementioned challenges, a plantwide distributed nonlinear control scheme based on differential dissipativity is proposed in this paper, which can ensure plantwide incremental exponential stability and achieve bounded incremental L2 gain performance. As a non‐unique property, the differential dissipativity of individual subsystem is shaped by a setpoint‐independent control structure – differential state feedback control. The dissipativity properties of subsystems and individual controllers are determined simultaneously as a large‐scale feasibility problem to ensure the plantwide stability and performance. It is converted into an LMI condition for plantwide supply rate planning and small‐scale sum‐of‐squares programming problems for individual subsystem dissipativity shaping, by using the alternating direction method of multipliers method. The proposed approach is illustrated using a chemical reactor network with a recycle stream. Copyright © 2016 John Wiley & Sons, Ltd.

Economic Equivalence of Economic Model Predictive Control and Hierarchical Control Schemes

The traditional approach to optimal economic operation of industrial processes has been the use of a hierarchically structured control system. This hierarchical structure comprises a steady-state economic optimization layer that computes optimal operating set points of the system and a dynamic control layer using model predictive control to track these set points. One limitation of this structure is that the economics of the process is not being dynamically optimized. To overcome this limitation, economic model predictive control, which optimizes the economics directly in the dynamic layer in order to give a superior economic performance, has been proposed to replace the hierarchical approach. This paper investigates this notion of superior economic performance and proposes a redesign of the traditional hierarchical structure that gives an economic performance that is as good as that of economic model predictive control. Specifically, a new approach to selecting the objective function in the model predict...

Modelling and Optimization of Operational Setpoint Parameters for Maximum Fermentative Biohydrogen Production Using Box-Behnken Design

Fermentative biohydrogen production has been flagged as a future alternative energy source due to its various socio-economical benefits. Currently, its production is hindered by the low yield. In this work, modelling and optimization of fermentative biohydrogen producing operational setpoint conditions was carried out. A box-behnken design was used to generate twenty-nine batch experiments. The experimental data were used to produce a quadratic polynomial model which was subjected to analysis of variance (ANOVA) to evaluate its statistical significance. The quadratic polynomial model had a coefficient of determination (R2) of 0.7895. The optimum setpoint obtained were potato-waste concentration 39.56 g/L, pH 5.56, temperature 37.87 °C, and fermentation time 82.58 h, predicting a biohydrogen production response of 537.5 mL H2/g TVS. A validation experiment gave 603.5 mL H2/g TVS resulting to a 12% increase. The R2 was above 0.7 implying the model was adequate to navigate the optimization space. Therefore, these findings demonstrated the feasibility of conducting optimized biohydrogen fermentation processes using response surface methodology.

Adaptive fuzzy PI controller with shifted control singletons

It is well known the fact that the design of a fuzzy control system is based on the human expert experience and control engineer knowledge regarding the controlled plant behavior. As a direct consequence, a fuzzy control system can be considered as belonging to the class of intelligent expert systems. The tuning procedure of a fuzzy controller represents a quite difficult and meticulous task, being based on prior data regarding good knowledge of the controlled plant. The complexity of the tuning procedure increases with the number of the fuzzy linguistic variables and, consequently, of the fuzzy inference rules and thus, the tuning process becomes more difficult. The paper presents a new design strategy for such expert fuzzy system, which improves their performance without increasing the number of fuzzy linguistic variables. The novelty consists in extending the classic structure of the fuzzy inference core with an intelligent module, which tunes one of the control singletons, providing a significant simplification of the design and implementation procedure. The proposed strategy implements a logical, not physical, supplementation of the linguistic terms associated to the controller output. Therefore, a fuzzy rules set with a reduced number of linguistic terms is used to implement the expert control system. This logical supplementation is based on an intelligent algorithm which performs a shifting of only one of the control singletons (the singleton associated to the SMALL_ linguistic variable), its value becoming variable, a fact that allows an accurate control and a better performance for the expert control system. The logic of this intelligent algorithm is to initially provide a high controller output, followed by a slowdown of the control signal near to the operating set point. The main advantage of the proposed expert control strategy is its simplicity: a reduced number of linguistic terms, combined with an intelligent tuning of a single parameter, can provide results as accurate as other more complex available solutions involving tuning of several parameters (well described by the technical literature). Also, a simplification of the preliminary off-line tuning procedure is performed by using a reduced set of fuzzy rules. The generality of the proposed expert control strategy allows its use for any other controlled process.

A novel optimization algorithm for efficient economic dispatch of Combined Heat and Power devices

Combined Heat and Power (CHP) units produce heat to warm living spaces, supply hot water and generate electricity. Their normal operation is determined by the building thermal demand. These systems supply hot water on demand from hot water storage tanks avoiding intermittent operation of the machines. A method based on a novel control algorithm is presented to optimize the operating costs of one or a set of CHP units in either commercial or residential buildings. The algorithm uses hot water storage tanks to schedule the daily operation of the CHP devices maximizing the benefits of the electricity that is generated, while ensuring that the heat demand is covered. This is especially relevant for regulatory environments with Time of Use tariffs for electricity. The method comprises an optimization algorithm that minimizes the value of a target function. The target function includes a series of weights that penalize the violation of certain constraints. The outputs of the optimization algorithm define the operating set points of CHP unit/s. The results of the case study simulations demonstrate that the proposed implementation of the algorithm can achieve cost effective savings. Finally, the successful operation of the algorithm is demonstrated in a real building installation.

Comparative Carbon Footprint Assessment of commercial walk-in refrigeration systems under different use configurations

The design of refrigeration systems must strictly comply with the rules determined by the increasingly stringent international regulations on the use of refrigerants. Regardless of the restrictions imposed, the compliance with best practices in ecodesign may provide competitive leverage in the market, given its sustainability advantages. The replacement of fluorinated gases by latest generation hydrofluorocarbons (HFC)'s, or their complete ban, are considered necessary but not sufficient solutions for reducing the environmental damage caused by refrigeration systems: refrigerant retrofitting must include performance requisites, entail energy savings and generate a global environmental benefit. In this paper the environmental impact associated with the life cycle of two commercial refrigeration systems with walk-in cold rooms (for medium- and low temperature food storage) is investigated using a streamlined version of Life Cycle Assessment (LCA) methodology: Carbon Footprint Assessment (CFA). The environmental burden created by the refrigeration systems is evaluated by analysing the whole life cycle of the entity including the refrigeration unit and refrigerant. The environmental impact created by the adoption of alternative refrigerants (i.e. R-404A, R-407F, and R-410A) under different conditions (i.e. room set point temperature, refrigerant leakage rate) is also evaluated and discussed. CFA results are used as environmental performance indices in the final evaluation of the most sustainable configurations. The analysis of the whole refrigeration system life cycle demonstrates that the use-phase contributes significantly to the total environmental impact, and that indirect emissions resulting from refrigerating unit electric energy consumption are larger than those associated with refrigerant leakage. For the low-temperature (LT) system, the use of R-407F results in better environmental performance than R-404A and significantly minimises the overall system impact. Also for the medium-temperature (MT) system the retrofitting of R-404A introduces significant environmental advantages, but the optimal choice between R-410A and R-407F depends on the value of the operating set point temperature and leakage rate. Particularly given a set point temperature of 0 °C and a leakage rate of 10%, R-410A determines the best environmental performance. Instead with [10, 13]% of leakage rates and depending on the set point temperature, R-407F results the best solution.

Design Exploration for Determining the Set Points of Continuous Casting Operation: An Industrial Application

To compete with other materials and/or contribute toward light-weighting of vehicles, newer grades of steel are continuously invented and experimented upon. Due to the costs and time involved in such developments, manufacture of new grades of steel at an industrial scale is difficult. We propose a method that is useful for steel manufacturers interested in producing a steel product mix with new grades of steels by predicting the required change in the operating set points of each unit operation in the manufacturing chain of products with the new grade of steel. Here, we demonstrate a method to determine the set points of one unit operation, continuous casting which is measured in terms of conflicting objectives including productivity, quality, and production costs. These parameters are sensitive to the operating set points of casting speed, superheat, mold oscillation frequency, and secondary cooling conditions. To ensure targeted performance and address the challenges of uncertainty and conflicting objectives, an integrated computational method based on surrogate models and the compromise decision support problem (cDSP) is presented. The method is used to explore the design space available for casting operations and determine operating set points to meet requirements imposed on the caster from subsequent downstream processes. This method is of value to the steel industry and enables the rapid and cost effective production of a product mix with a new grade of steel.

Integrated Moving Horizon-Based Dynamic Real-Time Optimization and Hybrid MPC-PID Control of a Direct Compaction Continuous Tablet Manufacturing Process

In this manuscript, a moving horizon-based real-time optimization (MH-RTO) has been integrated with a hybrid model predictive control (MPC) system for a continuous tablet manufacturing process for quality by design (QbD)-based efficient continuous manufacturing. In the proposed approach, the integrated MH-RTO provides the optimal operational set points for the tablet production rate in real time. The MH-RTO takes into consideration the capital and operating cost, the market fluctuations, the product inventory, the product quality assurance strategy, the regulatory constraints, and the product rejections. An advanced hybrid model predictive control system then ensures that the required production rate with desired quality is met with minimum resources and time. A robust optimization strategy and an efficient control system have been integrated to achieve the maximum profit. The MH-RTO integrated with a hybrid control strategy ensures the maximum possible profit irrespective of the market demand fluctuations. The basic advantage of the MH-RTO framework is that it takes into consideration the future demand and thus can lead to increased profit compared to a standard real-time optimization approach.

Self-optimizing control of air-source heat pump with multivariable extremum seeking

The air-source heat pump (ASHP) is widely adopted for cooling and heating of residential and commercial buildings. The performance of ASHP can be controlled by several operating variables, such as compressor capacity, condenser fan speed, evaporator fan speed and suction superheat. In practice, the system characteristics can be varied significantly by the variations in ambient condition, operation setpoint, internal thermal load and equipment degradation, which makes it difficult to obtain accurate plant models. As consequence, the model based control strategies for ASHP could limit the achievable energy efficiency. Model-free self-optimizing control strategies are thus more preferable. In this study, a multi-input extremum seeking control (ESC) scheme is proposed for both heating and cooling operation of ASHP. The zone temperature is assumed to be regulated by the compressor capacity, while the expansion valve opening is used to regulate the suction superheat at the given setpoint. The total power consumption of the compressor, the condenser fan and the evaporator fan is measured as input to the ESC, while the ESC controls the evaporator fan speed, the condenser fan speed and the suction superheat setpoint. The proposed scheme is evaluated with a Modelica based dynamic simulation model of ASHP under both cooling and heating modes of operation. Simulation results show the effectiveness of the proposed scheme to achieve the maximum achievable efficiency in a nearly model-free manner.

Design Exploration of Engineered Materials, Products, and Associated Manufacturing Processes

In the past few years, ICME-related research has been directed towards the study of multi-scale materials design. However, relatively little has been reported on model-based methods that are of relevance to industry for the realization of engineered materials, products, and associated industrial manufacturing processes. Computational models used in the realization of engineered materials and products are fraught with uncertainty, have different levels of fidelity, are incomplete and are even likely to be inaccurate. In light of this, we adopt a robust design strategy that facilitates the exploration of the solution space thereby providing decision support to a design engineer. In this paper, we describe a foundational construct embodied in our method for design exploration, namely, the compromise Decision Support Problem. We introduce a problem that we are using to establish the efficacy of our method. It involves the integrated design of steel and gears, traversing the chain of steel making, mill production, and evolution of the material during these processes, and linking this to the mechanical design and manufacture of the gear. We provide an overview of our method to determine the operating set points for the ladle, tundish and caster operations necessary to manufacture steel of a desired set of properties. Finally, we highlight the efficacy of our method.

Hill-Climbing for Plantwide Control to Economic Optimum

The application of hill-climbing control to “seek” and drive the unconstrained set point of controlled variables (CVs) to their economic optimum is proposed for economic plantwide control. Its application is demonstrated on a reactor-column recycle process for energy efficiency maximization at given throughput (Mode I) and also for maximizing process throughput (Mode II). In Mode I, a one degree-of-freedom hill-climbing feedback controller on top of the regulatory layer is shown to reduce reboiler duty by 3.7% for a 25% throughput increase compared to that of a constant set point operation. Similarly, in Mode II, a one degree-of-freedom hill-climber achieves 3.0% throughput increase compared to that of a constant set point operation. These results highlight the effectiveness of hill-climbing for economic plantwide control.

Modeling of Wind Farm Participation in AGC

Wind power has become one of the most prominent renewable energy applications in the power industry. Its annual installation is continuously setting a record high. Due to the large portion of generation mix within the system, it is desirable to operate wind power under the automatic generation control (AGC). This issue also raises another concern on the modeling of wind farms under AGC. The traditional way of portraying wind farm production in simulation is to use an aggregated wind turbine model that is generally operated in maximum power point tracking (MPPT). This approach is not suitable for wind's participation in AGC. Therefore, more studies should be done to investigate how the individual wind turbines affect the wind farm performance under the set-point operation. This paper first illustrates the controllability of wind turbines under the set-point control. Following that, a comprehensive guidance of wind generator modeling is demonstrated to yield different approaches for developing the wind farm model. Two types of wind farm models are derived and demonstrated to portray the capability of set-point tracking under the intermittent wind condition. Associated simulations are presented and compared to show the different characteristics of these two wind farm models in depicting the set-point operation under AGC.

Hill-Climbing for Economic Plantwide Control

The application of hill-climbing control in the plantwide control context for driving the setpoint corresponding to an unconstrained degree of freedom to the economic optimum steady state is demonstrated for a reactor-separator-recycle process. Optimality via hill-climbing is sought for two operation modes. In Mode I, the throughput is fixed and hill-climbing maximizes the process energy efficiency. In Mode II, hill-climbing is used to maximize process throughput. Rigorous dynamic plantwide simulation results show that hill climbing control reduces steam consumption by ~3.7% and increases plant throughput by ~3.0%, compared to constant setpoint operation.

Multi-objective particle swarm and genetic algorithm for the optimization of the LANSCE linac operation

Particle swarm optimization (PSO) and genetic algorithm (GA) are both nature-inspired population based optimization methods. Compared to GA, whose long history can trace back to 1975, PSO is a relatively new heuristic search method first proposed in 1995. Due to its fast convergence rate in single objective optimization domain, the PSO method has been extended to optimize multi-objective problems. In this paper, we will introduce the PSO method and its multi-objective extension, the MOPSO, apply it along with the MOGA (mainly the NSGA-II) to simulations of the LANSCE linac and operational set point optimizations. Our tests show that both methods can provide very similar Pareto fronts but the MOPSO converges faster.

Pulse bubble sparging for the control of hydraulically reversible fouling in submerged hollow fiber membrane systems

Previous studies have demonstrated that pulse bubble sparging is more effective at the control of hydraulically reversible fouling than coarse bubble sparging in submerged hollow fiber membrane systems. However, some of the optimal operating set points for pulse bubble sparging control have not yet been identified. The present study was conducted to further quantify the potential benefits associated with pulse bubble sparging for the control of hydraulically reversible fouling. In particular, the effect of pulse bubble release frequency and size on the shear stress induced onto membranes and the resulting effect on the control of hydraulically reversible fouling was assessed. The shear stress and fouling control resulting from continuous and intermittent coarse bubble sparging was also considered so that the performance of these conventionally used sparging approaches could be compared directly to those for pulse bubble sparging.The shear stress resulting from pulse bubble sparging was significantly greater than that induced by continuous coarse bubble sparging, and similar to that induced by intermittent coarse bubble sparging. However, for pulse bubble sparging, the rate of fouling was significantly lower than for either continuous or intermittent coarse bubble sparging, indicating that the magnitude of the shear stress on its own cannot be used to assess the efficacy of different sparging approaches for the control of hydraulically reversible fouling.The pulse bubble release frequency had a significant effect on the rate of fouling. At lower sparging flows (i.e. lower pulse bubble release frequencies), the fouling rate decreased as the sparging flow increased. However, at the highest sparging flow considered, the rate of fouling was greater than that observed at the lower sparging flows, indicating that an optimal bubble release frequency likely exists, below which an increase in frequency decreases the extent of hydraulically reversible fouling, and above which the control of hydraulically reversible fouling is inhibited. For the conditions investigated, a pulse bubble release frequency of approximately 0.5–0.6Hz was optimal. In addition, the results suggest that the optimal pulse bubble size for the control of hydraulically reversible fouling is likely in the 150–250mL range. Sparging into stagnant water also resulted in better hydraulically reversible fouling control than sparging when liquid upflow was promoted.

Semi-pilot scale production of hydrogen from Organic Fraction of Solid Municipal Waste and electricity generation from process effluents

The production of hydrogen from Organic Fraction of Solid Municipal Waste (OFSMW) was studied on a semi-pilot scale. The potential of generating electricity using the process effluents was further assessed using a two-chambered Microbial Fuel Cell. A maximum hydrogen fraction of 46.7% and hydrogen yield of 246.93 ml H2 g−1 Total Volatile Solids was obtained at optimum operational setpoints of 7.9, 30.29 °C and 60 h for pH, temperature and hydraulic retention time (HRT) respectively. A maximum electrical power density of 0.21 W m-2 (0.74 A m−2) was recorded at 500 Ω and the chemical oxygen demand (COD) removal efficiency of 50.1% was achieved from the process. The process economics of energy generation from organic wastes could be significantly improved by integrating a two-stage process of fermentative hydrogen production and electricity generation.

Two industrial examples of coupling experiments and simulations for increasing quality and yield of distilled beverages

The aim of this study was to check the ability of ProSim® software to model both continuous and batch distillations of two specific industrial units in order to obtain both a better understanding of the behaviour of aroma volatile components and a tool to optimise the still's operation. Simulations of multistage continuous distillation to produce neutral spirit from raw alcohol and of batch distillation to produce bitter orange distillate from bitter orange peels macerate were carried out with ProSimPlus and BatchColumn software. Simulations were compared with distillations performed in two industrial plants. For each case, the industrial plants were studied to determine all the operating parameters and the behaviour of certain compounds selected for their high concentration or quality impact. Then, the NRTL and Henry's law thermodynamic models were chosen. Simulation results of particular compositions of the selected compounds in the different extractions were analysed and compared with experimental measurements. Simulations represented faithfully the behaviour of compounds in the industrial plants. Therefore, it was possible for two totally separated cases to illustrate the interest of simulation software; for neutral spirit production to determine new operation set points in order to maximise productivity and improve quality for neutral spirit production and for bitter orange distillate production, to explain the choice of different cuts and the role of the presence of peels during distillation.

Signal Processing of Virtual‐Neutral to Ground Voltage for Power Control in Electric Arc Furnaces

This research work proposes to detect arc conditions of electric arc furnaces (EAFs) based upon digital signal processing of the line to ground three‐phase voltage measurements at the secondary side of the furnace transformer. It uses the voltage difference between a virtual‐neutral point of the symmetrical power source and the furnace shell ground voltage. For harmonic analysis this voltage is processed using Fourier transform. The obtained information is found to be useful to detect arc operational conditions like arc stability, arc balance, and arc slag coverage. With the here in proposed arc indicators, the power control of the EAF can be performed using the concept of a dynamic power profile to set the operational transformer tap and current set points of the EAF control systems.

Exergoeconomic methodology applied to energy efficiency analysis of industrial power transformers

This work aims to develop a methodology based on exergoeconomic models to be used as a tool in the analysis of energy efficiency transformers arranged in distribution networks. The exergetic modelling method adopted is based on building of thermoeconomic functional diagram that will be used later as a reference for defining the allocation of costs associated with the transformer choose for analysis. The exergetic cost for each compound of transformer has a tendency to decrease because the value aggregated by device operation. Also exergetic production cost and final cost of power output have this same tendency. Finally these costs provide a payback period less than a year, which makes viable the investment in this system with operational set points.

A two-stage modelling and optimization of biohydrogen production from a mixture of agro-municipal waste

A two-stage modelling and optimization of biohydrogen production is reported. A mixture design was used to determine the optimum proportions of bean husk (BH), corn stalk (CS), and organic fraction of solid municipal waste (OFSMW). The optimum operational setpoints for substrate concentration, pH, temperature and hydraulic retention time (HRT) were further investigated using the box-behnken design. The quadratic polynomial model from the mixture design had a coefficient of determination (R2) of 0.9427 and the optimized mixtures were in the ratio of OFSMW:BH:CS = 30:0:0 and OFSMW:BH:CS = 15:15:0 with yields of 56.47 ml H2/g TVS and 41.16 ml H2/g TVS respectively. Optimization on physico-chemical process parameters on the improved substrate gave the setpoints of 40.45 g/l, 7.9, 30.29 °C, 86.28 h for substrate concentration, pH, temperature and HRT respectively having a predicted H2 yield of 57.73 ml H2/g TVS. Model validation gave 58.62 ml H2/g TVS, thus an improvement of 3.8% on the optimized mixture. Biohydrogen production can be significantly enhanced by a suitable mixture of agro-municipal waste and operational optimal setpoints.