A systematic approach to the synthesis and design of flexible site utility systems

The paper presents a systematic approach for the synthesis of flexible utility systems satisfying varying energy demands. The approach combines benefits of total site analysis, thermodynamic analysis and mathematical optimisation. A thermodynamic efficiency curve (TEC) is developed, which gives an overview of the maximum thermodynamic efficiencies of all possible design alternatives. TEC and hardware composites guide the selection of candidate structures in the superstructure, excluding uneconomic options from the synthesis model. The integration of thermodynamics yields significant reduction in the synthesis model, addresses the impact of variable loads on the unit efficiencies, and enables a compact formulation of the design problem over long horizons of operation. The optimisation is formulated as a multi-period MILP problem that relies on new target models to describe the performance of steam turbines, condensing turbines, gas turbines and boilers. Target models account for the variation of efficiency with unit size, load and operating conditions in a simple, yet accurate way. As a result, these models are capable of accounting for the efficiency trends of realistic units.     

A multi-criteria optimisation approach for the design of sustainable utility systems

Large amounts of gaseous emissions are generated by combustion processes associated with the utility systems. The emissions include SO_x, CO₂, CO, NO_x, CH₄, and N₂O. Such emissions can result in significant impact on the surrounding environment. As a result of serious concerns about environmental problems in recent years, the design criteria for a modern utility system should include both environmental and economic requirements. This work proposes a multi-objective optimisation (MOO) strategy to identify the sustainable design of utility systems that satisfies both economic and environmental goals. A MOO mixed integer linear programming (MILP) model is developed to combine the minimisation of costs with the minimisation of environmental impact that is assessed in terms of life cycle environmental burdens. Most of the gaseous emissions are addressed in the model. The resulting MOO problem is solved using lexicographic goal programming (LGP) techniques. The new strategy has been applied to a case study for the design of a utility system with specific utility demands.     

Process optimisation using the combination of simulation and experimental design approach: Application to wet air oxidation

This study develops a coupling of energetic and experimental design approaches on a given configuration of wet air oxidation process (WAO), applied for wastewater containing a hard chemical oxygen demand (phenol for instance). Taking into account thermodynamic principles and process simulation, the calculation of minimum heat required by the process, exergetic efficiency and work balance is presented. Five parameters are considered: pressure (20-30 MPa); temperature (200-300 °C); chemical oxygen demand (23-143 g l⁻¹); air ratio (1.2-2) and temperature of exiting steam utilities (160-200 °C). Using the surface response method, it appears that initial chemical oxygen demand and temperature are the two parameters that mainly influence the result. With the modelling, good conditions for the functioning of the presented process are the following: pressure of 19.4 MPa, temperature of 283 °C, chemical oxygen demand of 54.9 g l⁻¹, air ratio of 1.7 and vapour temperature of 183 °C.     

Thermodynamic optimisation of distillation columns

In this paper a methodology for thermodynamic analysis and distillation column ‘targeting’ is presented, with emphasis on the use of side condensers and side reboilers. Research in the past has been towards the establishment of a heat distribution curve, showing the way in which heat can be added or extracted across the different column sections. One major disadvantage of these profiles is that they refer to reversible columns, and cannot be used effectively to target for modifications in a real column.The main feature of the proposed methodology is the introduction of a minimum driving force, defined in terms of exergy loss distribution of the existing column, to set realisable targets for side reboiling/condensing in real columns, resulting in considerable energy savings. In addition to providing realisable targets, the new approach also provides the design engineer with information about the best location to place a side exchanger, and the required additional column modifications. The methodology can be applied using conventional column models in commercial process simulation programs, but can be significantly simplified by using reboiled and refluxed absorber models in a bespoke program. Simulation results for modified designs set by the new approach, for binary and multicomponent separations, verify the feasibility of the targets. This contrasts with previous approaches, which result in temperature shifts and heat load penalties after placing side reboilers/condensers, thus requiring additional simulation time and experienced judgement.     

Optimization analysis of dual-purpose systems

This paper aims to analyze dual-purpose systems focusing the total cost optimization; a superstructure is proposed to present cogeneration systems and desalination technologies alternatives for the synthesis process. The superstructure consists of excluding components, gas turbines or conventional steam generators with excluding alternatives of supplying fuel for each combustion system. Also, backpressure or condensing/extraction steam turbine for supplying process steam could be selected. Finally one desalination unit chosen between electrically-driven or steam-driven reverse osmosis, multi-effect and multistage flash should be included. The analysis herein performed is based on energy and mass conservation equations, as well as the technological limiting equation of equipment. The results for ten different commercial gas turbines revealed that electrically-driven reverse osmosis was always chosen together with both natural gas and gasified biomass gas turbines.     

An energy systems engineering approach for the design and operation of microgrids in residential applications

A distributed energy system refers to an energy system where energy production is close to end use, typically relying on small-scale energy distributed technologies. It is a multi-input and multi-output energy system with substantial energy, economic and environmental benefits. However, distributed energy systems such as micro-grids in residential applications may not be able to produce the potential benefits due to lack of appropriate system configurations and suitable operation strategies. The optimal design, scheduling and control of such a complex system are of great importance towards their successful practical realization in real application studies. This paper presents a short review and an energy systems engineering approach to the modeling and optimization of micro-grids for residential applications, offering a clear vision of the latest research advances in this field. Challenges and prospects of the modeling and optimization of such distributed energy systems are also highlighted in this work.     

A systems based approach for financial risk modelling and optimisation of the mineral processing and metal production industry

Large scale engineering process systems are subject to a variety of risks which affect the productivity and profitability of the industry in the long run. This paper outlines the short comings of the current methods of risk quantification and proposes a systems engineering framework to overcome these issues. The functionality of the developed model is illustrated for the case of mineral processing and metal production industries using a copper ore processing and refined metal production case study. The methodology provides a quantitative assessment of the risk factors and allows the opportunity to minimise financial losses, which would help investors, insurers and plant operators in these sectors to make appropriate risk hedging policies. The models developed can also be coupled with evolutionary or swarm based algorithms for optimising the systems. A numerical example is illustrated to demonstrate the validity of the proposition.     

Integrated framework for the design of pipeline systems using stochastic optimisation and GIS tools

This work presents an optimisation framework for the routing and equipment design of main pipelines to be used for fluid transmission. There are many considerations in these design problems, involving various constraints, decisions and the associated costs for the construction, operation, maintenance, etc., of the system. In practice, engineers rely on experience, try out various design alternatives, and use simulators for engineering calculations, cost models, geographical information systems and equipment databases to identify promising options. The present approach proposes a systematic search for optimal and near-optimal solutions. The search is based on stochastic optimisation, and assumes that the same information and simulation tools as in the case of design by trial and error are available. An application example is used to demonstrate the approach and test the robustness of the optimal search using Simulated Annealing.     

Optimal integrated energy systems design incorporating variable renewable energy sources

The effect of variability in renewable input sources on the optimal design and reliability of an integrated energy system designed for off-grid mining operation is investigated via a two-stage approach. Firstly, possible energy system designs are generated by solving a deterministic non-linear programming (NLP) optimization problem to minimize the capital cost for a number of input scenarios. Two measures of reliability, the loss of power supply probability (LPSP) and energy index of reliability (EIR), are then evaluated for each design based on the minimization of the external energy required to satisfy load demands under a variety of input conditions. Two case studies of mining operations located in regions with different degrees of variability are presented. The results show that the degree of variability has an impact on the design configuration, cost and performance, and highlights the limitations associated with deterministic decision making for high variability systems.     

Optimal design of residential cogeneration systems under uncertainty

This paper presents a multi-objective optimization method for designing cogeneration systems in residential complexes and accounting for the involved uncertainty. The model accounts for satisfying the hot water and electric energy demands in a residential complex, while minimizing the total annual cost and the associated greenhouse gas emissions. The proposed model incorporates uncertain data for the ambient temperature, energy demands and prices of the local energy market, which are predicted through forecasting methods for determining the financial and environmental risks. Furthermore, the model accounts for determining the type and size of the central cogeneration unit, thermal storage unit, the needed auxiliary units, as well as the operating conditions. A housing complex in central Mexico is presented as case study. The results show significant economic and environmental benefits for the implementation of the proposed scheme as well as the importance of accounting for the involved uncertainty.     

The optimal design of membrane systems

This paper introduces a novel optimal design strategy for membrane separation systems. This strategy is characterised by two main features: firstly, detailed models are used. This is essential if sub-optimal and inaccurate solutions are to be avoided. Secondly, an optimisation technique based on genetic algorithms is implemented. The feasibility of the optimal design strategy is investigated using a pervaporation case study. To this end, an existing pervaporation plant is evaluated and a significantly improved design is found.     

露天矿连续工艺系统可靠性计算及优化

过去在研究矿山连续工艺系统可靠性时，一般仅注重工艺系统可靠性的计算，对系统的薄弱环节仅定性地提出改进措施，很少进行可靠性优化的研究。本文在介绍连续工艺系统可靠性计算方法的基础上，按照费用最小的原则对系统可靠性进行了优化。     

基于可靠性分析的公用工程操作优化

针对公用工程系统,基于可靠性分析提出新型的操作优化方法。该方法结合关键设备故障分析,采用系统的数学手段计算公用工程系统由于设备故障所产生的所有可能的操作状态及其概率。每一个状态进行单独的操作优化,其经济评价与该状态的概率相加权,以此获得系统整体经济评估。此方法中,设备的操作策略得到优化,如冷备用、热备用、负荷共享等。操作成本与设备故障造成的生产损失成本得以权衡。与传统的优化方法相比,该方法可获得更低的系统总成本。     

Thermo-environomic optimisation strategy for fuel decarbonisation process design and analysis

To meet the CO₂ reduction targets and ensure sustainable energy supply, the development and deployment of cost-competitive innovative low-carbon energy technologies is essential. To design and evaluate the competitiveness of such complex integrated energy conversion systems, a systematic thermo-environomic optimisation strategy for the consistent modelling, comparison and optimisation of fuel decarbonisation process options is developed. The environmental benefit and the energetic and economic costs are assessed for several carbon capture process options. The performance is systematically compared and the trade-offs are assessed to support decision-making and identify optimal process configurations with regard to the polygeneration of H₂, electricity, heat and captured CO₂. The importance of process integration in the synthesis of efficient decarbonisation processes is revealed. It appears that different process options are in competition when a carbon tax is introduced. The choice of the optimal configuration is defined by the priorities given to the different thermo-environomic criteria.     

Conceptual design of a novel hybrid fuel cell/desalination system

A novel concept for integrating fuel cells with desalination systems is proposed and investigated in this work. Two unique case studies are discussed — the first involving a hybrid system with a reverse osmosis (RO) unit and the second — integrating with a thermal desalination process such as multi-stage flash (MSF). The underlying motivation for this system integration is that the exhaust gas from a hybrid power plant (fuel cell/turbine system) contains considerable amount of thermal energy, which may be utilized for desalination units. This exhaust heat can be suitably used for preheating the feed in desalination processes such as reverse osmosis which not only increases the potable water production, but also decreases the relative energy consumption by approximately 8% when there is an increase of just 8°C rise in temperature. Additionally, an attractive hybrid system application which combines power generation at 70%+ system efficiency with efficient waste heat utilization is thermal desalination. In this work, it is shown that the system efficiency can be raised appreciably when a high-temperature fuel cell co-generates DC power in-situ with waste heat suitable for MSF. Results indicate that such hybrid system could show a 5.6% increase in global efficiency. Such combined hybrid systems have overall system efficiencies (second-law base) exceeding those of either fuel-cell power plants or traditional desalination plants.     

Reliability issues in the design and optimization of process utility systems

The reliability of process utility systems is a prime consideration for both their design and operation. This paper combines the optimization of utility system performance with reliability theory based on Markov analysis. Operation mode is first to be considered, e.g. hot standby, cold standby, load-sharing, etc. Downtime during start up has been considered for the first time. When optimising the working load, the downstream processes are also considered, so as to minimize the total penalty cost due to shutting down of the units serviced by the utility system. The proposed methodology combines the operation and design problems and optimizes them simultaneously.     

Computer-aided synthesis and design of plant utility systems

A design synthesis procedure is developed for preliminary design of utility systems. Given known steam sources (waste heat and auxiliary boilers) and sinks (heating, process injection, and driver horsepower needs), the algorithm determines the optimal header pressure levels, the distribution of steam turbines in the network, and the steam flows between all devices so as to maximize the real work recovered from the sources. Any number of pressure levels can be accommodated at only modest increase in computational effort.     

A systematic methodology for the environomic design and synthesis of energy systems combining process integration,Life Cycle Assessment and industrial ecology

This paper presents a systematic methodology for sustainable process systems design, combining the principles of industrial ecology, process design and process integration, Life Cycle Assessment (LCA) and multi-objective optimization (MOO). The superstructure considers an extended decision perimeter and embeds models based either on flowsheeting software or average market technologies, for which energy and material flows are extracted from the Life Cycle Inventory (LCI) database. Therefore, the overall supply chain can be synthesized within a given action system and the systematic recyclings identified. The methodology can be used to design eco-industrial parks or urban systems, to identify the best conversion pathways of resources or waste, or to fix the optimal value of environmental taxes. It is illustrated by an application to the environomic design of an urban energy system. This case study considers multiple energy services to be supplied and waste to be treated, with their seasonal variations, indigenous and imported resources, as well as different candidate conversion technologies. Results demonstrate that integrating an environmental objective in the design procedure leads to consider different system configurations than if only economic aspects are considered. The problematic of the optimal value of a CO₂ tax is as well addressed.     

Multi-objective optimisation using surrogate models for the design of VPSA systems

Vacuum/pressure swing adsorption is an attractive and often energy efficient separation process for some applications. However, there is often a trade-off between the different objectives: purity, recovery and power consumption. Identifying those trade-offs is possible through use of multi-objective optimisation methods but this is computationally challenging due to the size of the search space and the need for high fidelity simulations due to the inherently dynamic nature of the process. This paper presents the use of surrogate modelling to address the computational requirements of high fidelity simulations needed to evaluate alternative designs. We present SbNSGA-II ALM, surrogate based NSGA-II, a robust and fast multi-objective optimisation method based on kriging surrogate models and NSGA-II with the Active Learning MacKay (ALM) design criterion. The method is evaluated by application to an industrially relevant case study: a two column six step system for CO₂/N₂ separation. A 5 times reduction in computational effort is observed.     

Synthesis and optimisation of an integrated water and membrane network framework with multiple electrodialysis regenerators

The shrinking supplies of freshwater globally, coupled with strict environmental regulations, have driven the manufacturing industry towards sustainable water management for the minimisation of freshwater intake and wastewater generation. By using process integration and its enabling tools, this work considers the synthesis of an optimal water network with multiple regeneration capabilities. Development of the proposed framework is achieved by embedding a subnetwork of detailed electrodialysis models within a water network. Based on a superstructure and fixed flowrate, the optimisation problem is formulated as an MINLP model and solved in GAMS/DICOPT. To demonstrate the applicability of the proposed mathematical model a literature case study on a pulp and paper plant is presented and the results indicate a potential of 12% savings in freshwater intake, 16% reduction in wastewater generated and a 14% saving in the total annualised cost for the entire network.