Zhigang Shang

A transhipment model for the optimisation of steam levels of total site utility system for multiperiod operation

A new approach for the optimisation of steam levels of total site utility systems satisfying varying utility demands is presented, accounting for interactions between total site utility systems and chemical processes. The optimisation problem involves the selection of the steam levels with respect to their temperatures. In this paper, by exploiting total site analysis techniques, a new transhipment network is developed to represent the heat flows of a total site. Base on the transhipment network representation of the total site, a general multi-period mixed-integer linear programming (MILP) model is presented for identifying the optimal steam levels of the total site utility system. By using engineering and thermodynamic knowledge, a boiler hardware model (BHM) is developed to describe the performance of boilers, and the turbine hardware model (THM) is applied for the shaft-work targeting of steam turbines. Both models are capable of predicting the real efficiency trends of the units. The application of the proposed optimisation approach is illustrated through two case studies including single operation scenario and multiple operation scenarios.

Agent-based intelligent system development for decision support in chemical process industry

This paper presents an agent-based intelligent system to support coordinate manufacturing execution and decision-making in chemical process industry. A multi-agent system (MAS) framework is developed to provide a flexible infrastructure for the integration of chemical process information and process models. The system comprise of a process knowledge base and a group of functional agents. Agents in the system can communicate and cooperate with each other to exchange and share information, and to achieve timely decisions in dealing with various scenarios in process operations and manufacturing management. Process simulation, artificial intelligent technique, rule-based decision supports are integrated in this system for process analysis, process monitoring, process performance prediction and operation suggestion. The implementation of this agent-based system was illustrated with two case studies, including one application in process monitoring and process performance prediction for a chemical process and one application in de-bottlenecking of a site utility system.

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

Abstract Large amounts of gaseous emissions are generated by combustion processes associated with the utility systems. The emissions include SOx, CO2, CO, NOx, 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.

An integrated mathematical programming approach for the design and optimisation of offshore fields

The paper presents a systematic methodology for the optimal design and operational management of offshore oil fields. It is comprised of two stages. At the design stage, the optimal production capacity of a main field is determined with an adjacent satellite field and a well drilling schedule. The problem is formulated as a mixed-integer linear programming formulation. Continuous variables represent individual well, jacket and topsides costs. Binary variables are used to select individual wells within a defined field grid. The mathematical formulation is concise and efficient. An MINLP model is proposed for the operational management optimisation of the offshore oilfields. In the latter model, non-linear equations are extensively used to model the pressure drops in pipes and wells for multiphase flow. Non-linear cost equations have been derived for the production costs of each well accounting for the length, the production rate and their maintenance. Operational decisions determine the oil flowrates, the operation/shut-in for each well and the pressures for each point in the piping network.

A two-stage optimisation approach to the design of water-using systems in process plants

Abstract The minimisation of water and waster flows is an objective of increasing value in industries. The paper presents a systematic optimisation approach for the design of the water-using systems in process plants with minimum water usage and capital investment. The proposed approach combines the benefits of water-pinch concepts and mathematical programming techniques. It follows a two-stage procedure, namely targeting stage and network design stage. Both stages rely on the optimisation of a superstructure model with all possible connections between (i) freshwater sources and operations, and (ii) different water-using operations. The approach facilitates the inherent combinatorial nature of the design problem and solves it efficiently.

Synthesis, optimal planning and scheduling for process plant utility systems

Abstract A systematic methodology is presented for the synthesis, optimal planning and scheduling of plant utility systems. The methodology first addresses long-term synthesis and planning problems and continues with short-term maintenance scheduling applications. The synthesis approach determines new units, their layout, their number and capacities, as well as the operating strategies appropriate in view of process variations. The scheduling problem methodology determines maintenance, along with shut-down and start-up schedules for uncertain operational scenarios. The optimisation technology is applied in the form of natural decomposition schemes.

Agent-based Global Energy Management Systems for the Process Industry

Energy utility systems are typically responsible for satisfying internal customers (e.g., the various process plants in the industrial complex). The increasing independence of business units in the complex matches an emerging trend in the utility systems to operate for own economic viability and for the encouragement to trade with both internal and external customers. The paper presents a dynamic management system supporting autonomy and the optimal operation of the utility system. The management system comprises three functional components, which support negotiation, short-term (tactical) and long-term (strategic) optimisation. The negotiation component involves an agent-based system exploiting the knowledge base established with real-time and historical data, whereas the optimisation provides a primal front (operational changes) and background front (structural changes) to account for the tactical and strategic decisions.

Optimisation of integrated gasification combined cycles in refineries

Abstract In this paper, a systematic methodology has been presented for the optimal integration of the IGCC systems with the exiting refinery infrastructure, the hydrogen network and the utility network. The proposed approach determines the new unit investment scheme for the existing refineries, as well as operational strategies of all the units in order to maximise the annual profit taking into account the annualised capital cost. The proposed methodology follows a two-stage procedure, namely analysis stage and optimisation stage. The analysis stage screens among various integration alternatives and identify the promising options considering the trade-off between the economic and environmental benefits and the capital expenditure. Because only economically viable options are included, the superstructure will be potentially much smaller than a general superstructure which includes all the candidate options. With a reduced superstructure, the mathematical optimisation problem is formulated as an NLP model which can be solved effectively even for large problems.

A multicriteria process synthesis approach to the design of sustainable and economic utility systems

Abstract The proper design criteria for a modern utility plant should include both environmental and economic requirements. In other words, not only the capital and operating costs of a utility plant but also the corresponding utility wastes must be minimised. The paper presents a systematic multicriteria process synthesis approach for designing sustainable and economic utility systems. The proposed approach enables the design engineer to systematically derive optimal utility systems which are economically sustainable and economic by embedding Life Cycle Assessment (LCA) principles within a multiple objective optimisation framework. It combines the merits of total site analysis, LCA, and multi-objective optimisation techniques

Agent-enabled dynamic management system for process plants

Abstract The paper presents an agent-enabled environment to support decisions and the dynamic trading of utility services. The developments are set up to emulate different departments of a total site, individual production processes, the utility system, and trading departments. The proposed approach reviews ways to assess investment schemes, as well as design and operational scenarios. The agents make use of knowledge models that communicate with individual processes and assess scenarios for energy efficiency. Optimization models take into account objectives for improvements, whereas agents take into account the dynamics of the communication. Knowledge and optimization models are linked with databases that contain planning and operational data useful to manage and support decisions. The approach is illustrated with two case studies.