Application of gaussian processes to online approximation of compressor maps for load-sharing in a compressor station

Devising optimal operating strategies for a compressor station relies on the knowledge of compressor characteristics. As the compressor characteristics change with time and use, it is necessary to provide accurate models of the characteristics that can be used in optimization of the operating strategy. This paper proposes a new algorithm for online learning of the characteristics of the compressors using Gaussian Processes. The performance of the new approximation is shown in a case study with three compressors. The case study shows that Gaussian Processes accurately capture the characteristics of compressors even if no knowledge about the characteristics is initially available. The results show that the flexible nature of Gaussian Processes allows them to adapt to the data online making them amenable for use in real-time optimization problems

Improving LNG Facility Reliability and Operability Via OEM Integrated Compressor Controls

Lectur

Influence of compressor degradation on optimal operation of a compressor station

Normal practice in a compressor station with compressors in parallel is to allocate the mass flows equally. However, this strategy is not optimal if the compressors are not identical. A common reason why compressors become non-identical is because their performance degrades over time. Degradation increases the power necessary to run the compressor station and changes the optimal allocation of mass flows. This paper presents a framework for optimal operation in a compressor station with degrading compressors. The optimisation framework proposed in this work explicitly includes a model of degradation in the optimisation problem and analyses how the optimal load-sharing changes when the compressors are degrading. The optimisation framework was applied in an industrial case study of a compressor station in which three parallel compressors are subject to degradation. The case study confirms that it is possible to minimise the extra power consumption due to degradation by adjusting the operating conditions of the compressor station. The analysis also gives insights into the impact of degradation on the optimal solution when compressors work at their limits

Degradation modelling in process control applications

Degradation of industrial equipment is often influenced by how a system is operated, with certain operating points likely to accelerate degradation. The ability to mitigate degradation of an industrial system would result in improved performance and decreased costs of operation. The thesis aims to provide ways for managing degradation by adjusting the operating conditions of a system. The thesis provides original insights and a new classification of models of degradation to facilitate the integration of degradation models into process control applications. The thesis also develops an adaptive algorithm for degradation detection and prediction in turbomachinery, which is able to predict the expected future values of a degradation indicator and to quantify the uncertainty of the prediction. The thesis then proposes two frameworks for load-sharing in a compressor station in which the compressors are subject to degradation. One framework considers management of degradation and the other one focuses on power consumption of the whole station. These examples show how modelling of degradation can have an impact on the operation of an industrial system. The approaches have been evaluated with case studies developed in collaboration with industrial partners. As demonstrated in the case studies, the outcomes of the research presented in this thesis provide new ways to take account of degradation in process control applications. The thesis discusses steps and directions for future work to facilitate the technology transfer from academic to industrial implementation.Open Acces

Real-Time Optimization of Interconnected Systems via Modifier Adaptation, with Application to Gas-Compressor Stations

The process industries are characterized by a large number of continuously operating plants, for which optimal operation is of economic and ecological importance. Many industrial systems can be regarded as an arrangement of several subsystems, where outputs of certain subsystems are inputs to others. This gives rise to the notion of interconnected systems. Plant optimality is difficult to achieve when the model used in optimization is inaccurate or in the presence of process disturbances. However, in the presence of plant-model mismatch, optimal operation can be enforced via specific real-time optimization methods. Specifically, this thesis considers so-called Modifier-Adaptation schemes which achieve plant optimality by direct incorporation of process measurements in the form of first-order corrections. As a first contribution, this thesis proposes a novel problem formulation for modifier adaptation. Specifically, it is focused on plants consisting of multiple interconnected subsystems that allows problem decomposition and application of distributed optimization strategies. The underlying key idea is the use of measurements and global plant gradients in place of an interconnection model. As a second contribution, this thesis investigates modifier adaptation for interconnected systems relying on local gradients by using an interconnection model. We show that the use of local information in terms of model, gradients and measurements is sufficient to optimize the steady-state performance of the plant. Finally, we propose a distributed modifier-adaptation algorithm that, besides the interconnection model and local gradients, employs a coordinator. For this scheme, we prove feasible-side convergence to the plant optimum, where a coordinator ensures that the local optimal inputs computed for each subsystem are consistent with the interconnection model. The experimental effort necessary to estimate the plant gradients increases with the number of plant inputs and may become intractable and sometimes not feasible or reliable for large-scale interconnected systems. The proposed approaches that use the interconnection model and local gradients overcome this problem. As an application case study of industrial relevance, this thesis investigates the problem of optimal load-sharing for serial and parallel gas compressors. The aim of load-sharing optimization is operating compressor units in an energy-efficient way, while at the same time satisfying varying load demands. We show how the structure of both the parallel and serial compressor configurations can be exploited in the design of tailored modifier adaptation algorithms based on efficient estimation of local gradients. Our findings show that the complexity of this estimation is independent of the number of compressors. In addition, we discuss gradient estimation for the case where the compressors are operating close to the surge conditions, which induces discontinuities in the problem

Improving LNG Facility Reliability and Operability Via OEM Integrated Compressor Controls

Lectur

Aeronautical Engineering: A continuing bibliography, supplement 120

This bibliography contains abstracts for 297 reports, articles, and other documents introduced into the NASA scientific and technical information system in February 1980

All-electric LNG a viable alternative to conventional gas turbine driven LNG plant

The world demand for natural gas which is at an increasing trend has rekindled interest in the production and transportation of Liquefied Natural Gas (LNG) from resource rich areas in Africa, Middle East, Far East, Australia and Russia to customers in Europe, Americas, China and India. The challenges for the future are to produce and transport gas in a cost effective manner to be competitive in the market place. Gas is beginning to play an increasingly important role in energy scenario of the world economy. The easiest ways of getting gas to the market is by pipe lines. However to reach markets far and wide across oceans, gas needs to be converted and transported in liquid form. Competitive pressure and search for economies of scale is driving up the size of LNG facilities and hence the capital requirement of each link of the value chain. Interdependent financing of the various links of the value chain, while maintaining their economic viability, is the challenge that sponsors need to address. The industry is potentially a high risk business due to uncertainty associated with the characteristics of the industry, which calls for high level of investment in an environment of volatility of the price and political and economic changes in the world market. LNG production facilities are becoming larger and larger than ever before to take advantage of economies of scale. These massive plants not only have created new challenges in design, procurement and construction and environment but will create new challenges in operation and maintenance. Innovative technologies and first of a kind equipment applications with a rigorous technology development and a stringent testing plans ensure that the facility will achieve a long term reliable operation. Conventional LNG plants use Gas Turbine as main drivers for refrigerant compressors. To this effect All-Electric LNG has a potential to provide an alternative offer a life cycle advantage over the convention. Hence it would be worthwhile to study the pros and cons and prospects offered by this new technology from an overall life cycle perspective for future of LNG projects. This research is an endeavours in this direction