Waste heat recovery via organic rankine cycle: results of a era-SME technology transfer project

The main goal of the EraSME project “Waste heat recovery via an Organic Rankine Cycle”, completed by partners Howest (Belgium), Ghent University (Belgium) and University of Applied Sciences Stuttgart (Germany) between 1 January 2010 and 31 December 2012, was to find an entrance in Flanders for the Organic Rankine Cycle (ORC) technology in applications with sufficient amounts of waste heat at high enough temperatures. The project was preceded by a similar study that focused on renewable energy sources. Several tools were developed to aid in the viability assessment, the selection, and the sizing of ORC installations. With these methods, a fast determination of feasibility is possible. The outcome is based on the size, nature and temperature of the waste heat stream as well as the electricity price. An estimate can be given of the net power output, the investment costs and the economic feasibility. The tool is linked to a database of ORC manufacturer specifications. Another objective of the project was to keep track of the evolution in ORC market supply, both commercial and precommercial. We also looked beyond the product line of the main manufacturers. Some ORCs are developed for specific applications. ORC technology was benchmarked against alternatives for waste heat recovery, such as: steam turbines, heat pumps and absorption cooling. ORC in or as a combined heat and power (CHP) system was also examined. A laboratory test unit of 10kWe nominal power was installed during the project, which is now used in further research on dynamic behavior and control. It is still the only ORC demonstration unit in Flanders and has been very instructive in introducing representatives from industry, researchers and students to the technology. A considerable part of the project execution consisted of case studies in response to industrial requests from several sectors. Detailed and concrete feasibility studies allowed us to define the current application area of waste heat recovery ORC in a better way. A knowledge center for waste heat recovery (www.wasteheat.eu) was initiated to consolidate the know-how and to advise potential users

Virtual sector profiles for innovation sharing in process industry : sector 01: chemicals

Production data in process industry are proprietary to a company since they are key to the process design and technology expertise. However, data confidentiality restrains industry from sharing results and advancing developments in and across process sectors. Using virtual profiles that simulate the typical operating modes of a given process industry offers an elegant solution for a company to share information with the outside world. This paper proposes a generic methodology to create sector blueprints and applies it to the chemicals industry. It details the profile of a typical chemical site based on essential units and realistic data gathered from existing refineries and chemical plants

DEAN: A program for dynamic engine analysis

The Dynamic Engine Analysis program, DEAN, is a FORTRAN code implemented on the IBM/370 mainframe at NASA Lewis Research Center for digital simulation of turbofan engine dynamics. DEAN is an interactive program which allows the user to simulate engine subsystems as well as a full engine systems with relative ease. The nonlinear first order ordinary differential equations which define the engine model may be solved by one of four integration schemes, a second order Runge-Kutta, a fourth order Runge-Kutta, an Adams Predictor-Corrector, or Gear's method for still systems. The numerical data generated by the model equations are displayed at specified intervals between which the user may choose to modify various parameters affecting the model equations and transient execution. Following the transient run, versatile graphics capabilities allow close examination of the data. DEAN's modeling procedure and capabilities are demonstrated by generating a model of simple compressor rig

Carbon capture from natural gas combined cycle power plants: Solvent performance comparison at an industrial scale

Natural gas is an important source of energy. This article addresses the problem of integrating an existing natural gas combined cycle (NGCC) power plant with a carbon capture process using various solvents. The power plant and capture process have mutual interactions in terms of the flue gas flow rate and composition vs. the extracted steam required for solvent regeneration. Therefore, evaluating solvent performance at a single (nominal) operating point is not indicative and solvent performance should be considered subject to the overall process operability and over a wide range of operating conditions. In the present research, a novel optimization framework was developed in which design and operation of the capture process are optimized simultaneously and their interactions with the upstream power plant are fully captured. The developed framework was applied for solvent comparison which demonstrated that GCCmax, a newly developed solvent, features superior performances compared to the monoethanolamine baseline solvent

Relating Maxwell's Demon and Quantitative Analysis of Information Leakage for Practical Imperative Programs

International audienceShannon observed the relation between information entropy and Maxwell demon experiment to come up with information entropy formula. After that, Shannon's entropy formula is widely used to measure information leakage in imperative programs. But in the present work, our aim is to go in a reverse direction and try to find possible Maxwell's demon experimental setup for contemporary practical imperative programs in which variations of Shannon's entropy formula has been applied to measure the information leakage. To establish the relation between the second principle of thermodynamics and quantitative analysis of information leakage, present work models contemporary variations of imperative programs in terms of Maxwell's demon experimental setup. In the present work five contemporary variations of imperative program related to information quantification are identified. They are: (1) information leakage in imperative program (2) imperative multithreaded program (3) point to point leakage in the imperative program (4) imperative program with infinite observation and (5) imperative program in the SOA-based environment. For these variations, minimal work required by an attacker to gain the secret is also calculated using historical Maxwell's demon experiment. To model the experimental setup of Maxwell's demon, non-interference security policy is used. In the present work, imperative programs with one-bit secret information have been considered to avoid the complexity. The findings of the present work from the history of physics can be utilized in many areas related to information flow of physical computing, nano-computing, quantum computing, biological computing, energy dissipation in computing and computing power analysis

Levelised Cost of Storage for Pumped Heat Energy Storage in comparison with other energy storage technologies

Future electricity systems which plan to use large proportions of intermittent (e.g. wind, solar or tidal generation) or inflexible (e.g. nuclear, coal, etc.) electricity generation sources require an increasing scale-up of energy storage to match the supply with hourly, daily and seasonal electricity demand profiles. Evaluation of how to meet this scale of energy storage has predominantly been based on the deployment of a handful of technologies including batteries, Pumped Hydroelectricity Storage, Compressed Air Energy Storage and Power-to-Gas. However, for technical, confidentiality and data availability reasons the majority of such analyses have been unable to properly consider and have therefore neglected the potential of Pumped Heat Energy Storage, which has thus not been benchmarked or considered in a much detail relative to competitive solutions. This paper presents an economic analysis of a Pumped Heat Energy Storage system using data obtained during the development of the world’s first grid-scale demonstrator project. A Pumped Heat Energy Storage system stores electricity in the form of thermal energy using a proprietary reversible heat pump (engine) by compressing and expanding gas. Two thermal storage tanks are used to store heat at the temperature of the hot and cold gas. Using the Levelised Cost of Storage method, the cost of stored electricity of a demonstration plant proved to be between 2.7 and 5.0 €ct/kW h, depending on the assumptions considered. The Levelised Cost of Storage of Pumped Heat Energy Storage was then compared to other energy storage technologies at 100 MW and 400 MW h scales. The results show that Pumped Heat Energy Storage is cost-competitive with Compressed Air Energy Storage systems and may be even cost-competitive with Pumped Hydroelectricity Storage with the additional advantage of full flexibility for location. As with all other technologies, the Levelised Cost of Storage proved strongly dependent on the number of storage cycles per year. The low specific cost per storage capacity of Pumped Heat Energy Storage indicated that the technology could also be a valid option for long-term storage, even though it was designed for short-term operation. Based on the resulting Levelised Cost of Storage, Pumped Heat Energy Storage should be considered a cost-effective solution for electricity storage. However, the analysis did highlight that the Levelised Cost of Storage of a Pumped Heat Energy Storage system is sensitive to assumptions on capital expenditure and round trip efficiencies, emphasising a need for further empirical evidence at grid-scale and detailed cost analysis

Control and optimization of a three-phase catalytic slurry intensified continuous chemical reactor

International audienceIntensified continuous mini-reactors working in high pressure and temperature conditions are particularly effective at coping with mass transfer limitations during three-phase catalytic reactions. They are highly non-linear, multivariable systems and behave differently from conventional batch, fed-batch or continuous non-intensified reactors. In this paper, the optimization and control of this new process are presented using a two-layer approach consisting of a hierarchical control structure with an optimization layer which calculates the set points for an advanced controller. The latter is based on the concavity of the entropy function and the use of thermodynamic availability as a Lyapunov function. The three-phase catalytic o-cresol hydrogenation performed under high pressure and temperature in a small-scale pilot of the RAPTOR® reactor designed by the French company AETGROUP SAS, is taken as a representative test example to illustrate the strategy. The performance of the control structure is illustrated by simulation

Cyber physical security of avionic systems

“Cyber-physical security is a significant concern for critical infrastructures. The exponential growth of cyber-physical systems (CPSs) and the strong inter-dependency between the cyber and physical components introduces integrity issues such as vulnerability to injecting malicious data and projecting fake sensor measurements. Traditional security models partition the CPS from a security perspective into just two domains: high and low. However, this absolute partition is not adequate to address the challenges in the current CPSs as they are composed of multiple overlapping partitions. Information flow properties are one of the significant classes of cyber-physical security methods that model how inputs of a system affect its outputs across the security partition. Information flow supports traceability that helps in detecting vulnerabilities and anomalous sources, as well as helps in rendering mitigation measures. To address the challenges associated with securing CPSs, two novel approaches are introduced by representing a CPS in terms of a graph structure. The first approach is an automated graph-based information flow model introduced to identify information flow paths in the avionics system and partition them into security domains. This approach is applied to selected aspects of the avionic systems to identify the vulnerabilities in case of a system failure or an attack and provide possible mitigation measures. The second approach is based on graph neural networks (GNN) to classify the graphs into different security domains. Using these two approaches, successful partitioning of the CPS into different security domains is possible in addition to identifying their optimal coverage. These approaches enable designers and engineers to ensure the integrity of the CPS. The engineers and operators can use this process during design-time and in real-time to identify failures or attacks on the system”--Abstract, page iii