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Abstract The combined production of electricity, heat and cold by a polygeneration system connected to a district heating and cooling network can provide high energy utilization efficiency. The inherent complexity of simultaneous production of different services and the high variability in the energy demand make combined cooling and heating systems performance highly dependent on the operational strategy. In this paper, an operational optimization method based on the moving average of real-time measurements of energy demands and ambient conditions is proposed. Real energy demand data from a district heating and cooling network close to Barcelona, Spain, are used to test the method. A complex polygeneration system is considered, consisting of an internal combustion engine, a double-effect absorption chiller, an electric chiller, a boiler and a cooling tower. A detailed modelling of the system is provided, considering partial load behavior of the components and ambient conditions effects. Results of the real-time optimal management are discussed and compared to traditional operational strategies and to the ideal optimal management achievable with perfectly accurate forecast of energy demands. Moreover, the optimal width of the window adopted for the moving average of real-time data is identified.

Energy consumption is now one of the most important issues for network carriers, since the majority of the energy needed for their operation is consumed in the wireless access and optical transport networks. The continuous growth in the wireless customers and traffic volumes and the consequent energy demand on modern carriers’ broadband infrastructures require reconsidering their energy efficiency, by starting from the formulation of new, more complete and representative network models that should become the foundations for modern energy-aware control plane architectures. Accordingly, this work presents a novel comprehensive energy model for next-generation wireless access-over-optical-transport networks characterized by hybrid power systems (i.e., multiple dynamically available power sources). The objective is to identify the energy-related information that need to be handled at the control plane layer to support energy-aware networking practices. Such information can be made available to suitable energy-aware routing and wavelength assignment algorithms that may exploit them to optimize the overall network energy-consumption and reducing the associated carbon footprint. The proposed model may be taken as a reference for the implementation of new energy-aware control plane protocols (routing and signaling) that make use of power-related considerations to achieve energy-efficiency and energy-awareness in wavelength-routed network infrastructures. Peer Reviewed

Abstract Distillation of close-boiling mixtures, such as propylene–propane and ethyl benzene–styrene systems, is an energy intensive process. Vapor recompression techniques and heat pumping-assisted columns have been adopted for such applications for their high potential of energy savings. In direct vapor recompression columns, the vapors leaving the top of the column are compressed, and in the reboiler of the same column, these vapors are condensed to provide heat for vapor generation. Internal heat integrated distillation columns or iHIDiCs are new developments employing the same concept of vapor recompression. These new column configurations can have significantly lower energy demands than common vapor recompression units. In iHIDiCs, rectifying section is operated at a higher pressure (i.e. higher temperature) than in stripping, and therefore its heat can be used to generate vapor in stripping section. So far, design of these column configurations is performed based on engineering experience, simulation or experimental studies on given cases, including dynamic control simulations. Within previous and most recent research efforts on iHIDiCs, there exist no generalized design methods or systematic approaches for design of these internal integrated distillation columns. The present paper presents a systematic design procedure for iHIDiCs. A design hierarchy for iHIDiCs is developed, which includes two phases of design, thermodynamic and hydraulics. This design procedure is applied using commercial simulation-based design methods. In thermodynamic design, temperature profiles for column sections are used as a design tool to guide designers. On the other hand, hydraulic capacities of stages for heat exchange are analyzed to determine the maximum physical space area available for heat exchange. Hence, feasibility regions for both heat integration and hydraulic design are identified.

Abstract An electrolyte solution of Lithium Bromide (LiBr) water was chosen for study because of its wide use in prototype absorption machines. The LiBr must be operated close to the temperature and mass fraction at which lithium bromide achieves the highest efficiency. For the purpose of establishing the concentration in a prototype absorption machines, measurements were made of the properties that vary with temperature and concentration. The selected properties are electrical conductivity, density, refractive indexes and sound velocity. The resulting measured properties values were compared with some values found in previous works. The properties of aqueous lithium bromide solutions were measured at the concentration range of 45–65% of LiBr and temperatures range of 20–80 °C. Semi-empirical correlations that determine the properties of lithium bromide are also proposed. The methods for measuring the properties of aqueous solutions were considered taking into account their reliability, simplicity and sampling time.

Abstract Liquefied Natural Gas (LNG) is becoming vital in relation to energy transition and fighting climate change. Because of its cryogenic temperature (111 K), LNG is an exergy “mine” that can be exploited in the regasification process for multiple industrial applications. But this exergy is usually wasted. This research presents a Combined Cold and Power (CCP) system with exergy recovery from LNG-regasification. This exergy is exploited for the combined production of electricity and low-temperature refrigeration distributed through a CO 2 District Cooling Network. These systems entail many benefits, but also pending challenges. The CCP system is modelled using real operation data, and its performance is analyzed and benchmarked against that of a cryogenic power plant, both at design and off-design operating conditions. The proposed CCP system reports an equivalent electricity saving of 139 kWh/t-LNG with an exergetic efficiency of 40%, turning into useful energy up to 64% of the maximum cold recoverable in the regasification process. The performance enhances as the heat source temperature rises. Higher LNG flow rates contribute to increase the electricity and refrigeration production, but irreversibilities also increase. Finally, findings show that a low LNG regasification pressure is preferable in spite of the negative effect on the power generation.

A novel protocol for the synthesis of complex framework compounds containing a VCP fragment is presented by means of UV conversion of CP derivatives at r.t., providing high yields of target products in an unprecedented atom economical reversible step.

Abstract Multi-objective optimization has recently emerged as a useful technique in sustainability analysis, as it can assist in the study of optimal trade-off solutions that balance several criteria. The main limitation of multi-objective optimization is that its computational burden grows in size with the number of objectives. This computational barrier is critical in environmental applications in which decision-makers seek to minimize simultaneously several environmental indicators of concern. With the aim to overcome this limitation, this paper introduces a systematic method for reducing the number of objectives in multi-objective optimization with emphasis on environmental problems. The approach presented relies on a novel mixed-integer linear programming formulation that minimizes the error of omitting objectives. We test the capabilities of this technique through two environmental problems of different nature in which we attempt to minimize a set of life cycle assessment impacts. Numerical examples demonstrate that certain environmental metrics tend to behave in a non-conflicting manner, which makes it possible to reduce the dimension of the problem without losing information.

Póster presentado en ESCAPE-21, 21st European Symposium on Computer‐Aided Process Engineering, May 29-June 1, 2011, Chalkidiki, Thessaloniki, Greece. This work introduces a systematic method for the optimization of absorption cycles by combining the capabilities of simulation packages and optimization tools, including the Life Cycle Assessment (LCA). The case presented is a multi objective mixed-integer nonlinear programming (moMINLP) problem that is decomposed following the outer-approximation schema. The primal level entails the solution of the nonlinear programming (NLP) subproblem, where the binary variables are fixed. The master is a specially tailored mixed integer linear programming (MILP) problem. The NLP subproblems are solved by combining gradient-based NLP solvers (i.e., fmincon) linked with rigorous process simulation (Aspen Plus®). The methodology is tested using an absorption cooling system. The results obtained and the corresponding Paretto Curves of optimal design show that the objective function can be significantly reduced with the presented methodology. Financial support from the Consellería de Educación of the Generalitat Valenciana (BEST/2010/085) and Ministerio de Ciencias e Innovación (PPQ, CTQ2009-14420-C02-02).