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Abstract: The systematic, transparent and accurate on-line energy information of the production process is quite the basis of mill energy management and conservation. An Energy Management System (EMS) was built according to the characteristics of the energy usage in a typical newsprint paper mill. The EMS first realized the process data acquisition and integration, second fulfilled the on-line energy information calculation from the integrated data. A water and steam properties query component based on IAPWS-IF97 was developed and plugged into the EMS to facilitate the energy calculation of water and steam. The practical performance in the paper mill showed that the integrated energy information of the whole mill was gained and the on-line energy supervisory was achieved. In the end a systematic, transparent and accurate energy usage profile is obtained and it would provide the valuable fundamental energy data for the further energy analysis and optimization in the EMS. [Copyright &y& Elsevier]

Abstract: Water desalination using capacitive deionization (CDI) has been a recent topic of intense research as a novel technique for water desalination, capable of returning a fraction of the input energy during the regeneration of nanoporous electrodes used for ion adsorption. Usually, a set of consecutive and alternating desalination–regeneration processes is conducted to evaluate the performance of this type of systems under different operational conditions (applied electric potential, flow rate, and initial solution concentration). However, the effect of timing for desalination and regeneration processes on the performance of a capacitive deionization system has not been explored yet. This paper analyzes the effect of varying the duration of desalination and regeneration processes on overall system performance for three different salinity levels and three different CDI system sizes. More specifically, the variation in energy recovery ratio, thermodynamic efficiency, and net energy required per moles of salt adsorbed per unit of volume treated are evaluated. To optimize the timing for transient operation, one desalination test was performed until total saturation, which is identified by the outlet concentration returning to inlet concentration. From this experiment, three characteristic times were obtained: one that minimizes the outlet solution concentration, one that gives the highest adsorbed ions per energy input and one that corresponds to maximum average adsorption rate. The results obtained from testing these three timing strategies in an alternating desalination–regeneration process suggest the existence of different optimal operational points, depending on the specific needs, such as maximum desalination rate or maximum energy efficiency. The methodology presented in this paper can be extended to other operational conditions/systems to optimize their energetic performance. [Copyright &y& Elsevier]

Graphical abstract Highlights • A novel AP-DEACM method is proposed. • Performance evaluation and energy optimization model is obtained. • This proposed model is efficient in energy saving and carbon emission reduction. • The energy saving potential of ethylene and PTA production plants are 2.78% and 1.26%. • Carbon emission reduction potential is 3.62% in ethylene production plants. Abstract Data Envelopment Analysis (DEA) has been widely used in performance and energy efficiency evaluation. However, in the traditional DEA, the effective of each decision making unit (DMU) is evaluated through its own optimized perspective and regardless of other DMUs influence, which may result in too many effective DMUs. And the DEA cross-model (DEACM) can distinguish the effective DMUs better by constructing a cross-efficiency matrix, but the optimal weight of the DMU may not be unique, so the cross efficiency of the DEACM may be different. Therefore, this paper proposes a novel DEACM based on the affinity propagation (AP) clustering algorithm (AP-DEACM). Through the AP clustering algorithm, the high impact data affecting the performance capacity and energy saving are obtained. Then the better effective DMU is identified through the high discrimination of the AP–DEACM. Finally, the proposed AP-DEACM is used for performance evaluation and energy optimization modeling of the Pure Terephthalic Acid (PTA) production process and the ethylene industrial process in complex petrochemical industries. The experimental results show that the energy saving potential of PTA production plants and ethylene production plants are 2.78% and 1.26%, respectively, and the average value of carbon emission savings potential is 3.62% in ethylene production plants. [ABSTRACT FROM AUTHOR]

In recent years there has been increased concern on energy efficiency of industries. Since the scheduling problems in the shop floors are directly related to the energy consumption, an appropriate way to improve energy efficiency in industrial plants is to develop effective scheduling strategies. Hence, the aim of this paper is to design an energy-efficient scheduling in a shop floor industrial environment, i.e., flexible job-shop scheduling problem (FJSP). To this end, a multi-objective optimization model is developed with three objective functions: (i) minimizing total completion time, (ii) maximizing the total availability of the system, and (iii) minimizing total energy cost of both production and maintenance operations in the FJSP. To cope with this multi-objective optimization problem, an enhanced evolutionary algorithm incorporated with the global criterion, as a multi-objective handling technique, is proposed and then performance evaluation is performed based on an extensive numerical analysis. [ABSTRACT FROM AUTHOR]

In many modern buildings, different monitoring and control systems are used, but majority of them are not directly connected with the energy consumption optimisation. This paper presents a concept of an integrated performance monitoring system for promotion of energy awareness in buildings. The reference architecture of the envisioned system evolved from the traditional management structure, plan-do-check-act model. Traditional plan-do-check-act model has been upgraded with the integration of prediction engine, knowledge repository and modern scientific approaches for supporting energy awareness including early warning, optimisation and supervision. The proposed concept is constituted upon three modules: (1) data acquisition and processing, (2) knowledge repository, (3) performance monitoring system including prediction engine, consumption modelling, emissions calculation and decision support. The concept of three modules evolved from the idea to enrich existing solutions with the awareness about possible future abnormal situations and to enable preventive actions. Presented case study represents a repeatable application of the energy cost centres based modelling of energy consumption in educational and research buildings by using neuro-fuzzy modelling approach. Initial testing results are indicating the potential of electricity savings up to 15% enabled by visualisation and awareness about electricity consumption. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents an efficient intelligent tool applied to phasor measurements and frequency tracking of fundamental components for PMU application. The estimation task is modeled as an optimization problem in order to use genetic algorithms to search for optimal solutions. Very promising results are presented. This approach is compared to traditional methods considering the IEEE C37.118 standard and the results show that this intelligent tool offers better performance, especially during transient events, considering traditional methods. The proposed approach is implemented in hardware using FPGAs to take advantage of the intrinsic parallelism of genetic algorithms, making it applicable to real-time estimations. [Copyright &y& Elsevier]

Abstract: This paper presents a comprehensive global uncertainty and sensitivity analysis of daylighting and energy performance for private offices with automated interior roller shades using an advanced integrated thermal and lighting simulation model. The purpose was to identify the more important factors with respect to building thermal and lighting energy performance so as to facilitate decision making in building design stage and simplify further investigation such as optimization analysis. Seven studied parameters were selected: window-to-floor ratio, shading transmittance, shading front and back reflectance, space aspect ratio, insulation thermal resistance and glazing type. The performance metrics include useful daylight illuminance (500–2000lux), annual lighting, heating and cooling demand per unit floor area and annual source energy consumption per unit floor area. The uncertainty analysis is based on the Monte Carlo method with Latin Hypercube Sampling, showing the possible ranges in these performance indices. The sensitivity analysis uses a variance-based method in the extended FAST implementation. Application of the analysis to perimeter private office spaces for the climate of Philadelphia showed the first order and total order effects of each studied parameter to determine the building parameters that have the most significant impact. Results are presented for different facade orientations. [Copyright &y& Elsevier]

Abstract: This paper discusses the issue of selecting the design solution that best accords with an articulated preference of multiple criteria with an acceptable performance band. The application of a newly developed multi-criteria decision-making tool called RR-PARETO2 is presented. An example of HVAC design is used to illustrate how solutions could be selected within a multi-criteria optimization framework. In this example, five criteria have been selected, namely, power consumption, thermal comfort, risk of airborne infection of influenza and tuberculosis and effective differential temperature (Δt eq) of body parts. The goal is to select the optimal air exchange rate that makes reasonable trade-offs among all the objectives. Two scenarios have been studied. In the first scenario, there is an influenza outbreak and the important objective is to prevent the spread of infection. In the second scenario, energy prices are high and the primary objective is to reduce energy. In both scenarios, RR-PARETO2 algorithm selects solutions that make reasonable trade-offs among conflicting objectives. The example illustrates how objectives such as reduction of airborne disease transmission and maximizing thermal comfort can be incorporated in the design of a practical, full-scale HVAC system. [Copyright &y& Elsevier]

Abstract: Coupling exothermic with endothermic reactions is proposed as a significant improvement in reactor performance and energy integration. Furthermore, it forms an initial step for process optimization using pinch method. Through coupling of the exothermic reaction with endothermic one, oxidation with reduction, dehydrogenation with hydrogenation, hydration with dehydration, and even a series of tandem reactions, the utilization of energy and materials can be optimized. The underlying goal of this paper is to provide an extensive review through the years 1994–2011 of coupling exothermic and endothermic reactions as an important measure in process integration and intensifying. Developments in coupled reactions, classifying suitable reactors for couplings and categorizing several types of coupling exothermic and endothermic reactions are investigated in this study. Finally, various information concerning coupled reactions are presented in tables. Superiorities of novel models (coupled configurations) to the conventional configurations are clarified. Ultimately, various suggestions are proposed for further work. Results show that the short distance between heat sink and heat source can increase the efficiency of the heat transfer meanwhile incorporating two separated processes with coupled reactors can reduce the size of equipment. [Copyright &y& Elsevier]

Abstract: This paper discusses energy savings in wastewater processing plant pump operations and proposes a pump system scheduling model to generate operational schedules to reduce energy consumption. A neural network algorithm is utilized to model pump energy consumption and fluid flow rate after pumping. The scheduling model is a mixed-integer nonlinear programming problem (MINLP). As solving a data-driven MINLP is challenging, a migrated particle swarm optimization algorithm is proposed. The modeling and optimization results show that the performance of the pump system can be significantly improved based on the computed schedules. [Copyright &y& Elsevier]

Abstract: Apparent window size contradictions arise when optimizing simultaneously for low energy (small sizes) and visual comfort (large sizes). Diverse multi-objective optimization methods exist, but basic questions must be solved beforehand such as choosing appropriate evaluation measures. This work aims to determine the suitability of combined optimization criteria on window sizing procedures for low energy consumption with high visual comfort and performance. The paper showcases diverse measures available to valorise energy consumption and visual aspects. A series of energy and visual criteria were selected, defining acceptance thresholds for dynamic evaluations. Whole-building computer simulations were performed on a standardized office located in a temperate climate. Discrete window-to-wall ratio variations were studied to demonstrate how these criteria affect the solution space. Results were classified using a graphical optimization method, obtaining a solution space satisfying both energy and visual requirements. Most project expectations can be met within the range of sizes. However, unprotected windows barely meet acceptance criteria, needing additional control devices. Applying various related criteria with adequate values increases the diversity of acceptable solutions but too many limits it. Clear objectives and acceptance ranges have to be conceptualized in order to translate them into decisions. This becomes important when involving team design. [Copyright &y& Elsevier]

Abstract: All electronic devices, due to Joule effect, present heat dissipation, when they are electrically fed. The heat overstocking produces efficiency and performances reduction. On account of this the thermal control is mandatory. On small electronic equipments, the difficulty or impossibility of using a cooling fluid for the free or forced convection heat dissipation imposes the presence of cooling systems based on another kind of functioning principle such as the conduction. In this paper the thermal control, via pyroelectric materials, is presented. Furthermore, an optimisation of geometric, thermal and mechanical parameters, influencing the thermal dissipation, is studied and presented. Pyroelectric materials are able to convert heat into electrical charge spontaneously and, due to this capability, such materials could represent a suitable choice to increase the heat dissipation. The obtained electric charge or voltage could be used to charge a battery or to feed other equipments. In particular, a sequence of different materials such as , molybdenum or copper–tungsten, used in a multi-layer pyroelectric wafer, together with their thicknesses, are design features to be optimised in order to have the optimal thermal dissipation. The optimisation process is performed by a hybrid approach where a genetic algorithm (GA) is used coupled with a local search procedure, in order to provide an appropriate balance between exploration and exploitation of the search space, which helps in the search for the optimal or quasi-optimal solution. Since the design variables used in the optimisation procedure are defined in different domains, discrete (e.g. the number of layers in the pyroelectric wafer) and continuous (e.g. the layers thickness) domains, the genetic representation for the solution should take it into account. The chromosome used in the genetic algorithm will mix both integer and real values, what will also be reflected in the genetic operators used in the optimisation process. Finally, numerical analyses and results complete the work. [Copyright &y& Elsevier]

Abstract: Improving the heating performance of district heating networks (DHNs), one of the most important components in district heating systems, has significant influence on the promotion of energy efficiency. Based on the entransy theory, this paper develops an entransy dissipation-based method for global optimization of DHNs. We analyze the irreversibility of three types of heat transfer processes in DHNs: (1) the heat transfer process between the waters in primary heating networks and DHNs in substation heat exchangers; (2) the heat transfer process between supply water and indoor airs in radiators; and (3) the return water mixing process, then derive the expressions of entransy dissipation for each process, and finally deduce two different formulas of the total entransy dissipation in DHNs by the users’ demands and the structural and operating parameters of DHNs, respectively, from which we establish the mathematical relation between the users’ demands and the structural and operating parameters of DHNs. Based on this relation, two typical optimization problems of DHNs are converted into conditional extremum problems to deduce two optimization equation groups. Solving the equation groups gives the optimal structural and operating parameters for DHNs with highest energy efficiency. Finally, the method is proved valid and advantageous through the optimization for both 1-column-2-user and 2-column-4-user DHNs. [Copyright &y& Elsevier]

Abstract: The optimization of building cooling heating and power (BCHP) system is helpful to improve its comprehensive performance including energetic, economic and environmental aspects. However, the optimal results are closely dependent on the initial setting parameters. This paper deduces the energy consumption of BCHP system following the electrical load and presents the optimization problem of BCHP system that includes the decision variables, the objective function, the constraint conditions and the solution method. The influences of the initial parameters, which include the technical, economic and environmental parameters, the building loads and the optimization setting parameters, on the optimal decision variables and the performances of BCHP system are analyzed and compared. The contour curves of the performances of BCHP system in comparison to the conventional separation production (SP) system, and the sensitivity of the optimal decision variables to the initial parameters are obtained. [Copyright &y& Elsevier]

Abstract: The present paper reports a numerical investigation of spatial optimization of heat-exchanger by acting on its positioning in the vehicle’s cooling module. This analysis also elucidates how to act on the different parameters influencing heat-exchanger performance in order to optimize their functioning. A two-dimensional computation code permits optimizing the performance of the cooling module by positioning different heat exchangers, in both the driving and stop phases of the vehicle. The ultimate aim is to apply new control approaches to real vehicles so as to reduce pump and compressor energy consumption and thus fuel consumption. Compared to a reference “in-series” configuration of the cooling module HXs (in which the different HXs are superposed in the airflow direction), an “in-parallel” configuration (in which the different HX surfaces are in a row with respect to the air flow direction) increases the thermal power of the HXs by 4.4% and decreases the pressure losses by 0.9%. [Copyright &y& Elsevier]