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Abstract: The paper industry is, with about 6% of the total worldwide industrial energy use, an energy-intensive industry. The drying section is with approximately 50% the largest energy consumer in a paper mill, energy use in this section is mainly heat use. Several options to decrease heat use in conventional multi-cylinder drying sections are investigated, calculating the effect on energy use. Optimization measures include a) decreasing the amount of water evaporation by applying additives in higher consistencies and by lowering the water viscosity, b) decreasing the heat use of water evaporation by increasing the dew point temperature of the dryer and c) increasing the amount of heat recovery by using exhaust air to not only pre-heat the incoming air but also to increase process water temperatures. These could all be achieved by retrofitting and/or choosing different processing conditions in existing factories. The combined thermal heat saving potential due to the optimization actions is 1.3GJh/t paper (or 32% of the drying section’s heat use) as compared to the reference situation. [ABSTRACT FROM AUTHOR]

Highlights • A electromechanical servo-axis model is defined to evaluate axis losses. • A continuous optimization procedure is defined by interpolating discrete catalogs. • The optimal motor-reducer is found minimizing energy consumption, axis size. • Optimization is applied to two case studies, choosing optimal motor-reducer pairs. Abstract This papers deals with the optimal selection of motors and reducers in servo-controlled machines. A model of an electromechanical servo-axis is developed, which allows electrical and mechanical losses to be evaluated. The model is based on data that can be extracted from commercial catalogs, thus requiring no experimental characterization. Then, a novel optimal selection procedure is presented, called continuous optimization, based on the extension of a discrete commercial catalog to a continuous one, by means of data fitting on the electromechanical parameters that influence the motor and reducer operation. A non-linear constrained optimization problem is solved in order to find the optimal motor-reducer unit with respect to a variety of objective functions, such as motor size, overall energetic efficiency, total mass, etc. [ABSTRACT FROM AUTHOR]

Abstract The cell-free massive MIMO (multiple-input multiple-output) system involves a large number of access points serving a smaller number of mobile users (MUs) over identical time/ frequency resource. By providing large number of service antennas closer to the MUs, the cell-free massive MIMO can offer great spectral efficiency, better macro-diversity and minimal path loss. Despite several advantages, the cell-free massive MIMO suffers from energy overloading caused by uncontrolled backhaul power consumption for large number of distributed access points (APs) and pilot contamination during channel estimation. In this paper, we have taken into consideration a cell-free massive MIMO system with APs equipped with multiple antennas performing time-division-duplex (TDD) operation. Here, all the APs coordinate through a constrained backhaul network for joint transmission of signals to all the users simultaneously by multiplying the received signal with the normalized conjugate of the estimated channel state information (CSI) and send back a rounded off version of the weighted pattern to the central processing unit (CPU). Finally, an effective user defined algorithm is presented involving selection and grouping of various APs based on their individual contributions for a particular MU to improve the overall performance of the system. [ABSTRACT FROM AUTHOR]

Abstract In this paper, we consider user centric virtual cells model in distributed antenna systems (DAS). We investigate different power allocation optimization problems with interferences in DAS with and without user centric virtual cells model, respectively. The first objective problem is maximizing spectral efficiency (SE) of the DAS with user centric virtual cells model under the constraints of the minimum SE requirements of each user equipment (UE), maximum transmit power of each remote access unit (RAU). We firstly transform this non-convex objective function into a difference of convex functions (D.C.) problem, and then we obtain the optimal solutions by using the concave-convex procedure (CCCP) algorithm. The second objective problem is maximizing energy efficiency (EE) of the DAS with user centric virtual cells model under the same constraints as the first objective problem. Firstly, we exploit fractional programming theory to obtain the equivalent objective function of the second problem with subtract form, and then transform it into a D.C. problem and use CCCP algorithm to obtain the optimal power allocation. In each part, we propose the corresponding optimal power allocation algorithm and also use similar method to obtain optimal solutions of the same optimization problems in DAS without using user centric virtual cells model. Simulation results are provided to demonstrate the effectiveness of the DAS with user centric virtual cells model, which can significantly improve the SE and the EE of the communication systems. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the tradeoff between energy efficiency (EE) and spectral efficiency (SE) in downlink orthogonal frequency division multiplexing access (OFDMA) systems, whilst considering the channel estimation cost and the corresponding effect of imperfect channel state information (CSI) on SE and EE. The problem is formulated as a multi-objective optimization to determine the optimal pilot transmission power, data transmission power and subcarrier assignment, and then transformed into a single-objective optimization problem, which is a non-convex mixed-integer nonlinear programming (NCMINP) and NP-hard. To address it, we propose an efficient algorithm by adopting alternating optimization and convex optimization methods in lower power region as well as approximate conversion and branch-and-bound methods in high power region. Simulation results analyze and validate the performance of EE-SE tradeoff. [ABSTRACT FROM AUTHOR]

Nowadays, the development of the photovoltaic (PV) technology is consolidated as a source of renewable energy. The research in the topic of maximum improvement on the energy efficiency of the PV plants is today a major challenge. The main requirement for this purpose is to know in real-time the working point of each of the PV modules that integrate the PV field and improve their performance. For this purpose, a Power Line Communications (PLC) based Smart Monitoring and Communications Module, which is able to monitor at PV level their operating parameters, has been developed at the University of Málaga. This device can check if any of the panels is suffering any type of overriding performance, due to a malfunction or partial shadowing of its surface. In this paper, the data acquisition system is described and subsequently the solution of the most energy-efficient path was arised from information acquired in real-time. Through graph theory and Minkoski’s paths have been possible to deduce the recursive programming algorithm that generate a dynamic reconfiguration to solve this problem. [ABSTRACT FROM AUTHOR]

This paper studies the optimization problem of energy efficiency in multi-cell networks with multiple users such as 5G network. However, the spectrum allocation and inter-cell interference (ICI) in multi-cell networks are the important challenges. The Soft Frequency Reuse (SFR) scheme which manages the spectrum and reduces ICI is used to build SFR-cellular networks. We take the global energy efficiency of the SFR-cellular network as the objective function of the optimal problem to obtain the maximum energy efficiency. Unfortunately, the objective function is a non-concave function, which is significantly difficult to be solved directly. Therefore, we utilize the fractional program, successive convex approximation, Lagrange dual, and Karush–Kuhn–Tucker (KKT) conditions to transform the objective function into a concave function. In such case, we could solve the problem with the convex optimization method. Finally, based on SFR, we propose a global energy efficiency optimization algorithm to search for the optimal energy efficiency of networks. Simulation results show that the proposed algorithm holds the better performance. [ABSTRACT FROM AUTHOR]

This paper presents a real-time optimization method and demonstrates its application to a Proton Exchange Membrane Fuel Cell (PEMFC) system. The optimization function was defined as mix of two performance indicators, the FC net power and the Fuel Consumption Efficiency, using the appropriate weighting coefficients. The weighting coefficients will modify the optimization surface and many extreme could appear on plateau of the optimization surface. The Global Extremum Seeking (GES) algorithm proposed here as real-time optimization method will locate and track the global maximum point and related to this will be established the optimal fueling rates for the PEMFC system under a given load. In this study four strategies will be tested, including the Static Feed-Forward (sFF) control strategy as reference. The optimal operating conditions were sought at different levels of load and the gaps between these four strategies were estimated. For example, in comparison with the PEMFC system controlled by the sFF strategy, the GES operation of the PEMFC system could increase the energy efficiency with 1–2.1%, depending on the FC current level and values used for the weighting coefficients. If the PEMFC system operates under variable load profile, the Fuel Consumption Efficiency could also increase with more than 0.54 W/lpm for GES&LF-based optimization strategy in comparison with the sFF strategy. The effectiveness of GES&LF-based optimization strategy was shown considering a FC Hybrid Power Source under variable load profile. [ABSTRACT FROM AUTHOR]

Belt conveyors and crushers are always assembled in series to form coal conveying systems; reasonably, this paper takes them as a whole for energy efficiency optimization. The energy models of the key energy consuming devices, belt conveyors and crushers, are firstly constructed. They are then employed to formulate an open loop energy efficiency optimization problem for the studied coal conveying systems. The coal feed rate, belt speed and crusher rotational speed are taken as the optimization variables; and, the energy cost, with consideration of time-of-use (TOU) tariff, is formulated as the objective function. Next, basing on the above open loop optimization problem, a closed-loop model predictive control (MPC) strategy is constructed. The MPC strategy has the ability to deal with various disturbances with its feedback correction and receding horizon optimization mechanisms. A coal conveying system in a coal-fired power plant is taken as a case study for verification of the two strategies. The open loop optimization and MPC strategies are investigated respectively for comparison studies. The results show that, unlike the open loop optimization, the MPC strategy can deal with the disturbances of coal consumption forecasting, the disturbances of belt feeding rate and the disturbances of mean particle size of feeding coal effectively. The MPC strategy can considerably improve the energy efficiency of the whole coal conveying system while satisfying all the constraints. Its robustness and adaptability are verified through the comparison studies. [ABSTRACT FROM AUTHOR]

In this paper we address the problem of designing new energy-efficient static daylight devices that will surround the external windows of a residential building in Madrid. Shading devices can in fact largely influence solar gains in a building and improve thermal and lighting comforts by selectively intercepting the solar radiation and by reducing the undesirable glare. A proper shading device can therefore significantly increase the thermal performance of a building by reducing its energy demand in different climate conditions. In order to identify the set of optimal shading devices that allow a low energy consumption of the dwelling while maintaining high levels of thermal and lighting comfort for the inhabitants we derive a multi-objective optimization methodology based on Harmony Search and Pareto front approaches. The results show that the multi-objective approach here proposed is an effective procedure in designing energy efficient shading devices when a large set of conflicting objectives characterizes the performance of the proposed solutions. [ABSTRACT FROM AUTHOR]

In this paper, we present energy-aware production planning using a two-dimensional “Energy-Performance” measure. With this measure, the production plan explicitly takes into account machine-level requirements, process control strategies, product types and demand patterns. The “Energy-Performance” measure is developed based on an existing concept, namely, “Specific Energy” at machine level. It is further expanded to an “Energy-Performance” profile for a production line. A production planning problem is formulated as a stochastic MILP with risk-averse constraints to account for manufacturer’s risk averseness. The objective is to attain an optimal production plan that minimizes the total loss distribution subject to system throughput targets, probabilistic risk constraints and constraints imposed by the underlying “Energy-Performance” pattern. Electricity price and demand per unit time are assumed to be stochastic. Conditional Value at Risk (CVaR) of loss distributions is used as the manufacturer’s risk measure. Both single-machine and production lines are studied for different profiles and electricity pricing schemes. It is shown that the shape of “Energy-Performance” profile can change optimal plans. [ABSTRACT FROM AUTHOR]

Temperature and humidity independent control (THIC) systems demonstrate promising energy-saving potential compared with the conventional air conditioning systems. One type of THIC systems is proposed to use dual cooling sources with different temperatures since they could be produced easily by traditional vapor compression refrigeration chillers. This paper investigates the applicable condition of the THIC system based on dual cooling sources (DCSTHIC system). It is found that the DCSTHIC system has limited conditions (such as scopes of the heat moisture ratio and the fresh air rate) when applied, otherwise the indoor air temperature and humidity can’t be fulfilled, and further available scope of the heat moisture ratio realized by the DCSTHIC system is disclosed for air conditioned spaces. The minimum realized heat moisture ratio depends on the temperature of low-temperature cooling sources ( t LCS ). A parametric study is also conducted to analyze effects on the energy efficiency of DCSTHIC systems. These parameters include the heat moisture ratio ( ε ) and temperatures of dual cooling sources. Results show that DCSTHIC systems show more significant energy-saving potential in the air conditioned spaces with higher ε . The system COP improvement ranges from 3.1% to 17.5% compared with conventional air conditioning systems when the heat moisture ratio changes from 8000 kJ/kg to 15,000 kJ/kg. This study helps to guide the design and optimization of DCSTHIC systems. [ABSTRACT FROM AUTHOR]

The paper presents the analysis of some potentially suitable actions for reducing the energy losses of an islanded Medium Voltage distribution network, with the aim of improving electricity distribution efficiency. For this purpose, four actions are considered: 1) increasing the network's rated voltage; 2) reactive power compensation through static capacitor banks; 3) reactive power compensation through switchable capacitor banks; 4) installation of distributed photovoltaic (PV) generation. The first two measures are typically taken into account by the distribution system operators and can be examined by means of classical design methods, whereas the latter two more innovative actions are tested here using specialized software based on the NSGA-II multi-objective optimization algorithm. The fourth action, expanding distributed PV generation, can be motivated through public or private incentives. It is investigated here using an innovative approach to the optimization problem formulation considering the perspectives of both the utility and the consumer. A case study on a small Mediterranean island real existing network is also presented. [ABSTRACT FROM AUTHOR]

In the current situation of the energy crisis, the mining industry has been identified as a promising area for application of demand side management (DSM) techniques. This paper investigates the potential for energy-cost savings and actual energy savings, by implementation of variable speed drives to ventilation fans in underground mines. In particular, ventilation on demand is considered in the study, i.e., air volume is adjusted according to the demand at varying times. Two DSM strategies, energy efficiency (EE) and load management (LM), are formulated and analysed. By modelling the network with the aid of Kirchhoff’s laws and Tellegen’s theorem, a nonlinear constrained minimization model is developed, with the objective of achieving EE. The model is also made to adhere to the fan laws, such that the fan power at its operating points is found to achieve realistic results. LM is achieved by finding the optimal starting time of the mining schedule, according to the time of use (TOU) tariff. A case study is shown to demonstrate the effects of the optimization model. The study suggests that by combining load shifting and energy efficiency techniques, an annual energy saving of 2 540 035 kW h is possible, leading to an annual cost saving of USD 277035. [ABSTRACT FROM AUTHOR]

The electrical grid in most of the developing countries has inefficiencies in different areas such as transmission and distribution, power quality, grid reliability and system protection. These inadequacies in grid operations and asset protection, along with revenue leakage constitute an overall troubled energy profile. The fixes usually proposed in this regard are directed at reducing distribution network losses and improving residential and commercial demand side management. Lessons from the residential and commercial implementation of smart meters can be extended to industrial consumers to help relieve grid congestion and achieve better efficiency goals. This paper reviews smart meter technology and applications across residential, commercial and industrial sectors. We point out the areas for power quality and energy efficiency improvement within industries and propose ways for achieving them through smart meters, specifically in the context of Pakistan. We have incorporated empirical evidence from experimental setup at our university grid as proof of concept. We have also elaborated on the implementation methodology to avoid the possible pitfalls in the proposed solution. [ABSTRACT FROM AUTHOR]

In order to optimize the global energy performance of a ground source heat pump system, special attention needs to be paid to the auxiliaries as they stand for a considerable part of the total energy consumption. A new in situ experimental methodology based on the frequency variation of the water circulation pumps in order to optimize the energy performance of the system was previously published by the authors for a ground source heat pump system using a single stage heat pump with ON/OFF regulation. The original single stage heat pump was recently replaced with a multistage unit consisting of two compressors of the same capacity working in tandem. A new experimental campaign was carried out and a new study was performed in order to adapt the in situ optimization methodology to the performance of the tandem compressors unit, and, by extension, to the multistage case. This paper presents the in situ optimization methodology for the water circulation pumps frequency adapted for multistage ground source heat pump systems. Results show that energy savings up to 32% can be obtained by applying this optimization methodology. [ABSTRACT FROM AUTHOR]

Abstract: Changing legislation and rising energy costs are bringing the need for efficient baking processes into much sharper focus. High-speed air impingement bread-baking ovens are complex systems using air flow to transfer heat to the product. In this paper, computational fluid dynamics (CFD) is combined with experimental analysis to develop a rigorous scientific framework for the rapid generation of forced convection oven designs. A design parameterisation of a three-dimensional generic oven model is carried out for a wide range of oven sizes and flow conditions to optimise desirable features such as temperature uniformity throughout the oven, energy efficiency and manufacturability. Coupled with the computational model, a series of experiments measuring the local convective heat transfer coefficient (hc ) are undertaken. The facility used for the heat transfer experiments is representative of a scaled-down production oven where the air temperature and velocity as well as important physical constraints such as nozzle dimensions and nozzle-to-surface distance can be varied. An efficient energy model is developed using a CFD analysis calibrated using experimentally determined inputs. Results from a range of oven designs are presented together with ensuing energy usage and savings. [Copyright &y& Elsevier]

This paper develops a new process for identifying the lowest cost package of energy efficiency measures (EEM) and hybrid energy system configuration for off-grid homes. Hybrid energy systems, which combine two or more types of energy technologies, often require significant capital expenditure, however, the cost can be reduced by applying EEM to the house to decrease energy demand. The method proposed here, termed Combined Optimization Process (COP), was tested on an off-grid hypothetical case and incorporates an iterative assessment of a building energy and efficiency optimization tool (BEopt) and a hybrid system optimization tool (HOMER). The COP results were compared with the base case where no efficiency measures were applied, and also with a standard process, which involved a selection of best-practice efficiency measures. The COP method yielded net present cost savings of 10% less than the base case, and 5% less than the standard process. The COP method developed in this paper is applicable for existing houses converting to off-grid status as well as for the design stage of off-grid houses. [ABSTRACT FROM AUTHOR]

• We present a novel way to consider efficiency in energy system optimization models. • Our approach can consider a range of behaviors consistent with microeconomic theory. • This new approach is applied to a simple test case and includes sensitivity analysis. • Maximum recovered welfare from efficiency crediting is <50% of the first-best option. Energy system optimization models (ESOMs) are designed to examine the potential effects of a proposed policy, but often represent energy-efficient technologies and policies in an overly simplified way. Most ESOMs include different end-use technologies with varying efficiencies and select technologies for deployment based solely on least-cost optimization, which drastically oversimplifies consumer decision-making. In this paper, we change the structure of an existing ESOM to model energy efficiency in way that is consistent with microeconomic theory. The resulting model considers the effectiveness of energy-efficient technologies in meeting energy service demands, and their potential to substitute electricity usage by conventional technologies. To test the revised model, we develop a simple hypothetical case and use it to analyze the welfare gain from an energy efficiency subsidy versus a carbon tax policy. In the simple test case, the maximum recovered welfare from an efficiency subsidy is less than 50% of the first-best carbon tax policy. [ABSTRACT FROM AUTHOR]

Abstract: Economic, energy, and sustainability metrics are key performance indicators for process operations. The relative importance of these metrics varies from plant to plant, and often some metrics are in conflict with each other (sustainability vs. profitability). In this paper we discuss the current plant environment and how various metrics can be aligned by focusing on energy efficiency. Power-steam systems are the major energy drivers for most plants, and we discuss possible operational changes that might improve energy efficiency, as well as the role of process control. Managing the interplay of real-time optimization and regulatory control is a challenge for the future, as well as interfacing with the implementation of smart power grids by the utility industry. Combined heat and power along with energy storage presents interesting control and optimization opportunities to maximize energy efficiency. [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: 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: This paper presents a study concerning the optimization of a Waste Water Treatment process. The process deals with carbon and nitrogen removal and includes activated sludge reactors coupled with an anaerobic digestion reactor. Nitrification and de-nitrification biochemical reactions are due to the biological activity of heterotrophic and autotrophic micro-organisms occurring inside the reactors. Rigorous Plant-Wide models that represent the main biochemical transformations have been constructed as per the CEIT approach . The energy consumption for each Physical Unit Operation (P.U.O.) involved in the flow-sheet is evaluated and a full link is made between the biological activity and the electrical demand or production. Steady-state mathematical optimizations are then computed and the influence of primary settling efficiency on electrical autonomy is quantified and demonstrated. The ammonium recycling from digestion to activated sludge reactors is also demonstrated to be a limiting factor for the overall energy efficiency, as well as the C-substrate availability for denitrifying. Some conclusions are then drawn to improve the global electrical efficiency of the system. [Copyright &y& Elsevier]

Abstract: Increasing requirements for energy performance in new buildings mean the cost of incorporating energy-saving in buildings is also increasing. Building designers thus need to be aware of the long-term cost-effectiveness of potential energy-conserving measures. This paper presents a simplified and transparent economic optimisation method to find an initial design proposal near the economical optimum. The aim is to provide an expedient starting point for the building design process and more detailed economic optimisation. The method uses the energy frame concept to express the constraints of the optimisation problem, which is then solved by minimising the costs of conserving energy in all the individual energy-saving measures. A case example illustrates how the method enables designers to establish a qualified estimate of an economically optimal solution. Such an estimate gives a good starting point for the iterative design process and a more detailed economic optimisation. Furthermore, the method explicitly illustrates the economic efficiency of the individual building elements and services enabling the identification of potentials for further product development. [Copyright &y& Elsevier]

Abstract: Electric lighting consumes 19% of total electricity production worldwide. Open-plan offices constitute the majority of office stock, in which most office workers perform their daily tasks, and hence the lighting in those offices has significant impact on, not only energy usage, but also occupants’ productivity. This paper presents a unique lighting optimization approach for open-plan offices that is capable of tuning task lighting to each occupant''s preference in the most energy-efficient fashion. Exploiting individual controllability of the advanced networked lighting systems, each luminaire can be dynamically actuated at a different level to realize various lighting configurations without any physical rewiring. This research formulates lighting actuation into a linear programming problem and finds the optimal light outputs for each of the luminaires that collaboratively deliver specified lighting to each workstation while using the least amount of energy. Simulations using our lighting optimization approach have shown its versatility in providing proper workstation-specific task lighting under different requirements compared to business-as-usual practices. Energy savings are generated from tuning the light levels to occupants’ needs as well as keeping unoccupied areas unlit or minimally lit with this approach. [Copyright &y& Elsevier]

Abstract: Significant energy efficiency gains in zones with concentrated activity from energy intensive industries can often be achieved by recovering and reusing waste heat between processing plants. We present a systematic approach to target waste heat recovery potentials and design optimal reuse options across plants in industrial zones. The approach first establishes available waste heat qualities and reuse feasibilities considering distances between individual plants. A targeting optimization problem is solved to establish the maximum possible waste heat recovery for the industrial zone. Then, a design optimization problem is solved to identify concrete waste heat recovery options considering economic objectives. The paper describes the approach and illustrates its application with a case study. [Copyright &y& Elsevier]

Abstract: With the 2009/28/EC Directive, the European Union has to guarantee three objectives by 2020: 20% reduction in greenhouse gases emissions, 20% share of renewable energy and 20% improvement of energy efficiency. New technologies and policies applied to power systems can positively influence the overall energy efficiency. The dimensions and complexity of the power system discourage the use of exact optimization techniques and heuristic methods are an effective option to find a rapid, robust and good solution. This paper presents a review of articles with applications of heuristic methods to the transmission and distribution system with the aim of improving energy efficiency. [Copyright &y& Elsevier]

Abstract: This paper studied the influences of operational parameters to improve the energy efficiency during ‘ultrasonic lysis–cryptic growth’ sludge reduction. Subsequent batch reactor with a hydraulic retention time of 8h was used to treat urban sewage, and ultrasound wave with a specific energy of 20kWh/kgTS was employed for sludge lysis. A new index, EE, was defined to evaluate the energy efficiency in ultrasonic lysis–cryptic growth sludge reduction system. Results showed that the most important operational parameter was the proportion of sonicated sludge (SP), which determined the energy consumption and significantly impacted the energy efficiency. The upper limit of SP in this study was 30%, beyond which the effluent quality was unacceptable. Higher SP caused heavier sludge reduction but more energy consumption; when SP was 30%, the excess sludge reduction was the greatest (67.6%) and the energy consumption was the highest (0.101kWh/d). With a given SP, frequent sludge lysis was adverse to sludge reduction. In summary, the recommended conditions for ‘ultrasonic lysis–cryptic growth’ sludge reduction were SP of 15%, lysis frequency of 1time/day. Under these conditions, the highest energy efficiency of 0.012kgTS/kWh was achieved. [Copyright &y& Elsevier]

Abstract: In transmission and distribution systems, the high number of installed transformers, a loss source in networks, suggests a good potential for energy savings. This paper presents how the Spanish Distribution regulation policy, Royal Decree 222/2008, affects the overall energy efficiency in distribution transformers. The objective of a utility is the maximization of the benefit, and in case of failures, to install a chosen transformer in order to maximize the profit. Here, a novel method to optimize energy efficiency, considering the constraints set by the Spanish Distribution regulation policy, is presented; its aim is to achieve the objectives of the utility when installing new transformers. The overall energy efficiency increase is a clear result that can help in meeting the requirements of European environmental plans, such as the ‘20–20–20’ action plan. [ABSTRACT FROM AUTHOR]

Abstract: This paper describes the formulation of a computational framework for simulating and optimising DCMD to minimise the consumed energy. A simulation procedure for DCMD was established on the basis of equating heat and mass fluxes through different domains in the process. Steady-state simulations for a wide range of operating conditions were carried out. It was revealed that the highest achievable energy efficiency of DCMD within the tested range was about 49.9%. A double loop optimisation problem was formulated in MATLAB to solve the highly nonlinear equations with unknown outlet and membrane surface conditions to implement the simulation procedure. An additional outer loop was also implemented to accommodate the dynamic condition of a real lab-scale DCMD system concentrating 1.5kg glucose solution from 30 to 60% w/w. A pseudo-real-time dynamic optimisation was performed to minimise the energy expenses for the DCMD process. This energy accounted for the heat exchanged between the feed and permeate streams within the membrane module and the power for their pumping, while maintaining a minimum mass flux of 0.5kgm−2 h−1. The optimal operating conditions found in this study could save the total energy consumption by 26.3%. [Copyright &y& Elsevier]

Abstract: Several authors have pointed out the need to identify the optimum operating conditions (OCs) of autothermal thermophilic aerobic digestion (ATAD). This study proves the hypothesis that the OCs have the potential to substantially improve the energy efficiency and plant capacity of established ATAD systems. As ATAD is a semi-batch process, its energy efficiency has to be optimized via dynamic optimization (DO). This methodology requires an adequate mathematical model, and appropriate selection of optimization variables. The paper presents an improved mathematical ATAD model based on previous models found in the literature. A global sensitivity analysis (GSA) was performed in order to identify variables with significant influence upon energy efficiency and plant capacity, thus paving the way for the DO of ATAD systems. The results of the GSA show that reactor volume, reactor temperature, and aeration flowrate are significant variables, which is consistent with reported literature. The results of the GSA also show that both energy efficiency and plant capacity of ATAD systems can be substantially improved by altering reactor volume and OCs. [Copyright &y& Elsevier]

Abstract: In wireless networks, end-to-end communication depends on link capacities which, in turn, are determined by transmit powers of interfering links. Optimal network performance and energy efficiency can be achieved by jointly optimizing congestion control and power control. In this paper, we study this joint optimization problem by formulating it into convex programming, i.e., we maximize a compound function which is a network utility function minus a factor, named tradeoff factor, of the associated power cost. We prove that this tradeoff factor is essential for good energy efficiency while maintaining the network throughput at a satisfactory level. The problem is solved by a distributed dual-decomposition based algorithm energy efficient jointly optimal congestion and power control (EJOC). EJOC tackles the power control problem in a recursive manner, operating as easily as the steepest descent method but converging much faster. This optimization framework is further extended to networks where each data source may have multiple alternative paths to its destination. Simulation results show that the proposed algorithm converges faster than other algorithm and is capable of significantly improving the energy efficiency of the network. [Copyright &y& Elsevier]