Energy Optimization Methodology Research Articles

Methodology for Energy Efficiency Analysis and Optimization of Ship Systems using Exergy Modeling

Methodology for Energy Efficiency Analysis and Optimization of Ship Systems using Exergy Modeling

Integration of energy and seismic-structural design variables through the optimization of a multi-story residential light-frame timber building with different seismic lateral connectors and building stories

The structural and energy performance of the light-frame buildings is intrinsically linked, but the design process of both domains is not. Light-frame timber buildings are subjected to overheating due to the lack of thermal mass. A solution to eliminate or mitigate overheating is adding thermal mass, but the main drawback is increasing the seismic forces the building needs to withstand. Furthermore, the length of exterior shearwalls, fenestration openings, and studs spacing affect both the energy and structural performances. This paper aims to analyze and integrate energy and seismic-structural design variables for a light-frame residential timber building with different lateral seismic connectors and building stories. An Energy and Structural Timber Building Optimization (ESTIBO) methodology is proposed to integrate energy and seismic-structural design variables by optimizing the building energy performance. ESTIBO is based on GenOpt optimization software using a hybrid multidimensional optimization algorithm, while the energy simulations are performed on EnergyPlus using the Rhino's Grasshopper plugin. A structural model is implemented in Matlab under a modal response analysis of the building structure. The main results show that integrating critical design variables achieves different optimal values considering feasible structural solutions with reduced heating and cooling loads. It was found the four main variables that primarily reflect the link between energy and seismic-structural performances are stud spacing, wall insulation thickness, wall insulation type (high or low specific heat capacity), and floor concrete layer thickness. This paper contributes to improving the understanding of light-frame timber buildings' performance regarding the interaction of energy and structural-seismic design variables. Moreover, ESTIBO demonstrated to be able to provide optimal energy and seismic-structural solutions. Thus, it can support the early design stage of light-frame timber buildings.

Introduction to thermoacoustic Stirling engines: First steps and praxis

The work focuses on the theoretical study and design of Thermoacoustic Stirling-Like Cycle Engines. One of the main goals of this study is to describe the application of a methodology for energy analysis and optimization of thermoacoustic devices. This new approach avoids complicated mathematical treatments, facilitates access to this fascinating technology for all audiences. The presented methodology is based on the distribution of the active and reactive acoustic power flow according to the passive acoustic circuit. In addition, this methodology allows optimizing the device by comparing different acoustic circuits. This method is evaluated at a theoretical level with the models and simulations developed, for each of the case studies described. Besides, this publication shows the praxis from the first steps, so the reader is guided in the design and manufacture of a compact Stirling thermoacoustic energy recovery engine, operating in laboratory conditions. The resulting demonstrator is itself an academic tool for knowledge transfer.

Methodology and Software Tool for Energy Consumption Evaluation and Optimization in Multilayer Transport Optical Networks

In communication networks, the volume of traffic, the number of connected devices and users continues to grow. As a result, the energy consumption generated by the communication infrastructure has become an important parameter that needs to be carefully considered and optimized both when designing the network and when operating it in real-time. In this paper, the methodology of calculation of complex parameters of energy consumption for transport telecommunication networks is proposed. Unlike the known techniques, the proposed methodology takes into account heterogeneity and multilayer networks. It also takes into account the energy consumption parameter during the downtime of the network equipment in the process of processing the service data blocks, which is quite an important task for improving the accuracy of energy consumption at the stage of implementing the energy-saving network. We also developed simulation software to estimate and manage the energy consumption of the optical transport network using the LabVIEW environment. This software tool allows telecommunication network designers to evaluate energy consumption, which allows them to choose the optimal solution for the desired projects. The use of electro-and acousto-optical devices for optical transport networks is analyzed. We recommended using electro-optical devices for optical modulators and acousto-optical devices for optical switches. The gain from using this combination of optical devices and the parameter of rij electro-optical coefficient and M2 acousto-optical quality parameter found in the paper is about 36.1% relative to the complex criterion of energy consumption.

Interconnect-Aware Area and Energy Optimization for In-Memory Acceleration of DNNs

State-of-the-art in-memory computing (IMC) architectures employ an array of homogeneous tiles and severely underutilize processing elements (PEs). In this article, the authors propose an area and energy optimization methodology to generate a heterogeneous IMC architecture coupled with an optimized Network-on-Chip (NoC) for deep neural network (DNN) acceleration. – Yiran Chen, Duke University

The Inclusion of End-of-Life Modeling in the Life Cycle Energy Optimization Methodology

Abstract In this study, an end-of-life (EOL) model is included in the life cycle energy optimization (LCEO) methodology to account for the energy burdens and credits stemming from a vehicle’s EOL processing phase and balance them against the vehicle’s functional requirements and production and use-phase energies. The substitution with a correction factor allocation method is used to model the contribution of recycling to the EOL phase’s energy. The methodology is illustrated through the optimization of the design of a simplified vehicle subsystem. For the latter, multiple recycling scenarios with varying levels of assumed recycling induced material property degradation were built, and their impact on the vehicle subsystem’s optimal solutions was compared to that of scenarios based on landfilling and incineration with energy recovery. The results show that the vehicle subsystem’s optimal designs are significantly dependent on the EOL scenario considered. In particular, the optimal designs associated with the recycling scenarios are on average substantially heavier, and less life cycle energy demanding, than their landfilling or incineration with energy recovery-related counterparts, thus demonstrating how the inclusion of EOL modeling in the LCEO methodology can significantly alter material use patterns, thereby effecting the very mechanisms enabling the embodiment of the resulting life cycle energy optimal designs.

Methodology for Energy Optimization in Wastewater Treatment Plants. Phase III: Implementation of an Integral Control System for the Aeration Stage in the Biological Process of Activated Sludge and the Membrane Biological Reactor.

The proposed methodology for optimizing energy efficiency, based on good management of the aeration process through the implementation of an appropriate control strategy, achieved reductions of more than 40% in energy consumption at the San Pedro del Pinatar Wastewater Treatment Plant (WWTP) (Murcia, Spain). Phases I and II of this methodology managed to reduce the oxygen needs of the microorganisms in the biological system, optimize the efficiency of oxygen transfer to the biological reactor and redesign the installation to correct abnormal energy loss situations. In addition, we established the basis for Phase III, which implemented a control strategy to achieve stable values close to the setpoints of the fundamental operating parameters of the aeration process. The control system is based on the measurements recorded by strategically installed sensors and mathematical algorithms based on models, achieving an expert adaptive-predictive system that regulates aeration both in the biological stage by activated sludge and the aeration of the installed ultrafiltration membrane system. The objectives were: (i) to achieve automatic execution of the best management strategy; (ii) to reduce the energy demand; (iii) to improve the operation and stability of the process; (iv) to reduce operating costs; and (v) to contribute to the fulfillment of the sustainable development objectives.

Methodology for Energy Optimization in Wastewater Treatment Plants. Phase II: Reduction of Air Requirements and Redesign of the Biological Aeration Installation

Phase I of the proposed energy optimization methodology showed how the selection of best management criteria for the biological aeration process, and the guarantee of its control at the wastewater treatment plant (WWTP) in San Pedro del Pinatar (Murcia, Spain) produced reductions of around 20% in energy consumption by considerably reducing the oxygen needs of the microorganisms in the biological system. This manuscript focused on phase II of this methodology, which describes the tools that can be used to detect and correct deviations in the optimal operating points of the aeration equipment and the intrinsic deficiencies in the installation, in order to achieve optimization of the oxygen needs by the microorganisms and improve the efficiency of their transfer from the gas phase to the liquid phase. The objectives pursued were: (i) to minimize the need for aeration, (ii) to reduce the pressure losses in the installation, (iii) to optimize the air supply pressures to avoid excessive energy consumption for the same airflow, and (iv) to optimize the control strategy for the actual working conditions. The use of flow modeling and simulation techniques, the measurement and calculation of air transfer efficiency through the use of off-gas hoods, and the redesign of the aeration facility at the San Pedro del Pinatar WWTP were crucial, and allowed for reductions in energy consumption in Phase II of more than 20%.

Methodology for Energy Optimization in Wastewater Treatment Plants. Phase I: Control of the Best Operating Conditions

Most purification systems work correctly from the point of view of water quality; purification, like any industrial process, must also be carried out efficiently with a minimization of costs. The overall project examined the potential benefits of using a recommended methodology for process evaluation and energy optimization in the aeration stage of activated sludge in the biological reactor at wastewater treatment plants (WWTP), which accounts for more than 44% of total operating costs. This energy control methodology encompasses the process, the installation and the control system. These three phases are examined in separate articles to make it easier to guide the user in the arduous task of optimizing energy efficiency of the WWTP from start to finish. This article focuses on Phase I of the methodology, the stage in charge of selecting the correct variables to control the best process conditions in the activated sludge system of the WWTP. Operating conditions that are a function of the recommended sludge age are influenced by exogenous factors such as temperature. The implementation of a real-time control system of the selected process variables, adapted to the needs, achieves reductions in the overall energy consumption of the installation, in this phase alone, of more than 15%, by reducing the oxygen requirements of the system and the recirculation ratios.

Energy saving analysis of the cooling plant using lake water source base on the optimized control strategy with set points change

A cooling plant using lake water source, combining free cooling technology and variable capacity technology, was constructed to remove the heat in data centers. This study explores the energy savings potential through energy optimization methodology considering the mutual effect of multi-variables set points on the performance of the entire cooling system compared to the reference control strategies with fixed set points (I and II). Because the lake water added one more dimension and resulted in a complex nonlinear problem, the energy optimization methodology using genetic algorithm was proposed. Based on the energy model of the cooling plant and genetic optimization, it is expected that the proposed control strategy can adapt to the variation of cooling load, thermal performance of the cooling plant, environmental conditions and drive the system toward a high overall energy efficiency. To evaluate the performance, we conducted a case study on a data center using Dongjiang lake water, in China, by comparing the strategy against method I and II. It was found that the cooling plant base on the control strategy III achieved the maximum energy savings of 33.1% over the control strategy I, and also obtained about 14.8% compared to the control strategy II.

Energy optimization methodology for e‐infrastructure providers

SummaryThe environmental protection is a dominant concern for all types of industries, organizations, and governments. In this regard, the reduction of the energy consumption is substantial in bringing down the CO2 gas emission, which is considered as an important factor causing global warming. The e‐infrastructure service providers, such as National Research and Education Networks or National Grid Initiatives have crucial role in the context of energy awareness because the energy consumption of the networking, data, and computational infrastructures keeps increasing exponentially over the time. In addition to this, scientific gateways and cloud services are becoming more significant to tackle scientific and societal challenges. Therefore, there is a need to provide robust and reliable services taking into account energy consumption aspect of e‐infrastructures. The aim of the article is to introduce an energy optimization methodology for the beneficiaries of the e‐infrastructures to explore, optimize, and report the energy consumption and CO2 emission of data, computing, and networking facilities. The suggested methodology has been implemented within the Armenian e‐infrastructure aiming at the reduction of the energy consumption and thereby the CO2 emission.

Energy optimization methodology of multi-chiller plant in commercial buildings

This study investigates the potential energy savings in commercial buildings through optimized operation of a multi-chiller plant. The cooling load contributes 45–60% of total power consumption in commercial and office buildings, especially at tropics. The chiller plant operation is not optimal in most of the existing buildings because the chiller plant is either operated at design condition irrespective of the cooling load or optimized locally due to lack of overall chiller plant behavior. In this study, an overall energy model of chiller plant is developed to capture the thermal behavior of all systems and their interactions including the power consumption. An energy optimization methodology is proposed to derive optimized operation decisions for chiller plant at regular intervals based on building thermal load and weather condition. The benefits of proposed energy optimization methodology are examined using case study problems covering different chiller plant configurations. The case studies result confirmed the energy savings achieved through optimized operations is up to 40% for moderate size chiller plant and around 20% for small chiller plant which consequently reduces the energy cost and greenhouse gas emissions.

Simultaneous Optimization of Standby and Active Energy for Sub-Threshold Circuits

Increased downscaling of CMOS circuits with respect to feature size and threshold voltage has a result of dramatically increasing in leakage current. So, leakage power reduction is an important design issue for active and standby modes as long as the technology scaling increased. In this paper, a simultaneous active and standby energy optimization methodology is proposed for 22 nm sub-threshold CMOS circuits. In the first phase, we investigate the dual threshold voltage design for active energy per cycle minimization. A slack based genetic algorithm is proposed to find the optimal reverse body bias assignment to set of noncritical paths gates to ensure low active energy per cycle with the maximum allowable frequency at the optimal supply voltage. The second phase, determine the optimal reverse body bias that can be applied to all gates for standby power optimization at the optimal supply voltage determined from the first phase. Therefore, there exist two sets of gates and two reverse body bias values for each set. The reverse body bias is switched between these two values in response to the mode of operation. Experimental results are obtained for some ISCAS-85 benchmark circuits such as 74L85, 74283, ALU74181, and 16 bit RCA. The optimized circuits show significant energy saving ranged (from 14.5% to 42.28%) and standby power saving ranged (from 62.8% to 67%).

Energy storage for residential dwellings. Methodology to improve energy efficiency and habitability

The paper aims to develop a methodology for energy optimization of the residential sector which proposes a proper use of energy storage technologies applied to massive retrofitting. This research began as a mitigation measure against the low thermal qualities of existing buildings in Argentina, the energy crisis and its environmental consequences. Strategies of morphological and technological-constructive criteria according to representative typologies were adopted. In order to evaluate energy consumption, a method was implemented which considered the relationship between energy savings and initial investment cost through an “energy-economic efficiency index”. An application example on an existing building is exposed in order to visualize the analysis developed. Its implementation on relevant typologies allows us to expand the results and to analyse mitigation levels in the representative urban areas and thus replicate improvement proposals promoting a significant reduction in residential consumption considering its envelope as energy storage. The results show that savings of 20% would be achieved in the sector, noting that the participation of this sector represent almost a quarter of the national energy matrix. This (theoretically) reduction in energy demand is beneficial both for all individual users (who can amortize initial retrofitting costs in a brief time of 10 years or less according to energy subsidy levels), as for the group of the population and the state, because this reduction would allow dispensing with fuel imports and reframing subsidy policies. In conclusion, this paper shows how the proper use of energy storage technologies in residential dwellings may largely reduce the energy needs while delivering better indoor environment quality and providing the basis for future implementation of renewable sources.

The forest biorefinery and its implementation in the pulp and paper industry: Energy overview

Incorporating a biorefinery unit to an operating Kraft pulping process has significant technological, economic and social advantages over the construction of a grassroot biorefinery. Also, the conversion of a Kraft mill from total pulp making to complete biorefinery can be done in a stepwise fashion and so give a company that envisages such transformation the opportunity to master the new technologies, evaluate options and develop an appropriate business plan. In all cases however, the road to conversion presents serious challenges. As components of the wood such as lignin or hemicelluloses are withdrawn from the Kraft pulp line, the heat production capacity from the recovery boiler where they are currently burnt is diminished. At the same time the operation of the added biorefinery unit increases the steam demand. In order to avoid fossil fuel dependency, the total site must be highly integrated and optimized. The application of an intensive and innovative energy optimization methodology to actual case studies has shown that the green, low GHG emissions biorefinery is feasible. The economics can be attractive for a site combining specialty wood pulp and bio-product, biomass gasification, power cogeneration and heat upgrading by optimally positioned and designed absorption heat cycles. The methodology has been applied to biorefining technologies for lignin and hemicelluloses extraction and valorisation, both technologies being coupled with gasification of wood residue.