Optimize Energy Use Research Articles

Optimising energy use in an existing commercial building: a case study of Australia\u2019s Reef HQ Aquarium

Reef HQ Aquarium is a major tourism attraction in tropical North Queensland, Australia. In 8 years, a 50% reduction in grid electricity was achieved through targeted infrastructure investment, whilst growing the business. Initially, grid energy consumption was 2438 MWh per annum, with 490-kW peak demand and energy intensity of 1625 MJ m−2 year−1 used on typical equipment such as HVAC (heating, ventilation and air conditioning), machinery, lighting and catering equipment. Savings of 13% were achieved in the first year by increasing indoor air temperature set-points by 1.5 °C with no significant costs or impacts on occupant thermal comfort or worker productivity. Peak demand was decreased by 46% by upgrading the computerised building management system (BMS), HVAC, machinery and lighting; and by installing a 206-kW photovoltaic (PV) solar power system. This case study illustrates that (a) significant energy use reductions are possible at low cost; (b) capital investment in energy-efficient infrastructure can have short payback times and high direct and indirect benefits, particularly where equipment is ending its life. This study is unique as it examines how a commercial building with integrated chilled water thermal energy storage (TES) and a 3.2-ML chilled seawater aquarium system can be controlled by a BMS to optimise solar power to manage peak energy demand and also increase the utilisation of generated PV power in the absence of electrical battery storage. An interesting building is used to demonstrate efficiency methods with elements such as HVAC and lighting which usually consume over half commercial buildings’ energy use.

Infrastructure Circuits for Lifetime Improvement of Ultra-Low Power IoT Devices

An ultra-low power (ULP), energy-harvesting system-on-chip, that can operate in various application scenarios, is needed for enabling the trillions of Internet-of-Things (IoT) devices. However, energy from the ambient sources is little and system power consumption is high. Circuits and system development require an optimal use of available energy. In this paper, we present circuits that can improve the energy utilization in an IoT device by providing improvements at critical points of the flow of harvested energy. A boost converter circuit, that can harvest energy from 10-mV input voltage and a few nanowatt of input power, makes more harvested energy available for the IoT device. A single-inductor-multiple-output buck-boost converter provides high-efficiency and low-voltage power management solution to put most of the harvested energy for system use. A real time clock and ULP bandgap reference circuit significantly reduce the standby power consumption. The proposed ULP circuits are developed in 130-nm CMOS technology. The combined effects of these circuits and the system design technique can improve the life-time of an example IoT device by over four times in higher power consumption mode and over 70 times in ULP mode.

Energy efficiency maturity (EEM) assessment framework for energy-intensive SMEs: Proposal and evaluation

Despite being a key industrial segment in terms production contribution and energy demand, small and medium-sized enterprises (SMEs) have been trailing in the implementation of available energy efficiency (EE) technologies, measures and practices due to both intrinsic and extrinsic barriers. The industrial EE audit programs driven by Government for SMEs had limited success in promoting EE practices due to an “onesize-fit-all” approach instead of a more personalized maturity-based approach towards EE assessment. Some of the energy management maturity models reported in the academic literature integrates the comprehensive requirements of ISO 50001, the international energy management standard, with the established maturity assessment instruments. However, these models are of little use to the SMEs due to the lack of resources and professional knowledge with the SMEs to meet ISO 50001 requirements. This study conceptualized and validated an energy efficiency maturity (EEM) framework for energy-intensive SMEs to facilitate a pre-assessment of EE maturity profile and draw out a personalized improvement plan. The framework consisted of three elements: EE characteristics & dimensions (derived from literature); EE maturity levels; and the Implementation method (adapted from Zero Defect Zero effect or ZED scheme designed for Indian SMEs). For validation of the EEM framework, a case of an Indian small-scale steel re-rolling mill (SRRM) was selected. The mill was rated at “Level 2 - Beginner” during the pre-assessment using the EEM instrument reached to “Level 4 - Achiever” after completion of first set of need-based EE improvement projects. These projects were attempted to build specific EE dimensions such as Energy Management roles; EE opportunity reporting; Product/Process innovation for optimization of energy use, which the mill lacked during the pre-assessment.

Implementation of material flow cost accounting for efficiency improvement in wastewater treatment unit of Tabriz oil refining company

The optimal use of material and energy by different industries has recently become an issue of great importance due to limited energy resources around the world. Material flow cost accounting (MFCA) has been suggested as a novel management system that can enhance waste management and provide an estimation of actual values of losses. This research aims to apply MFCA to the wastewater treatment unit of the Tabriz Oil Refining Company. In order to establish MFCA, the amount of input and output material, material costs, system costs and energy costs were studied. Using mass balance in all sections of wastewater treatment unit, losses were identified and costs and benefits were established. Results from MFCA calculation indicated that the annual cost of the unit is 28.14 million USD. This study also investigated the effect of changing the type of microorganisms in the biological treatment section that are able to digest high levels of ammonia and hydrogen sulfide and addition of reverse osmosis to the cooling drain section. It was found that the positive product's value increased from 58.92% to 90.76% and negative product's cost reduced from 41.08% to 9.23%. In addition to economic issues, use of these modifications considerably reduces environmental issues due to the release of NH3 and H2S to the environment and contamination of ground water through evaporation ponds.

Dead-band vs. machine-learning control systems: Analysis of control benefits and energy efficiency

In residential and commercial buildings, thermostat controllers have been typically utilized to maintain room temperature near desired set-point. Recently, advanced computing and statistical technologies, such as Fuzzy Inference System (FIS) and Artificial Neural Network (ANN) algorithms, were introduced to complement the control performance for optimal energy use in building thermal systems. However, most schemes were developed to control fuel use or fan motor speed in a plant or a system, and showed some disadvantages to immediately respond to sensitive changes in thermal demands for a zone scaled level.This paper introduces heating energy models capable of controlling the amount of supply air and its temperature simultaneously, and the FIS and ANN algorithms are developed to control the optimal supply air conditions for a heating season. Both the FIS and ANN models are compared to thermostat controllers with 4-step dead-band setups from normal to sensitive levels. The sum of errors, caused by the difference between desired set-point and controlled room temperatures, and the amount of energy supply are used to define control precision and energy efficiency of the control models. From the simulation results, the machine-learning based ANN controller averagely reduces control errors by 88% and mitigates increases in energy consumption by 2% in comparison with thermostat on/off controllers. The control system can be effective when various sensitive settings are required as a type of buildings and rooms without an excessive increase in energy use.

Optimized energy use through systematic short-term management of industrial waste incineration

The introduced work aims to systematic optimize detailed short-term scheduling for industrial waste incineration to support daily decision-making processes. The overall objective is to reduce the utilization of auxiliary fuel used to overcome waste related energy in the incineration process. The reduction is achieved through adequate mixing and scheduling of waste streams with different energy content and improved logistic strategies. With it, regulatory and technical constraints are fulfilled and holdups in production processes derived from bottlenecks in the waste treatment are avoided.The considered system consists of storage tanks, a piping network, tank wagons for waste transportation, unloading pumps and incineration lances. The optimization model is formulated as a mixed-integer linear programming (MILP) problem with a discrete time representation based on a single uniform grid. It consists of two blocks: i) waste transfer and mixing, and ii) the incineration process itself including energy calculations and constraints.The industrial case study of this work shows a saving potential of auxiliary fuel of up to 90%, leading to a reduction of CO2 emissions of up to 13%. Hence, the systematic scheduling of industrial waste incineration leads to an important reduction of auxiliary fuel consumption, resulting in economic and environmental benefits.

A Decision Support Framework for Smart Cities Energy Assessment and Optimization

Abstract Cities are becoming more and more of a focal point for our economies and societies, particularly because of the on-going urbanization, and the trend towards increasingly knowledge intensive economies as well as their growing share of resource consumption and emissions. Energy is an essential component of life in the cities, as it supports the whole spectrum of their economic activities and secures a certain level of quality of life to residents. To meet public policy objectives under these circumstances, cities need to change and develop in a smart way, without disregarding the issues of energy efficiency and sustainability. In this context, the aim of this paper is to present a Decision Support Framework able to assess and optimize the energy use in Smart Cities. The proposed methodology is addressed to the cities local authorities, so as to optimize the energy use in their premises and achieve significant reduction of CO2 emissions. The novel Framework includes two pillars: ‘Assessment’ and ‘Optimization’. The ‘Assessment’ pillar highlights the strengths, the underperforming sectors and the potentials of a city in terms of energy optimization. The ‘Optimization’ pillar includes a number of targeted action plans that can be used by the building energy managers of a city. The proposed actions in this pillar derive from the DSS for Energy Management component of the Framework that offers short-term scenarios in a weekly basis, and from the DSS for Energy Efficiency component that offers long-term scenarios in a yearly basis. Moreover, these two pillars combine a number of web based components. The ‘Assessment’ pillar uses The Smart City Energy Assessment Framework tool (e-SCEAF), which can provide fruitful results for assessing the energy behavior and performance of a city. The ‘Optimization’ pillar uses the Thermal Comfort Validator (TCV) with the relevant action plan and a Toolset for Assessing the Energy use of Buildings. TCV can assist the energy managers in adjusting thermal comfort parameters, in such a way as to optimize energy use and maintain comfort levels in accepted ranges. The Toolset for Assessing the Energy use of Buildings is able to collect real energy consumption data and calculate automatically the energy savings from a list of improvement scenarios. The novelty of the proposed Framework lies on the merging of multidisciplinary data sources from the following domains: weather, building monitoring, users’ feedback, energy prices and energy production.

Optimum configurations of annulus with triangular fins for laminar convection

Optimum configurations of a finned annulus with longitudinal fins of triangular cross-section have been investigated numerically for the enhancement of overall (hydraulic and thermal) performance so that optimum use of energy and saving of cost may be achieved. A steady, laminar and incompressible flow is considered in the fully-developed region of the finned annulus subjected to the thermal boundary condition of constant heat transfer rate per unit axial length. Optimization has been carried out by using genetic algorithm. Finite element method is employed to perform the numerical simulation of the flow and provide function values to the optimizer. Using surface flow area goodness factor as the objective function, various optimum configurations have been proposed depending on practical and industrial requirements. A comparison of the present optimum configurations has been carried out with those based on the Nusselt number as an objective function. The results indicate that the present objective function gives, in many cases, cost- and weight-efficient optimum configurations with considerable reduction in pressure loss and provides optimum use of energy along with saving of the cost. Relative performance measures recommend the use of at least 18 fins to have trade off between the gain in heat transfer coefficient and loss in the pressure gradient.

Biocatalysis in continuous-flow mode: A case-study in the enzymatic kinetic resolution of secondary alcohols via acylation and deacylation reactions mediated by Novozym 435®

AbstractEnzymatic kinetic resolution reactions are a well-established way to achieve optically active compounds. When enzymatic reactions are combined to continuous-flow methodologies, other benefits are added, including reproducibility, optimized energy use, minimized waste generation, among others. In this context, we herein report a case study involving lipase-mediated transesterification by acylation and deacylation reactions of secondary alcohols/esters in batch and continuous-flow modes. Acylation reactions were performed with high values of enantiomeric excess (72 up to >99%) and enantioselectivity (E > 200) for both batch and continuous-flow modes. On the other hand, for deacylation reactions using n-butanol as nucleophile, enatiomeric excess ranged between 38 to >99% and E from 6 to >200 were observed for batch mode. For deacylation reactions in continuous-flow mode, results were disappointing, as in some cases, very low or no conversion was observed. Enantiomeric excess ranged from 16 to >99% and enantioselectivity from 5 to >200 were observed. In terms of productivity, continuous-flow mode reactions were superior in both strategies (acylation: r from 1.1 up to 18.1-fold higher, deacylation: 2.8 up to 7.4- fold higher in continuous-flow than in batch mode).

A grey model approach to indoor air quality management in rooms based on real-time sensing of particles and volatile organic compounds

The study presents an attempt to develop a model for the management of indoor air quality based on real-time sensing of particulate matter (nano and micro particles) and volatile organic compounds. The development of the model used a grey box approach where the initial data on pollutant variation was collected during the experimental phase, and further applied to the pollutant mass balance model. The pollution sources have been analyzed in a controlled environment to obtain patterns of temporal variation, which have been approximated by mathematical functions. Approximations allowed the employment of pollutant mass balance model for determining the variation of pollutant source and further to modeling variation of pollutant concentration with changing air change rate. The proposed management approach can be applied to control indoor air quality in homes, assuring optimal utilization of the air handling unit in order to achieve the acceptable indoor air quality in the lowest time span and optimal energy use.

Determining system-wide energy use in an established metro network

Energy is becoming an increasingly important topic in all transport systems. However, when evaluating alternative methods for the optimisation of energy use, it is vital to obtain a thorough understanding of the energy flows within the system. While new systems generally have comprehensive automatic energy metering and monitoring of their components, there is much legacy infrastructure without this capability. This article develops a methodology to determine a breakdown of energy use for the Tyne and Wear Metro, the results of which are compared with other railway systems. This is complemented by an investigation into the energy consumption of stabled rolling stock.

Design & Simulation of PV Grid system with Dispatchable Supercapacitor

This paper presents a reliable, extended range power storage for grid connected PV systems. The power supply consists of solar PV source, a battery and Super capacitor (SC). Main source of power is battery, and is connected with super capacitor. These are connected at the starting and transient phase like overloading. Photovoltaic cell works for the steady condition. The total effect of such arrangement is to improve travel range, reduced size of battery , enhanced excellent response during overloading condition and improved battery life .Better performance which gives optimal use of energy, smooth ride and minimum size of sources of energy. Many stand-alone photovoltaic systems need storage device for providing steady state energy to the load when photovoltaicirradiation is not sufficient. Generally, Batteries are used for such application. Thus, providing a large peak current, like starting of motor, degrades plates of battery, results in devastation of battery. An alternate solution of providing heavy current is to connect battery with super capacitors forming an hybrid energy storage system, for which battery could provide steady state energy also the super capacitor can provide the peak power to connected load. A secondary source, solar panel module is available to charge battery and super capacitor.

A novel multi-market optimization problem for commercial heating, ventilation, and air-conditioning systems providing ancillary services using multi-zone inverse comprehensive room transfer functions

Electricity grids increasingly include demand response in not only the energy market, but also grid-stabilizing ancillary services markets. Commercial buildings can provide demand response through use of their heating, ventilating, and air-conditioning systems to access the buildings’ thermal storage capacity. Within a model predictive control framework, commercial buildings can optimize demand response while respecting thermal comfort and system limits. In this article, a novel multi-market optimization problem that minimizes total operating costs, including energy costs, and separate revenues from regulation and reserve markets, is proposed. The 24-hour multi-zone and multi-market optimization problem is solved using a multi-zone inverse comprehensive room transfer function model of an 18-zone office building and accompanying variable air volume heating, ventilating, and air-conditioning system model. Optimal energy use, ancillary service provision, energy cost, and ancillary service revenues are reported for eight scenarios, which highlight the impact of ancillary service provision on optimal energy use and the effect of thermal mass on demand response provision. This work improves the operating capabilities of an individual building using model predictive control and can also be used to better understand demand-side resource potential for energy and ancillary services from a grid-planning perspective.

When to eat? The influence of circadian rhythms on metabolic health: are animal studies providing the evidence?

As obesity and metabolic diseases rise, there is need to investigate physiological and behavioural aspects associated with their development. Circadian rhythms have a profound influence on metabolic processes, as they prepare the body to optimise energy use and storage. Moreover, food-related signals confer temporal order to organs involved in metabolic regulation. Therefore food intake should be synchronised with the suprachiasmatic nucleus (SCN) to elaborate efficient responses to environmental challenges. Human studies suggest that a loss of synchrony between mealtime and the SCN promotes obesity and metabolic disturbances. Animal research using different paradigms has been performed to characterise the effects of timing of food intake on metabolic profiles. Therefore the purpose of the present review is to critically examine the evidence of animal studies, to provide a state of the art on metabolic findings and to assess whether the paradigms used in rodent models give the evidence to support a 'best time' for food intake. First we analyse and compare the current findings of studies where mealtime has been shifted out of phase from the light-dark cycle. Then, we analyse studies restricting meal times to different moments within the active period. So far animal studies correlate well with human studies, demonstrating that restricting food intake to the active phase limits metabolic disturbances produced by high-energy diets and that eating during the inactive/sleep phase leads to a worse metabolic outcome. Based on the latter we discuss the missing elements and possible mechanisms leading to the metabolic consequences, as these are still lacking.

CH Panel Based Routing Scheme For Mobile Wireless Sensor Network

Mobile Wireless sensor networks (MWSNs) are resource constrained. Energy is one of the most important resources in such networks. Therefore, optimal use of energy is necessary. In this paper, we present a novel energy-efficient routing protocol for WSNs. The protocol is reliable in terms of data delivery at the base station (BS). We consider mobility in sensor nodes and in the BS. The proposed protocol is hierarchical and cluster based. Each cluster consists of one cluster head (CH) node, two deputy CH nodes, and some ordinary sensor nodes. The reclustering time and energy requirements have been minimized by introducing the concept of CH panel. At the initial stage of the protocol, the BS selects a set of probable CH nodes and forms the CH panel. Depending on the topology of the network, the data transmission from the CH node to the BS is carried out either directly or in multihop fashion. Moreover, alternate paths are used for data transmission between a CH node and the BS. Rigorous simulation results depict the energy efficiency, throughput, and prolonged lifetime of the nodes under the influence of the proposed protocol. Future scope of this work is outlined.

Day-ahead economic optimization of energy use in an olive mill

This article presents an economic case study on biomass and power dispatch focused on the olive oil extraction industry. A method is proposed to minimize the energy cost associated to olive oil production. This is realized through load shaping and optimal selection of the destination of subproducts and wastes. The mill and the loads linked to the extraction process are modeled using the energy hub concept, and an Economic Model Predictive Control (EMPC) based power and biomass dispatcher is introduced. The control strategy has been simulated over different scenarios to validate the optimization scheme.

E2R2: Energy-Efficient and Reliable Routing for Mobile Wireless Sensor Networks

Wireless sensor networks (WSNs) are resource constrained. Energy is one of the most important resources in such networks. Therefore, optimal use of energy is necessary. In this paper, we present a novel energy-efficient routing protocol for WSNs. The protocol is reliable in terms of data delivery at the base station (BS). We consider mobility in sensor nodes and in the BS. The proposed protocol is hierarchical and cluster based. Each cluster consists of one cluster head (CH) node, two deputy CH nodes, and some ordinary sensor nodes. The reclustering time and energy requirements have been minimized by introducing the concept of CH panel. At the initial stage of the protocol, the BS selects a set of probable CH nodes and forms the CH panel. Considering the reliability aspect of the protocol, it puts best effort to ensure a specified throughput level at the BS. Depending on the topology of the network, the data transmission from the CH node to the BS is carried out either directly or in multihop fashion. Moreover, alternate paths are used for data transmission between a CH node and the BS. Rigorous simulation results depict the energy efficiency, throughput, and prolonged lifetime of the nodes under the influence of the proposed protocol. Future scope of this work is outlined.

Optimal energy use of the collector tube in solar power tower plant

As one of the most important parts of the solar power tower plant, the receiver plays an important role in the high-efficiency operation of the solar power tower system. Obtaining the maximum available energy in the receiver is highly desired in real-world operations. In this paper heat transfer and exergy transfer methods are used to model the energy transfer process in a collector tube. Different from common analysis methods, in order to ensure the molten salt to obtain the maximum available energy, an objective function is proposed to convert the task into a constrained optimization problem. The gravitational search (GS) algorithm is employed to search for the optimal solution of the proposed objective function. Numerical results indicate that the proposed optimization method can find the optimal operation parameters under different conditions. The heat transfer and exergy transfer characteristics along the collector tube under the optimal working condition are revealed, which quantifies the available energy along the collector tube, as well as reveals the location of energy degradation in the tube. The research findings will provide a beneficial reference for the effective use of the solar energy.

Impact of orientation of residential neighborhoods on optimizing sustainable and equitable exposure of insolation—Case study of Sulaimani, Iraq

In the northern hemisphere, neighborhoods are often preferred to be laid out in a rectilinear gridiron pattern with half of the houses in double-lot blocks having south-facing facades for optimal use of available solar energy. Adjoining houses, with north-facing facades, receive minimal insolation, leading to an overall inequitable use of available insolation. This paper presents a method of determining the overall optimal block orientation using 3ds Max software with linear regression models. The city of Sulaimani, Iraq, is used to illustrate. Obtaining the optimal orientation is essential for guiding planners in the land subdivision process, before the lots are designed. To optimize sustainable and equitable exposure to insolation in the city of Sulaimani, the annual insolation value (AIV) was calculated based on the algebraic sum of the amount of insolation energy for each double facade at each 5°, then factored by the cooling and heating degree-day ratio for each month. These values represent the annual energy required for cooling and heating for each orientation. The insolation inequity index (III) was proposed to measure the inequity between various opposite orientations. Accordingly, the value of (III) is equal to one for the ideal case (zero inequity). All orientations were examined, and the (0°–180°) demonstrated the highest inequity (III=0.60), which indicates 40% inequity while the highest equity (III=0.98) was (110°–290°). Nevertheless, the last orientation was not the most sustainable because its total (AIV) was not the minimum. The optimal direction was determined to be (100°–280°), which has the minimum total (AIV) of 484kWh (maximum sustainability) with the largest value of (III=0.92) (maximum equity). It was found that if this optimal orientation was applied in Sulaimani, the inequity would have been reduced by 22% from III=0.70 in 1955 to III=0.92 in 2003.

Fuzzy-Logic Based Frequency Controller for Wind Farms Augmented With Energy Storage Systems

Displacement of conventional synchronous generators by non-inertial units such as wind or solar generators will result in reduced-system inertia affecting under-frequency response. Frequency control is important to avoid equipment damage, load shedding, and possible blackouts. Wind generators along with energy storage systems can be used to improve the frequency response of low-inertia power system. This paper proposes a fuzzy-logic based frequency controller (FFC) for wind farms augmented with energy storage systems (wind-storage system) to improve the primary frequency response in future low-inertia hybrid power system. The proposed controller provides bidirectional real power injection using system frequency deviations and rate of change of frequency (RoCoF). Moreover, FFC ensures optimal use of energy from wind farms and storage units by eliminating the inflexible de-loading of wind energy and minimizing the required storage capacity. The efficacy of the proposed FFC is verified on the low-inertia hybrid power system.