Optimize Energy Usage Research Articles

Direct Digital Manufacturing in the Context of a Circular Economy

Additive manufacturing technologies have evolved from prototype to part production. Coupling this shift with organizational transformations evolved rapid prototyping industry into Direct Digital Manufacturing (DDM) industry. Any evolution in production systems is now, more than ever before, dependent on sustainability principles. The development of the DDM industry must be guided by these principles, taking the chance it offers to change the production paradigm. Circular Economy (CE) is a shift in the production and resource management model, and one of the ways to work towards sustainability. Coupling DDM with CE principles is thus contributing to change industrial production to a more sustainable one. This paper intends to relate DDM technologies with CE principles, to identify aspects where DDM is contributing to CE, as well as aspects that should be explored further for that purpose. It is observed that DDM can enable optimization of material and energy usage, modify logistics towards de-localized production and recycling and enable prolonged lifespan of products through better access to spare parts, for instance. It is also observed that DDM has good potential to shift materials usage towards natural materials, especially in a context of consumer or local community production, but not so much within the current industrial context. Education is shown to play a pivotal role, since incorporating circular economy principles in educational contexts should spark a shift in consumer perspectives, modifying demand and hence, industrial production.

Memory of Periodic Thermal Stimulation in an Immune Complex

AbstractProteins search their conformational space in order to attain the native fold and bind productively to relevant biological partners. Most proteins must be able to alternate between at least one active conformational state back to an inactive conformer, especially for macromolecules that perform work and need to optimize energy usage. This property may be invoked by a physical stimulus (eg. temperature) or by a chemical ligand, and may occur through mapping of the protein external environment onto a subset of protein conformers. We have stimulated with temperature cycles two partners of an immune complex before and after assembly. We have revealed with calorimetry that properties of the external stimulus are also found in the characteristics of the immune complex (i. e. periodic variations in the binding affinity). These results are important for delineating the bases of molecular memory ex vivo and may serve in the optimization of protein based sensors.

Optimization of Energy Usage of the Building Envelope Material at the Rental Office Buildings

This study aims to determine the effect of materials used in building envelopes on energy use in office buildings. To obtain energy use analysis data, ASHRAE 90.1 - 2013 based parameters are used in the Sefaira Building Simulation application. The building analyzed will be simulated, using variables such as sunlight conduction with roofs, walls, building window ratios, gap ratios in buildings, and use of electrical equipment per square meter. Based on the analysis carried out, the use of building energy by using standard material specifications from the application reaches 180 kWh / m2 / yr from what is supposed to be 79 kWh / m2 / yr. After being analyzed, a specification change is given to the liquid application so that the results of the analysis are 89 kWh / m2 / yr. So that the energy that can be reduced reaches 91 kWh / m2 / yr. This proves that the selection of building material specifications can affect energy use in rental office buildings.

Optimized energy consumption model for smart home using improved differential evolution algorithm

This paper proposes an improved enhanced differential evolution algorithm for implementing demand response between aggregator and consumer. The proposed algorithm utilizes a secondary population archive, which contains unfit solutions that are discarded by the primary archive of the earlier proposed enhanced differential evolution algorithm. The secondary archive initializes, mutates and recombines candidates in order to improve their fitness and then passes them back to the primary archive for possible selection. The capability of this proposed algorithm is confirmed by comparing its performance with three other well-performing evolutionary algorithms: enhanced differential evolution, multiobjective evolutionary algorithm based on dominance and decomposition, and non-dominated sorting genetic algorithm III. This is achieved by testing the algorithms' ability to optimize a multi-objective optimization problem representing a smart home with demand response aggregator. Shiftable and non-shiftable loads are considered for the smart home which model energy usage profile for a typical household in Johannesburg, South Africa. In this study, renewable sources include battery bank and rooftop photovoltaic panels. Simulation results show that the proposed algorithm is able to optimize energy usage by balancing load scheduling and contribution of renewable sources, while maximizing user comfort and minimizing peak-to-average ratio.

Nonstationary convective drying of raspberries, assisted by microwaves and ultrasound

This study was conducted to investigate the drying characteristics and quality of raspberries dried in non-stationary conditions. Seven drying programs were carried out, including convective (CV) drying as a reference. The non-stationary-hybrid programs were based on continuous CV drying with intermittent microwave and ultrasound assistance. The Midilli–Kucuk model was used successfully to describe the drying kinetics of raspberry fruits. The comparison between moisture ratio, drying rate, diffusion coefficient, energy consumption, and quality analysis, showed that non-stationary-hybrid drying improves process kinetics and results in less color change, higher anthocyanin retention, and better texture profile analysis characteristics with optimal energy usage than other methods. In addition, the physical and microstructural changes occurred during different drying processes were discussed.

Optimal variables estimation for energy reduction via a remote supervisory control: application to a counter-flow rotary dryer

This research anatomizes an automatic mode control of a counter flow rotary dryer by variable speed drive technology, to control moisture content of product in an organic fertilizer drying process. Effects of rotary dryer cyclone blower and biogas blower were investigated on a fertilizer production by the 3k factorial experiment technique. Response surface methodology was employed to determine optimum variables. The multiple-response was revealed that the rotary dryer, the cyclone blower, and the biogas blower were 90 %, 48 %, and 92 %, respectively. These values were observed to make the system to consume electricity at the rate of 8.91 kW/h and the product moisture was observed at 18.90 % db. To inspect control system accuracy and accountability, the results obtained from the mathematical model was compared with the data from supervisory control and data acquisition system and with the data from real measurement also. The output responses were the electric power used and the product moisture obtained. The statistical investigation determined the optimization of energy usage.

Digital Energy Hub for Optimizing Energy Usage: A Review

Energy usage as it relates to its security and management is an important aspect that all organizations having a vested stake in power production should be concerned with in these coming years. In this respect, harnessing the knowledge so that it may benefit various sectors, from the power producer right down to the customers, can be achieved by way of the digital energy hub, as proposed in this paper. We first put into context the workings and functions of such a digital platform, and then proceed to outline how it could benefit the many parties involved. Lastly, we take into account the challenges that needs to be addressed for its successful implementation, in which information security and privacy is a top priority amongst other issues.

Energy efficiency optimization in big data processing platform by improving resources utilization

Big data creates tremendous value for humanity, but also places a heavy burden on the environment. Energy consumption of computing platforms, especially big data processing platforms, cannot be ignored, and optimization of energy usage is imperative. To the out-of-core data processing, this paper proposes that the energy efficiency of a big data processing platform is closely related to the utilization of its computing resources; and an efficient resource allocation strategy for data processing tasks improves the platform’s resources utilization. To improve the resources utilization, different resources are allocated according to a task-related Best Resource Ratio (BRR for short), such as “cpu, disk, network in the ratio of 1:2:4″, rather than the resource’s quantity, such as “cpu = 1 GHz, network = 20MB/s”. We deduce the BRR of data processing tasks, and design a resource ratio based approach (R2), which includes a task scheduling algorithm and resource allocation algorithm, for energy efficiency optimization. Experiments show that the R2 approach can improve energy efficiency by 10%, 10% and 6% compared to FIFO, Capacity and Fair schedulers respectively, by maximizing resource utilization of a 12-node MapReduce platform.

Energy Audit with Innovative Technology Management for Resourcing the Clean Energy and Sustainability in India

Energy is an essential input to the overall development of the economy. It provides light and fuel to millions of households, industry, agriculture, commerce all service sectors and so on. Since energy is a critical component, development of conventional and non-conventional forms of energy for meeting the growing demand of the society at reasonable price and quality is the responsibility of the government. Energy Audit is an important and vital tool in the management of energy both at industry and nation level. It is required for improvising the efficient management practices in energy production, utilization and distribution with better technology and to thereby conserve for future growth and development. With the growing importance for industrial sectors in the country’s development and increasing energy consumptions, it has become essential and necessity to opt for more optimization methods in the consumption of energy. A saving of 15 to 30% can be done by optimal usage of energy at home. Energy conservation and safety is the topmost priority in today’s world to have a consistent growth, increase in production and to protect our environment. Energy audit and its management is instrumental to cope with the variation in the cost of energy, to identify the appropriate mixes of energy, to improvise the energy conservative equipment and technologies. Along with innovative technology for energy consumptions we also require innovative methods in the management of energy audit to help the country with efficient energy management system, reduce cost and save energy for future requirements. To study and understand the need for Energy audit with innovative technology management in India. To analyze its importance for resourcing clean energy and sustainability in India.

Simultaneous Energy and Water Optimisation in Shale Exploration

This work presents a mathematical model for the simultaneous optimisation of water and energy usage in hydraulic fracturing using a continuous time scheduling formulation. The recycling/reuse of fracturing water is achieved through the purification of flowback wastewater using thermally driven membrane distillation (MD). A detailed design model for this technology is incorporated within the water network superstructure in order to allow for the simultaneous optimisation of water, operation, capital cost, and energy used. The study also examines the feasibility of utilising the co-produced gas that is traditionally flared as a potential source of energy for MD. The application of the model results in a 22.42% reduction in freshwater consumption and 23.24% savings in the total cost of freshwater. The membrane thermal energy consumption is in the order of 244 × 103 kJ/m3 of water, which is found to be less than the range of thermal consumption values reported for membrane distillation in the literature. Although the obtained results are not generally applicable to all shale gas plays, the proposed framework and supporting models aid in understanding the potential impact of using scheduling and optimisation techniques to address flowback wastewater management.

Speed vs Efficiency and Storage Type in Portable Energy Systems

Portable power management systems must optimise power interfacing, storage and routing, to meet application specific functionality requirements. Two key aspects are reliability and efficiency. For reliable operation, it is required that powering on/off the system must occur in a planned manner. For efficient operation, it is desired that the system is powered for an optimal amount of time. maximizing its useful operational outcome per unit of energy consumed. This can be achieved by optimizing energy usage based on the anticipated energy income and power demand of duty-cycled power consumers. Both battery and supercapacitor storage can be employed to meet energy and power density demand, on both sides, and to enable fast transition from cold-starting to active power management. A simplified model is used to calculate the reliability of a simple solar-powered microsystem. The modelling of dynamically configurable interfacing and storage may enable a new generation of power management, providing reliable power from irregular and small energy sources.

Unconventional methods for pressure loss reduction in standard pipe elements

Abstract Reduction of pressure at pump houses are the most feasible and most advantageous as the pipe design method that is used, is more than 200 years old and is based up on 19th century production technology. My research focuses on a general approach on improving and reducing the pressure loss of these pipe elements with the help of non-conventional methods, thus resulting in a lower and more optimal energy usage of pump houses. The problematic zones are identified with the help of numerical modelling, geometry changes can be made and tested the same method. The geometrical changes aiming at pressure loss reduction follow non-conventional ideas, form hemodynamic and other biomechanics sources. Pipes in the pump houses are designed, for more than 50 years of operation. Even a small pressure loss reduction with this new method will mean large amount of energy saving in total. The results show that 15%–60% of pressure loss reduction is feasible, according to the complexity of the geometry. Pressure loss reduction will reduce energy consumption of water pumps which will result in a more efficient water works operation.

Optimisation of energy usage in ceramic kiln using pinch technique

The Pinch technology is one of the most advanced methodologies for energy saving in processes and total sites based on thermodynamic principles. In ceramic industry, energy distribution in kiln is very complex. The pinch analysis was used to minimise energy levels for ceramic kiln during operation at Phuoc Du Long ceramic company in Vietnam. Using Pinch technology, it was possible to identify appropriate changes in the core process conditions that could have an impact on energy savings. After the heat and material balance was established, targets for energy saving could be set prior to the design of the heat exchanger network in ceramic kiln. The results showed that the efficiency of the heat exchanger in the flue heat exchanger network had been determined. This also indicated that at the optimisation conditions, the heat loss was at a minimum. The heat and material balance were established in ceramic kiln. From the basic heat and material balance inside the old type of ceramic kiln, the energy lost via flue gas emission and heat transfer was found to be about 600 kJ. The Pinch point at 820 °C was determined to give a chance for energy saving.

Real-time energy management for electric arc furnace operation

Electric arc furnaces are used extensively in the steel industry for steel production. Development of energy savings strategies for the highly energy-intensive batch process is extremely challenging due to the complexity of the process and lack of measurements due to the harsh operating conditions. Here we introduce a new energy management approach that effectively curtails the energy cost in real-time through the implementation of economically optimal operating decisions. An economics- oriented shrinking horizon nonlinear model predictive control (NMPC) algorithm that exploits time-varying electricity prices is coupled with a multi-rate moving horizon estimator (MHE) to form an integrated decision- making framework. With a detailed first-principles dynamic model functioning at the core, the multi-variable interactions and plant variations are successfully incorporated into the control strategy to achieve reliable performance. We also present a novel initialization scheme for obtaining fast on-line solutions of the economic NMPC and multi-rate MHE dynamic optimization problems. Using this initialization algorithm, we show that the optimal input decisions are obtained with sufficient computational speed for real-time implementation. The energy usage optimization results indicate a significant reduction in the operating cost and peak electricity demand compared to the case where the electricity price profile is not updated.

Big Data Analytics for Discovering Electricity Consumption Patterns in Smart Cities

New technologies such as sensor networks have been incorporated into the management of buildings for organizations and cities. Sensor networks have led to an exponential increase in the volume of data available in recent years, which can be used to extract consumption patterns for the purposes of energy and monetary savings. For this reason, new approaches and strategies are needed to analyze information in big data environments. This paper proposes a methodology to extract electric energy consumption patterns in big data time series, so that very valuable conclusions can be made for managers and governments. The methodology is based on the study of four clustering validity indices in their parallelized versions along with the application of a clustering technique. In particular, this work uses a voting system to choose an optimal number of clusters from the results of the indices, as well as the application of the distributed version of the k-means algorithm included in Apache Spark’s Machine Learning Library. The results, using electricity consumption for the years 2011–2017 for eight buildings of a public university, are presented and discussed. In addition, the performance of the proposed methodology is evaluated using synthetic big data, which cab represent thousands of buildings in a smart city. Finally, policies derived from the patterns discovered are proposed to optimize energy usage across the university campus.

The role of knowledge about user behaviour in demand response management of domestic hot water usage

Load balancing is an important topic in smart grid systems. Dynamic pricing is a common approach to achieve a better balance between renewable energy production and energy usage. This assumes that individual households adapt their energy usage patterns based on energy prices. However, the actual behaviour of consumers in a household is an uncertain factor that might influence the effectiveness of pricing strategies. In this paper, we investigate to what extent knowledge about actual user behaviour can contribute to local optimization of energy usage. We use simulations to study whether a smart heating system that applies a pre-heating strategy for domestic water during periods of low prices can benefit from good predictions of the user behaviour, in financial terms or in terms of energy saving. Also, we use the simulations to investigate the effect of different goal temperatures for the pre-heating strategy. The results show that pre-heating does not make a difference with respect to the energy efficiency, but that during cold months, pre-heating can result in a financial benefit. In addition, we calculate what certainty about the user behaviour is needed to be able to effectively use pre-heating during the warmer summer month. These results can help to design residential energy optimization systems.

Fuzzy Logic System for Intermixed Biogas and Photovoltaics Measurement and Control

This study develops a new integrated measurement and control system for intermixed biogas and photovoltaic systems to achieve safe and optimal energy usage. Literature and field studies show that existing control methods on small- to medium-scale systems fall short of comprehensive system optimization and fault diagnosis, hence the need to revisit these control methods. The control strategy developed in this study is intelligent as it is wholly based on fuzzy logic algorithms. Fuzzy logic controllers due to their superior nonlinear problem solving capabilities to classical controllers considerably simplify controller design. The mathematical models that define classical controllers are difficult or impossible to realize in biogas and photovoltaic generation process. A microcontroller centered fuzzy logic measurement and control embedded system is designed and developed on the existing hybrid biogas and photovoltaic installations. The designed system is able to accurately predict digester stability, quantify biogas output, and carry out biogas fault detection and control. Optimized battery charging and photovoltaic fault detection and control are also successfully implemented. The system is able to optimize the operation and performance of biogas and photovoltaic energy generation.

Turkey's energy system development: linking an energy supply model with an industrial simulation model and solving it iteratively

Turkey is in the progress to include nuclear energy to its electricity generation capacity. The energy modelling studies for Turkey mainly focus on usage of renewable energy and local fossil fuels and include nuclear power plants (NPP) only with their electricity generation capacities without taking into consideration the front- and back-ends of the nuclear fuel cycle. This study takes into consideration the life cycle assessment (LCA) of nuclear energy based on optimisation of energy system costs and usage of energy resources under atmospheric CO2 and SO2 emission constraints using MESSAGE iteratively with an industrial simulation model. This iterative modelling calculates the marginal costs of final energy generation and energy demands for domestic production. The results of this study are assessed using economic, environmental and social indicators. The study concludes that both environmental and nuclear energy scenarios are viable options to set national atmospheric CO2 and SO2 emission targets for Turkey.

Turkey's energy system development: linking an energy supply model with an industrial simulation model and solving it iteratively

Turkey is in the progress to include nuclear energy to its electricity generation capacity. The energy modelling studies for Turkey mainly focus on usage of renewable energy and local fossil fuels and include nuclear power plants (NPP) only with their electricity generation capacities without taking into consideration the front- and back-ends of the nuclear fuel cycle. This study takes into consideration the life cycle assessment (LCA) of nuclear energy based on optimisation of energy system costs and usage of energy resources under atmospheric CO2 and SO2 emission constraints using MESSAGE iteratively with an industrial simulation model. This iterative modelling calculates the marginal costs of final energy generation and energy demands for domestic production. The results of this study are assessed using economic, environmental and social indicators. The study concludes that both environmental and nuclear energy scenarios are viable options to set national atmospheric CO2 and SO2 emission targets for Turkey.

Performance investigation of vapour recompressed batch distillation for separating ternary wide boiling constituents

The vapour recompression scheme (VRC) has been very effective in continuous distillation for energy intensification. The applicability of this scheme for the separation of multicomponent wide boiling con- stituents in batch distillation is a major challenge, because of the unsteady nature of the batch. In this study, the vapour recompression scheme has been implemented for the separation of multicomponent wide boiling constituents in the batch distillation. For the optimal usage of energy from compressed vapours manipulation of top tray vapour or external energy is done. A comparative study of the vapour recompressed batch distillation having a variable speed single compressor (SVRBD) and double stage compressor (DVRBD) with conventional batch distillation in terms of energy savings and total annual- ized cost is done. The VRC schemes achieve an energy savings of 50% and 10.03% total annualized cost (TAC) for SVRBD and DVRBD achieve 52% energy savings and 12.21% TAC with a payback period of 10 years.