Search results for: energy system optimization models

Authors: Seon-Ho Yoon, Jin-Young Choi, Dong-Jun Won

Abstract:

This paper presents hierarchical operation strategies which are minimizing operation error between day ahead operation plan and real time operation. Operating power systems between centralized and decentralized approaches can be represented as hierarchical control scheme, featured as primary control, secondary control and tertiary control. Primary control is known as local control, featuring fast response. Secondary control is referred to as microgrid Energy Management System (EMS). Tertiary control is responsible of coordinating the operations of multi-microgrids. In this paper, we formulated 3 stage microgrid operation strategies which are similar to hierarchical control scheme. First stage is to set a day ahead scheduled output power of Battery Energy Storage System (BESS) which is only controllable source in microgrid and it is optimized to minimize cost of exchanged power with main grid using Particle Swarm Optimization (PSO) method. Second stage is to control the active and reactive power of BESS to be operated in day ahead scheduled plan in case that State of Charge (SOC) error occurs between real time and scheduled plan. The third is rescheduling the system when the predicted error is over the limited value. The first stage can be compared with the secondary control in that it adjusts the active power. The second stage is comparable to the primary control in that it controls the error in local manner. The third stage is compared with the secondary control in that it manages power balancing. The proposed strategies will be applied to one of the buildings in Electronics and Telecommunication Research Institute (ETRI). The building microgrid is composed of Photovoltaic (PV) generation, BESS and load and it will be interconnected with the main grid. Main purpose of that is minimizing operation cost and to be operated in scheduled plan. Simulation results support validation of proposed strategies.

Keywords: Battery Energy Storage System (BESS), Energy Management System (EMS), Microgrid (MG), Particle Swarm Optimization (PSO)

Procedia PDF Downloads 229

Authors: Ahmed R. Abdelaziz, Zaki M. I. Osha

Abstract:

Solar radiation data are of great significance for solar energy system design. This study aims at developing and calibrating new empirical models for estimating monthly mean daily global solar radiation on a horizontal surface in Alexandria, Egypt. Day length hours, sun height, day number, and declination angle calculated data are used for this purpose. A comparison between measured and calculated values of solar radiation is carried out. It is shown that all the proposed correlations are able to predict the global solar radiation with excellent accuracy in Alexandria.

Keywords: solar energy, global solar radiation, model, regression coefficient

Procedia PDF Downloads 369

Authors: Sholeh Motaghian, Pekka Toivanen, Keiji Haataja

Abstract:

The swift expansion of the transportation industry and its associated emissions have captured the focus of policymakers who are dedicated to upholding ecological sustainability. As a result, understanding the key contributors to transportation emissions is of utmost significance. Amidst the escalating transportation emissions, the significance of electric vehicles cannot be overstated. Electric vehicles play a critical role in steering us towards a low-carbon economy and a sustainable ecological setting. The effective integration of electric vehicles hinges on the development of energy consumption models capable of accurately and efficiently predicting energy usage. Enhancing the energy efficiency of electric vehicles will play a pivotal role in reducing driver concerns and establishing a vital framework for the efficient operation, planning, and management of charging infrastructure. In this article, the works done in this field are reviewed, and the advantages and disadvantages of each are stated.

Keywords: deep learning, electrical vehicle, energy consumption, machine learning, smart grid

Procedia PDF Downloads 28

Authors: M. Dezvarei, S. Morovati

Abstract:

In recent years, increasing usage of electrical energy provides a widespread field for investigating new methods to produce clean electricity with high reliability and cost management. Fuel cells are new clean generations to make electricity and thermal energy together with high performance and no environmental pollution. According to the expansion of fuel cell usage in different industrial networks, the identification and optimization of its parameters is really significant. This paper presents optimization of a proton exchange membrane fuel cell (PEMFC) parameters based on modified particle swarm optimization with real valued mutation (RVM) and clonal algorithms. Mathematical equations of this type of fuel cell are presented as the main model structure in the optimization process. Optimized parameters based on clonal and RVM algorithms are compared with the desired values in the presence and absence of measurement noise. This paper shows that these methods can improve the performance of traditional optimization methods. Simulation results are employed to analyze and compare the performance of these methodologies in order to optimize the proton exchange membrane fuel cell parameters.

Keywords: clonal algorithm, proton exchange membrane fuel cell (PEMFC), particle swarm optimization (PSO), real-valued mutation (RVM)

Procedia PDF Downloads 316

Authors: Majdi M. Alomari, Nafesah I. Alshdaifat, Mohammad S. Widyan

Abstract:

Different countries have introduced different schemes and policies to counter global warming. The rationale behind the proposed policies and the potential barriers to successful implementation of the policies adopted by the countries were analyzed and estimated based on different models. It is argued that these models enhance the transparency and provide a better understanding to the policy makers. However, these models are underpinned with several structural and baseline assumptions. These assumptions, modeling features and future prediction of emission reductions and other implication such as cost and benefits of a transition to a low-carbon economy and its economy wide impacts were discussed. On the other hand, there are potential barriers in the form political, financial, and cultural and many others that pose a threat to the mitigation options.

Keywords: energy models, environmental policy instruments, mitigating CO2 emission, economic wide impact

Procedia PDF Downloads 497

Authors: N. Chayaopas, W. Assawinchaichote

Abstract:

In order to maximize energy capturing from wind energy, controlling the doubly fed induction generator to have optimal power from the wind, generator speed and output electrical power control in wind energy system have a great importance due to the nonlinear behavior of wind velocities. In this paper purposes the design of a control scheme is developed for power control of wind energy system via H∞ fuzzy integral controller. Firstly, the nonlinear system is represented in term of a TS fuzzy control design via linear matrix inequality approach to find the optimal controller to have an H∞ performance are derived. The proposed control method extract the maximum energy from the wind and overcome the nonlinearity and disturbances problems of wind energy system which give good tracking performance and high efficiency power output of the DFIG.

Keywords: doubly fed induction generator, H-infinity fuzzy integral control, linear matrix inequality, wind energy system

Procedia PDF Downloads 315

Authors: Napat Watjanatepin, Wikorn Wong-Satiean

Abstract:

The objective of this research is to design and construct the PV-Wind hybrid autonomous system for the greenhouse plantation, and analyze the technical performance of the PV-Wind energy system. This design depends on the water consumption in the greenhouse by using 24 of the fogging mist each with the capability of 24 liter/min. The operating time is 4 times per day, each round for 15 min. The fogging system is being driven by water pump with AC motor rating 0.5 hp. The load energy consumed is around 1.125 kWh/d. The designing results of the PV-Wind hybrid energy system is that sufficient energy could be generated by this system. The results of this study can be applied as a technical data reference for other areas in the central part of Thailand.

Keywords: PV-Wind hybrid autonomous system, greenhouse plantation, fogging system, central part of Thailand

Procedia PDF Downloads 283

Authors: Mark Schudeleit, Christian Sieg, Ferit Küçükay

Abstract:

This paper describes how to dimension the electric components of a 48V hybrid system considering real customer use. Furthermore, it provides information about savings in energy and CO2 emissions by a customer-tailored 48V hybrid. Based on measured customer profiles, the electric units such as the electric motor and the energy storage are dimensioned. Furthermore, the CO2 reduction potential in real customer use is determined compared to conventional vehicles. Finally, investigations are carried out to specify the topology design and preliminary considerations in order to hybridize a conventional vehicle with a 48V hybrid system. The emission model results from an empiric approach also taking into account the effects of engine dynamics on emissions. We analyzed transient engine emissions during representative customer driving profiles and created emission meta models. The investigation showed a significant difference in emissions when simulating realistic customer driving profiles using the created verified meta models compared to static approaches which are commonly used for vehicle simulation.

Keywords: customer use, dimensioning, hybrid electric vehicles, vehicle simulation, 48V hybrid system

Procedia PDF Downloads 477

Authors: Mitat Uysal

Abstract:

A new met heuristic optimization algorithm called as Migrating Birds Optimization is used for curve fitting by rational cubic Bezier Curves. This requires solving a complicated multivariate optimization problem. In this study, the solution of this optimization problem is achieved by Migrating Birds Optimization algorithm that is a powerful met heuristic nature-inspired algorithm well appropriate for optimization. The results of this study show that the proposed method performs very well and being able to fit the data points to cubic Bezier Curves with a high degree of accuracy.

Keywords: algorithms, Bezier curves, heuristic optimization, migrating birds optimization

Procedia PDF Downloads 304

Authors: Wook-Won Kim, Je-Seok Shin, Jin-O Kim

Abstract:

This paper propose the method for optimal scheduling for battery energy storage system with reliability constraint of energy storage system in reliability aspect. The optimal scheduling problem is solved by dynamic programming with proposed transition matrix. Proposed optimal scheduling method guarantees the minimum fuel cost within specific reliability constraint. For evaluating proposed method, the timely capacity outage probability table (COPT) is used that is calculated by convolution of probability mass function of each generator. This study shows the result of optimal schedule of energy storage system.

Keywords: energy storage system (ESS), optimal scheduling, dynamic programming, reliability constraints

Procedia PDF Downloads 376

Authors: Mohammadhadi Mirmohammadi, Reza Safian, Hossein Haddad

Abstract:

This paper presents an innovative solution for complex multi-objective optimization problem which is a part of efforts toward maximizing rolling mill throughput and minimizing processing costs in tandem cold rolling. This computational intelligence based optimization has been applied to the rolling schedules of tandem cold rolling mill. This method involves the combination of two derivative-free optimization procedures in the form of nested loops. The first optimization loop is based on Improving Hit and Run method which focus on balance of power, force and reduction distribution in rolling schedules. The second loop is a real-coded genetic algorithm based optimization procedure which optimizes energy consumption and productivity. An experimental result of application to five stand tandem cold rolling mill is presented.

Keywords: derivative-free optimization, Improving Hit and Run method, real-coded genetic algorithm, rolling schedules of tandem cold rolling mill

Procedia PDF Downloads 666

Authors: Mahmoud Samkan

Abstract:

In this paper, the design and assessment of new coordination between Power System Stabilizers (PSSs) and Static Var Compensator (SVC) in a multimachine power system via statistical method are proposed. The coordinated design problem of PSSs and SVC over a wide range of loading conditions is handled as an optimization problem. The Bacterial Swarming Optimization (BSO), which synergistically couples the Bacterial Foraging (BF) with the Particle Swarm Optimization (PSO), is employed to seek for optimal controllers parameters. By minimizing the proposed objective function, in which the speed deviations between generators are involved; stability performance of the system is enhanced. To compare the capability of PSS and SVC, both are designed independently, and then in a coordinated manner. Simultaneous tuning of the BSO based coordinated controller gives robust damping performance over wide range of operating conditions and large disturbance in compare to optimized PSS controller based on BSO (BSOPSS) and optimized SVC controller based on BSO (BSOSVC). Moreover, a statistical T test is executed to validate the robustness of coordinated controller versus uncoordinated one.

Keywords: SVC, PSSs, multimachine power system, coordinated design, bacteria swarm optimization, statistical assessment

Procedia PDF Downloads 353

Authors: Afroditi Zamanidou, Dionysios Giannakopoulos, Konstantinos Manolitsis

Abstract:

A notable amount of electrical energy demand in many countries worldwide is used to cover public energy demand for road, square and other public spaces’ lighting. Renewable energy can contribute in a significant way to the electrical energy demand coverage for public lighting. This paper focuses on the sizing and design of a hybrid energy system (HES) exploiting the solar-wind energy potential to meet the electrical energy needs of lighting roads, squares and other public spaces. Moreover, the proposed HES provides coverage of the electrical energy demand for a Wi-Fi hotspot and a charging hotspot for the end-users. Alongside the sizing of the energy production system of the proposed HES, in order to ensure a reliable supply without interruptions, a storage system is added and sized. Multiple scenarios of energy consumption are assumed and applied in order to optimize the sizing of the energy production system and the energy storage system. A database with meteorological prediction data for 51 areas in Greece is developed in order to assess the possible deployment of the proposed HES. Since there are detailed meteorological prediction data for all 51 areas under investigation, the use of these data is evaluated, comparing them to real meteorological data. The meteorological prediction data are exploited to form three hourly production profiles for each area for every month of the year; minimum, average and maximum energy production. The energy production profiles are combined with the energy consumption scenarios and the sizing results of the energy production system and the energy storage system are extracted and presented for every area. Finally, the economic performance of the proposed HES in terms of Levelized cost of energy is estimated by calculating and assessing construction, operation and maintenance costs.

Keywords: energy production system sizing, Greece’s deployment potential, meteorological prediction data, wind-solar hybrid energy system, levelized cost of energy

Procedia PDF Downloads 124

Authors: Wu Xingchun, Chen Xi

Abstract:

Nowadays, China's building energy consumption constitutes 25% of the total energy consumption, half of which was caused by air conditioning in both summer and winter. The ventilation system in Chinese traditional residence, which is totally passive and environmentally friendly, works effectively to create comfortable indoor environment. The research on the ventilation system in Chinese traditional residence can provide advancements to architecture design and energy savings to the society. Through field investigation, case analysis, strategy proposing and other methods, it comes out that the location and layout, the structure system and the design of atrium are the most important elements for a good ventilation system. Taking every factor into consideration, techniques are deployed extensively such as the organization of draught, the design of the thermal pressure ventilation system and the application of modern materials. With the enlightenment of the ventilation system in Chinese traditional residence, we can take effective measures to achieve low energy consumption and sustainable architecture.

Keywords: ventilation system, chinese traditional residence, energy consumption, sustainable architecture

Procedia PDF Downloads 682

Authors: Julio Macedo

Abstract:

Several methodologies are now available to conceive the improvements of a process so that it becomes competitive as for example total quality, process reengineering, six sigma, define measure analysis improvement control method. These improvements are of different nature and can be external to the process represented by an optimization model or a discrete simulation model. In addition, the process stakeholders are several and have different desired performances for the process. Hence, the methodologies above do not have a tool to aid in the conception of the required improvements. In order to fill this void we suggest the use of intelligent reference models. A reference model is a set of qualitative differential equations and an objective function that minimizes the gap between the current and the desired performance indexes of the process. The reference models are intelligent so when they receive the current state of the problematic process and the desired performance indexes they generate the required improvements for the problematic process. The reference models are fuzzy cognitive maps added with an objective function and trained using the improvements implemented by the high performance firms. Experiments done in a set of students show the reference models allow them to conceive more improvements than students that do not use these models.

Keywords: continuous improvement, fuzzy cognitive maps, process competitiveness, qualitative simulation, system dynamics

Procedia PDF Downloads 58

Authors: Muhammad Abu-Khaizaran, Ahmad Faza’, Tariq Othman, Yahia Yousef

Abstract:

This paper presents a study to provide sufficient and reliable information about constructing a Photovoltaic energy profile of the Birzeit University campus (BZU) based on the weather forecast. The developed Photovoltaic energy profile helps to predict the energy yield of the Photovoltaic systems based on the weather forecast and hence helps planning energy production and consumption. Two models will be developed in this paper; a Clear Sky Irradiance model and a Cloud-Cover Radiation model to predict the irradiance for a clear sky day and a cloudy day, respectively. The adopted procedure for developing such models takes into consideration two levels of abstraction. First, irradiance and weather data were acquired by a sensory (measurement) system installed on the rooftop of the Information Technology College building at Birzeit University campus. Second, power readings of a fully operational 51kW commercial Photovoltaic system installed in the University at the rooftop of the adjacent College of Pharmacy-Nursing and Health Professions building are used to validate the output of a simulation model and to help refine its structure. Based on a comparison between a mathematical model, which calculates Clear Sky Irradiance for the University location and two sets of accumulated measured data, it is found that the simulation system offers an accurate resemblance to the installed PV power station on clear sky days. However, these comparisons show a divergence between the expected energy yield and actual energy yield in extreme weather conditions, including clouding and soiling effects. Therefore, a more accurate prediction model for irradiance that takes into consideration weather factors, such as relative humidity and cloudiness, which affect irradiance, was developed; Cloud-Cover Radiation Model (CRM). The equivalent mathematical formulas implement corrections to provide more accurate inputs to the simulation system. The results of the CRM show a very good match with the actual measured irradiance during a cloudy day. The developed Photovoltaic profile helps in predicting the output energy yield of the Photovoltaic system installed at the University campus based on the predicted weather conditions. The simulation and practical results for both models are in a very good match.

Keywords: clear-sky irradiance model, cloud-cover radiation model, photovoltaic, weather forecast

Procedia PDF Downloads 102

Authors: A. Bozkurt, C. Kocatepe, R. Yumurtaci, İ. C. Tastan, G. Tulun

Abstract:

Efficient use of energy, with the increase in demand of energy and also with the reduction of natural energy sources, has improved its importance in recent years. Most of the losses in the system from electricity produced until the point of consumption is mostly composed by the energy distribution system. In this study, analysis of the resulting loss in power distribution transformer and distribution power cable is realized which are most of the losses in the distribution system. Transformer losses in the real distribution system were analyzed by CYME Power Engineering Software program. These losses are disclosed for different voltage levels and different loading conditions.

Keywords: distribution system, distribution transformer, power cable, technical losses

Procedia PDF Downloads 615

Authors: Majid AghaAlikhani, Mostafa Hojati, Saeid Satari-Yuzbashkandi

Abstract:

This paper studies energy use patterns and relationship between energy input and yield for soybean (Glycine max (L.) Merrill) in Mazandaran province of Iran. In this study, data were collected by administering a questionnaire in face-to-face interviews. Results revealed that the highest share of energy consumption belongs to chemical fertilizers (29.29%) followed by diesel (23.42%) and electricity (22.80%). Our investigations showed that a total energy input of 23404.1 MJ.ha-1 was consumed for soybean production. The energy productivity, specific energy, and net energy values were estimated as 0.12 kg MJ-1, 8.03 MJ kg-1, and 49412.71 MJ.ha-1, respectively. The ratio of energy outputs to energy inputs was 3.11. Obtained results indicated that direct, indirect, renewable and non-renewable energies were (56.83%), (43.17%), (15.78%) and (84.22%), respectively. Three econometric models were also developed to estimate the impact of energy inputs on yield. The results of econometric models revealed that impact of chemical, fertilizer, and water on yield were significant at 1% probability level. Also, direct and non-renewable energies were found to be rather high. Cost analysis revealed that total cost of soybean production per ha was around 518.43$. Accordingly, the benefit-cost ratio was estimated as 2.58. The energy use efficiency in soybean production was found as 3.11. This reveals that the inputs used in soybean production are used efficiently. However, due to higher rate of nitrogen fertilizer consumption, sustainable agriculture should be extended and extension staff could be proposed substitution of chemical fertilizer by biological fertilizer or green manure.

Keywords: Cobbe Douglas function, economical analysis, energy efficiency, energy use patterns, soybean

Procedia PDF Downloads 302

Authors: Roghieh A. Biroon, Zoleikha Abdollahi

Abstract:

The recent growth of renewables, e.g., solar panels, batteries, and electric vehicles (EVs) in residential and small commercial sectors, has potential impacts on the stability and operation of power grids. Considering approximately 50 percent share of the residential and the commercial sectors in the electricity demand market, the significance of these impacts, and the necessity of addressing them are more highlighted. Utilities and power system operators should manage the renewable electricity sources integration with power systems in such a way to extract the most possible advantages for the power systems. The most common effect of high penetration level of the renewables is the reverse power flow in the distribution feeders when the customers generate more power than their needs. The reverse power flow causes voltage rise and thermal issues in the power grids. To overcome the voltage rise issues in the distribution system, several techniques have been proposed including reducing transformers short circuit resistance and feeder impedance, installing autotransformers/voltage regulators along the line, absorbing the reactive power by distributed generators (DGs), and limiting the PV and battery sizes. In this study, we consider a medium-scale battery energy storage to manage the power energy and address the aforementioned issues on voltage deviation and power loss increase. We propose an optimization algorithm to find the optimum size and location for the battery. The optimization for the battery location and size is so that the battery maintains the feeder voltage deviation and power loss at a certain desired level. Moreover, the proposed optimization algorithm controls the charging/discharging profile of the battery to absorb the negative power flow from residential and commercial customers in the feeder during the peak time and sell the power back to the system during the off-peak time. The proposed battery regulates the voltage problem in the distribution system while it also can play frequency regulation role in islanded microgrids. This battery can be regulated and controlled by the utilities or a third-party ancillary service provider for the utilities to reduce the power system loss and regulate the distribution feeder voltage and frequency in standard level.

Keywords: ancillary services, battery, distribution system and optimization

Procedia PDF Downloads 110

Authors: Fazıl Gökgöz, Fahrettin Filiz

Abstract:

Load forecasting has become crucial in recent years and become popular in forecasting area. Many different power forecasting models have been tried out for this purpose. Electricity load forecasting is necessary for energy policies, healthy and reliable grid systems. Effective power forecasting of renewable energy load leads the decision makers to minimize the costs of electric utilities and power plants. Forecasting tools are required that can be used to predict how much renewable energy can be utilized. The purpose of this study is to explore the effectiveness of LSTM-based neural networks for estimating renewable energy loads. In this study, we present models for predicting renewable energy loads based on deep neural networks, especially the Long Term Memory (LSTM) algorithms. Deep learning allows multiple layers of models to learn representation of data. LSTM algorithms are able to store information for long periods of time. Deep learning models have recently been used to forecast the renewable energy sources such as predicting wind and solar energy power. Historical load and weather information represent the most important variables for the inputs within the power forecasting models. The dataset contained power consumption measurements are gathered between January 2016 and December 2017 with one-hour resolution. Models use publicly available data from the Turkish Renewable Energy Resources Support Mechanism. Forecasting studies have been carried out with these data via deep neural networks approach including LSTM technique for Turkish electricity markets. 432 different models are created by changing layers cell count and dropout. The adaptive moment estimation (ADAM) algorithm is used for training as a gradient-based optimizer instead of SGD (stochastic gradient). ADAM performed better than SGD in terms of faster convergence and lower error rates. Models performance is compared according to MAE (Mean Absolute Error) and MSE (Mean Squared Error). Best five MAE results out of 432 tested models are 0.66, 0.74, 0.85 and 1.09. The forecasting performance of the proposed LSTM models gives successful results compared to literature searches.

Keywords: deep learning, long short term memory, energy, renewable energy load forecasting

Procedia PDF Downloads 232

Authors: Sadegh Torfi

Abstract:

Realization of anticipated energy efficiency from recuperative run-around energy recovery (RER) systems requires identification of the system components influential parameters. Because simulation modeling is considered as an integral part of the design and economic evaluation of RER systems, it is essential to calibrate the developed models and validate the performance predictions by means of comparison with data from experimental measurements. Several theoretical and numerical analyses on RER systems by researchers have been done, but generally the effect of distance between hot and cold flow is ignored. The objective of this study is to develop a thermohydroulic model for a typical RER system that accounts for energy loss from the interconnecting piping and effects of interconnecting pipes length performance of run-around energy recovery systems. Numerical simulation shows that energy loss from the interconnecting piping is change linear with pipes length and if pipes are properly isolated, maximum reduction of effectiveness of RER systems is 2% in typical piping systems.

Keywords: combined heat and power, heat recovery, effectiveness, CGS

Procedia PDF Downloads 177

Authors: Alexander Hedlund, Anna-Karin Stengard, Olof Björkqvist

Abstract:

A step towards reducing greenhouse gases and energy consumption is to collaborate with the energy system between several industries. This work is based on a case study on integration of pulp and paper mills with a district heating system in Sundsvall, Sweden. Present research shows that it is possible to make a significant reduction in the electricity demand in the mechanical pulping process. However, the profitability of the efficiency measures could be an issue, as the excess steam recovered from the refiners decreases with the electricity consumption. A consequence will be that the fuel demand for steam production will increase. If the fuel price is similar to the electricity price it would reduce the profit of such a project. If the paper mill can be integrated with a district heating system, it is possible to upgrade excess heat from a nearby kraft pulp mill to process steam via the district heating system in order to avoid the additional fuel need. The concept is investigated by using a simulation model describing both the mass and energy balance as well as the operating margin. Three scenarios were analyzed: reference, electricity reduction and energy substitution. The simulation show that the total input to the system is lowest in the Energy substitution scenario. Additionally, in the Energy substitution scenario the steam from the incineration boiler covers not only the steam shortage but also a part of the steam produced using the biofuel boiler, the cooling tower connected to the incineration boiler is no longer needed and the excess heat can cover the whole district heating load during the whole year. The study shows a substantial economic advantage if all stakeholders act together as one system. However, costs and benefits are unequally shared between the actors. This means that there is a need for new business models in order to share the system costs and benefits.

Keywords: energy system, cooperation, simulation method, excess heat, district heating

Procedia PDF Downloads 202

Authors: Rama Debbarma

Abstract:

The present study deals with the performance of Linear base isolation system to mitigate seismic response of structures characterized by random system parameters. This involves optimization of the tuning ratio and damping properties of the base isolation system considering uncertain system parameters. However, the efficiency of base isolator may reduce if it is not tuned to the vibrating mode it is designed to suppress due to unavoidable presence of system parameters uncertainty. With the aid of matrix perturbation theory and first order Taylor series expansion, the total probability concept is used to evaluate the unconditional response of the primary structures considering random system parameters. For this, the conditional second order information of the response quantities are obtained in random vibration framework using state space formulation. Subsequently, the maximum unconditional root mean square displacement of the primary structures is used as the objective function to obtain optimum damping parameters Numerical study is performed to elucidate the effect of parameters uncertainties on the optimization of parameters of linear base isolator and system performance.

Keywords: linear base isolator, earthquake, optimization, uncertain parameters

Procedia PDF Downloads 397

Authors: Kung-Jen Tu, Danny Vernatha

Abstract:

To assist individual departments within universities in their energy management tasks, this study explores the application of Building Information Modeling in establishing the ‘BIM based Energy Management Support System’ (BIM-EMSS). The BIM-EMSS consists of six components: (1) sensors installed for each occupant and each equipment, (2) electricity sub-meters (constantly logging lighting, HVAC, and socket electricity consumptions of each room), (3) BIM models of all rooms within individual departments’ facilities, (4) data warehouse (for storing occupancy status and logged electricity consumption data), (5) building energy management system that provides energy managers with various energy management functions, and (6) energy simulation tool (such as eQuest) that generates real time 'standard energy consumptions' data against which 'actual energy consumptions' data are compared and energy efficiency evaluated. Through the building energy management system, the energy manager is able to (a) have 3D visualization (BIM model) of each room, in which the occupancy and equipment status detected by the sensors and the electricity consumptions data logged are displayed constantly; (b) perform real time energy consumption analysis to compare the actual and standard energy consumption profiles of a space; (c) obtain energy consumption anomaly detection warnings on certain rooms so that energy management corrective actions can be further taken (data mining technique is employed to analyze the relation between space occupancy pattern with current space equipment setting to indicate an anomaly, such as when appliances turn on without occupancy); and (d) perform historical energy consumption analysis to review monthly and annually energy consumption profiles and compare them against historical energy profiles. The BIM-EMSS was further implemented in a research lab in the Department of Architecture of NTUST in Taiwan and implementation results presented to illustrate how it can be used to assist individual departments within universities in their energy management tasks.

Keywords: database, electricity sub-meters, energy anomaly detection, sensor

Procedia PDF Downloads 282

Authors: Wook-Won Kim, Je-Seok Shin, Jin-O Kim

Abstract:

As the penetration of Energy Storage System (ESS) increases in the power system due to higher performance and lower cost than ever, ESS is expanding its role to the ancillary service as well as the storage of extra energy from the intermittent renewable energy resources. For multi-ESS with different capacity and SOC level each other, it is required to make the optimal schedule of SOC level use the multi-ESS effectively. This paper proposes the energy allocation method for the multiple battery ESS with reliability constraint, in order to make the ESS discharge the required energy as long as possible. A simple but effective method is proposed in this paper, to satisfy the power for the spinning reserve requirement while improving the system reliability. Modelling of ESS is also proposed, and reliability is evaluated by using the combined reliability model which includes the proposed ESS model and conventional generation one. In the case study, it can be observed that the required power is distributed to each ESS adequately and accordingly, the SOC is scheduled to improve the reliability indices such as Loss of Load Probability (LOLP) and Loss of Load Expectation (LOLE).

Keywords: multiple energy storage system (MESS), energy allocation method, SOC schedule, reliability constraints

Procedia PDF Downloads 340

Authors: Shama Urooj

Abstract:

The present work investigates the relationship among financial inclusion, modernization, and energy performance in SCO member countries during the years 2011–2021. PCA is used to create composite indexes of financial inclusion, modernization, and energy performance. We used panel regression models that are both reliable and heteroscedasticity-consistent to look at the relationship among variables. The findings indicate that financial inclusion (FI) and modernization, along with the increased FDI, all appear to contribute to the energy performance in the SCO member countries. However, per capita GDP has a negative impact on energy performance. These results are unbiased and consistent with the robust results obtained by applying different econometric models. Feasible Generalized Least Square (FGLS) estimation is also used for checking the uniformity of the main model results. This research work concludes that there has been no policy coherence in SCO member countries regarding the coordination of growing financial inclusion and modernization for energy sustainability in recent years. In order to improve energy performance with modern development, policies regarding financial inclusion and modernization need be integrated both at national as well as international levels.

Keywords: financial inclusion, energy performance, modernization, technological development, SCO.

Procedia PDF Downloads 45

Authors: Ilham Ihoume, Rachid Tadili, Nora Arbaoui

Abstract:

The use of solar energy in agricultural applications has gained significant at‎tention ‎‎in recent years as a sustainable and environmentally friendly alternative to ‎‎conventional energy sources. In particular, solar drying of crops has ‎been identified ‎‎as an effective method to preserve agricultural produce while ‎minimizing energy ‎‎consumption and reducing carbon emissions. In this context, the present study ‎‎aims to evaluate the thermo-economic and ecological ‎performance of a solar-electric hybrid greenhouse dryer designed for grape ‎drying. The proposed system ‎‎integrates solar collectors, an electric heater, ‎and a greenhouse structure to create a ‎‎controlled and energy-efficient environment for grape drying. The thermo-economic assessment involves the ‎analysis of the thermal performance, energy ‎‎consumption, and cost-effectiveness of the solar-electric hybrid greenhouse dryer. ‎‎On the other ‎hand, the ecological assessment focuses on the environmental impact ‎‎of the ‎system in terms of carbon emissions and sustainability. The findings of this ‎‎‎study are expected to contribute to the development of sustainable agricultural ‎‎practices and the promotion of renewable energy technologies in the ‎context of ‎‎food production. Moreover, the results may serve as a basis for the ‎design and ‎‎optimization of similar solar drying systems for other crops and ‎regions.‎

Keywords: solar energy, sustainability, agriculture, energy ‎‎analysis‎

Procedia PDF Downloads 20

Authors: Mohammad Ali Farrokhpour

Abstract:

In the current decade and sustainable transportation systems, scooter sharing has attracted widespread attention as an environmentally-friendly means of public transportation which can help develop public transportation. The combination of scooters and subway in the area of sustainable transportation systems can provide a great many opportunities for developing access to public transportation. Of the challenges which have arisen and initiated discussions of interest about the implementation of a scooter-subway system to replace personal vehicles is the issue of routing in the aforementioned system. This has been chosen as the main subject of the present paper. Thus, the present paper provides an account for routing in this system. Because the issue of routing includes multiple factors such as time, costs, traffic, green spaces, etc., the above-mentioned problem is considered to be a multi-objective NP-hard optimization problem. For this purpose, the hybrid optimization approach of PSO-GA has been put forward in the present paper for the provided answers to be of higher accuracy and validity than those of normal optimization methods. The results obtained from modeling and problem solving for the case study in the MATLAB software are indicative of the efficiency and desirability of the model and the proposed approach for solving the model

Keywords: route planning, scooter sharing, public transportation, sharing system

Procedia PDF Downloads 54

Authors: Ghoname Abdullah, Hidekazu Nishimura

Abstract:

Dust accumulation on the photovoltaic module's surface results in appreciable loss and negatively affects the generated power. Hence, in this paper, the design of a photovoltaic array cleaning system is presented. The cleaning system utilizes one drive motor, two guide rails, and four sweepers during the cleaning process. The cleaning system was experimentally implemented for one month to investigate its efficiency on PV array energy output. The energy capture over a month for PV array cleaned using the proposed cleaning system is compared with that of the energy capture using soiled PV array. The results show a 15% increase in energy generation from PV array with cleaning. From the results, investigating the optimal scheduling of the PV array cleaning could be an interesting research topic.

Keywords: cleaning system, dust accumulation, PV array, PV module, soiling

Procedia PDF Downloads 105

Authors: Khaled M. El Naggar

Abstract:

This paper introduces a digital method for fault section identification in transmission lines. The method uses digital set of the measured short circuit current to locate faults in electrical power systems. The digitized current is used to construct a set of overdetermined system of equations. The problem is then constructed and solved using the proposed digital optimization technique to find the fault distance. The proposed optimization methodology is an application of simulated annealing optimization technique. The method is tested using practical case study to evaluate the proposed method. The accurate results obtained show that the algorithm can be used as a powerful tool in the area of power system protection.

Keywords: optimization, estimation, faults, measurement, high voltage, simulated annealing

Procedia PDF Downloads 372