Browsing by Author "Biyik, Emrah"

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Citation - WoS: 1
Citation - Scopus: 1
A day-ahead EMS for transformer aging mitigation in distribution systems via coordinated PV-BESS inverter control under dynamic thermal constraint
(ELSEVIER SCIENCE SA, 2026) Sezai Polat; Emrah Biyik; Hacer Sekerci Oztura; Oztura, Hacer Sekerci; Şekerci Öztura, Hacer; Polat, Sezai; Biyik, Emrah
This paper proposes a novel day-ahead energy management system (EMS) that integrates dynamic thermal rating (DTR) of distribution transformers into the co-optimization of active and reactive power flows from photovoltaic (PV) and battery energy storage systems (BESS). The model comprehensively incorporates inverter and battery degradation costs transformer insulation aging and inverter losses while respecting operational and thermal constraints through both soft and hard constraint formulations. Simulations are performed on a modified IEEE 33-bus distribution system under three operational scenarios. Results demonstrate that aging-related costs can be reduced by up to 78 % through the inclusion of aging cost as a soft constraint and up to 85 % via the enforcement of hard hot-spot temperature (HST) constraints-without the need for transformer or BESS capacity increases. In comparison increasing the BESS capacity from 750 kWh to 1250 kWh yields a 2.4 % decrease in operational cost and 21 % reduction in aging cost. Increasing the transformer capacity from 3000 kVA to 4000 kVA further reduces aging cost by 96 % and operational cost by 5.8 % albeit at significant capital expenditure. The proposed DTR-aware EMS allows for safe transformer operation beyond nominal ratings enabling deferred infrastructure upgrades while maintaining system reliability and economic efficiency.
Citation - WoS: 4
Citation - Scopus: 5
A Framework for Capacity Expansion Planning in Failure-Prone Flow-Networks via Systemic Risk Analysis
(Institute of Electrical and Electronics Engineers Inc., 2022) Nazlı Karatas Aygün; Önder Bulut; Emrah Biyik; Aygun, Nazl Karatas; Bulut, Onder; Biyik, Emrah
In this article a capacity expansion framework is proposed for failure-prone flow-networks. A systemic risk measure that quantifies the risk of unsatisfied demand due to cascaded edge failures is considered. To minimize the total cost of additional edge capacities while keeping the risk of unsatisfied demand below a certain threshold a general stochastic optimization problem is formulated. The distribution of unsatisfied demand is calculated via Monte-Carlo simulations embodied within a grid search algorithm that identifies the feasible region. Thereafter the cost-optimal edge capacity expansion plan is computed by a differential evolution algorithm. Contributions of this article are: 1) consideration of both immediate investment and future risk costs of capacity expansion plans, 2) a generic flow-network model that can be tuned for different real-life applications, 3) addressing the stochastic nature of both supply and demand simultaneously within a systemic risk framework, 4) use of eigenvector centrality for edge grouping in systemic risk analysis. An extensive numerical study is performed to investigate the effects of different edge grouping methods characteristics of stochastic components and cost parameters on the feasible region and optimal solution. The proposed framework is also demonstrated on a case study adapted from ERCOT 13-bus test system. © 2022 Elsevier B.V. All rights reserved.
Citation - WoS: 347
Citation - Scopus: 419
A key review of building integrated photovoltaic (BIPV) systems
(Elsevier B.V., 2017) Emrah Biyik; Mustafa Araz; A. Hepbasli; Mehdi Shahrestani; Runming Yao; Li Shao; Emmanuel A. Essah; Armando Coelho Oliveira; Teodosio del Caño; Elena Rico; Shahrestani, Mehdi; Hepbasli, Arif; Biyik, Emrah; Yao, Runming; Shao, Li; Araz, Mustafa; Atli, Yusuf Baver
Renewable and sustainable energy generation technologies have been in the forefront due to concerns related to environment energy independence and high fossil fuel costs. As part of the EU's 2020 targets it is aimed to reach a 20% share of renewable energy sources in final energy consumption by 2020 according to EU's renewable energy directive. Within this context national renewable energy targets were set for each EU country ranging between 10% (for Malta) and 49% (for Sweden). A large share of renewable energy research has been devoted to photovoltaic systems which harness the solar energy to generate electrical power. As an application of the PV technology building integrated photovoltaic (BIPV) systems have attracted an increasing interest in the past decade and have been shown as a feasible renewable power generation technology to help buildings partially meet their load. In addition to BIPV building integrated photovoltaic/thermal systems (BIPV/T) provide a very good potential for integration into the building to supply both electrical and thermal loads. In this study we comprehensively reviewed the BIPV and BIPVT applications in terms of energy generation amount nominal power efficiency type and performance assessment approaches. The two fundamental research areas in the BIPV and BIPVT systems are observed to be i) improvements on system efficiency by ventilation hence obtaining a higher yield with lowering the panel temperature ii) new thin film technologies that are well suited for building integration. Several approaches to achieve these objectives are reported in the literature as presented in this paper. It is expected that this comprehensive review will be beneficial to researchers and practitioners involved or interested in the design analysis simulation and performance evaluation financial development and incentives new methods and trends of BIPV systems. © 2018 Elsevier B.V. All rights reserved.
Citation - WoS: 168
Citation - Scopus: 211
A key review of wastewater source heat pump (WWSHP) systems
(Elsevier Ltd, 2014) A. Hepbasli; Emrah Biyik; Orhan Ekren; Huseyin Gunerhan; Mustafa Araz; Ekren, Orhan; Araz, Mustafa; Hepbasli, Arif; Gunerhan, Huseyin; Biyik, Emrah
Heat pumps (HPs) are part of the environmentally friendly technologies using renewable energy and have been utilized in the developed countries for years. Wastewater is seen as a renewable heat source for HPs. At the beginning of the 1980s waste (sewage) water source heat pumps (WWSHPs) were widely applied in North European countries like Sweden and Norway and partially applied in China. In the past two decades the WWSHP has become increasingly popular due to its advantages of relatively higher energy utilization efficiency and environmental protection. The present study comprehensively reviews WWSHP systems in terms of applications and performance assessments including energetic exergetic environmental and economic aspects for the first time to the best of the authors' knowledge. In this context a historical development of WWSHPs was briefly given first. Next wastewater potential and its characteristics were presented while a WWSHP system was introduced. The previously conducted studies on WWSHPs were then reviewed and classified in a tabulated form. Finally some concluding remarks were listed. The COP values of the reviewed studies ranged from 1.77 to 10.63 for heating and 2.23 to 5.35 for cooling based on the experimental and simulated values. The performance assessments are mostly made using energy analysis methods while the number of exergetic evaluations is very low and has not been comprehensively performed. It is expected that the comprehensive review here will be very beneficial to those dealing with the design analysis simulation and performance assessment of WWSHP systems. © 2017 Elsevier B.V. All rights reserved.
Citation - WoS: 20
Citation - Scopus: 23
A Model Predictive Control Design for Selective Modal Damping in Power Systems
(IEEE, 2015) Abhishek Jain; Emrah Biyik; Aranya Chakrabortty; Chakrabortty, Aranya; Biyik, Emrah; Jain, Abhishek
This paper presents a novel real-time predictive control technique to damp dominant inter-area oscillation modes in power systems. We first show that conventional Power System Stabilizers (PSS) in synchronous generators are best suited to damp only the intra-area oscillation modes and participate poorly in inter-area damping. We then design a centralized Model Predictive Controller (MPC) to provide supplementary control to these conventional PSSs based on a Selective Discrete Fourier Transform (SDFT) approach. The SDFT extracts the energies associated with the inter-area frequency components in the output spectrum of the system and uses this information to construct a weighting matrix Q. The MPC is then formulated as a quadratic minimization of the outputs using Q resulting in damping only the inter-area modes of interest. In reality however the most dominant DFT magnitudes will not be known ahead of time since they are decided by the location of the disturbance. Therefore we next augment the MPC design by predicting the dominant DFT magnitudes in the desired low frequency range using online measured data and tuning Q accordingly. We illustrate the effectiveness of the proposed approach using an IEEE 39-bus prototype power system model for the New England system.
Citation - WoS: 90
Citation - Scopus: 93
A predictive control strategy for optimal management of peak load thermal comfort energy storage and renewables in multi-zone buildings
(ELSEVIER, 2019) Emrah Biyik; Aysegul Kahraman; Biyik, Emrah; Kahraman, Aysegul
Buildings are responsible for about 40% of the global energy consumption where heating ventilation and air conditioning (HVAC) systems account for the most part of it. Continuous increase in the installation of new HVAC systems and higher penetration of renewables and energy storage in the building energy network require more sophisticated control approaches to realize the full potential of these systems. In this paper an optimal control framework to coordinate HVAC battery energy storage and renewable generation in buildings is developed. The controller aims to reduce peak load demand while achieving thermal comfort within industry standards. To facilitate this a simple lumped mathematical model that describes the zone transient thermal dynamics is structured with a minimal data from the building and is trained with actual thermal and electrical data. Next a model predictive control algorithm that takes into account building thermal dynamics battery state of charge renewable generation status and actual operational data and constraints is formulated to regulate HVAC demand battery power and building thermal comfort. The controller considers the changes in the outside dry-bulb air temperature electricity price required energy amount and comfort conditions simultaneously in order to find the proper optimal zone temperatures guaranteeing occupant comfort. The new controller was tested using data from a real building and preliminary results indicate that significant reduction in peak electrical power demand can be achieved by the proposed approach.
Citation - WoS: 5
Citation - Scopus: 4
A Reduced Order Modeling Methodology for Steam Turbine Clearance Control Design
(American Society of Mechanical Engineers (ASME) infocentral@asme.org, 2017) Emrah Biyik; Fernando Javier D'Amato; Arun K. Subramaniyan; Changjie Sun; Subramaniyan, Arun; Sun, Changjie; Biyik, Emrah; D'Amato, Fernando J.
Finite element models (FEMs) are extensively used in the design optimization of utility scale steam turbines. As an example by simulating multiple startup scenarios of steam power plants engineers can obtain turbine designs that minimize material utilization and at the same time avoid the damaging effects of large thermal stresses or rubs between rotating and stationary parts. Unfortunately FEMs are computationally expensive and only a limited amount of simulations can be afforded to get the final design. For this reason numerous model reduction techniques have been developed to reduce the size of the original model without a significant loss of accuracy. When the models are nonlinear as is the case for steam turbine FEMs model reduction techniques are relatively scarce and their effectiveness becomes application dependent. Although there is an abundant literature on model reduction for nonlinear systems many of these techniques become impractical when applied to a realistic industrial problem. This paper focuses on a class of nonlinear FEM characteristic of thermo-elastic problems with large temperature excursions. A brief overview of popular model reduction techniques is presented along with a detailed description of the computational challenges faced when applying them to a realistic problem. The main contribution of this work is a set of modifications to existing methods to increase their computational efficiency. The methodology is demonstrated on a steam turbine model achieving a model size reduction by four orders of magnitude with only 4% loss of accuracy with respect to the full order FEMs. © 2017 Elsevier B.V. All rights reserved.
Citation - WoS: 23
Citation - Scopus: 26
An online structurally constrained LQR design for damping oscillations in power system networks
(Institute of Electrical and Electronics Engineers Inc., 2017) Abhishek Jain; Aranya Chakrabortty; Emrah Biyik; Chakrabortty, Aranya; Biyik, Emrah; Jain, Abhishek
This paper presents an online distributed control design for suppressing inter-area oscillations in large power systems under structural constraints posed on the underlying communication network. The presence of multiple clusters of generators in a power system results in several inter-area oscillation modes. By modal analysis we first show that the contribution of each inter-area mode on the electromechanical state response of the generators is heavily dependent on the perturbed initial state of the system. We then take advantage of this observation to design structural constraints on the communication graph. A parallelized constrained linear quadratic regulator (LQR) design is then proposed to balance the tradeoff between performance and the level of sparsity induced in the network. Algorithms for practical implementation of the design are provided. Results are compared with the full order LQR and illustrated on the New England 39-bus power system model. © 2017 Elsevier B.V. All rights reserved.
Citation - WoS: 16
Citation - Scopus: 20
Cloud-based model predictive building thermostatic controls of commercial buildings: Algorithm and implementation
(Institute of Electrical and Electronics Engineers Inc., 2015) Emrah Biyik; James D. Brooks; Hullas Sehgal; Jigar J. Shah; Sahika Gency; Shah, Jigar; Gency, Sahika; Biyik, Emrah; Brooks, James D.; Sehgal, Hullas; Genc, Sahika
The contribution of this paper is in two-folds: 1) If more predictive and intelligent control of the thermostat setpoints with no explicit models of Root Top Units (RTUs) yet with simplistic lumped parameter thermal models of buildings can be effective in reducing a small commercial buildings summer-time peak load while adequately maintaining comfort levels and 2) how this simplistic indirect control approach to RTUs compare to more sophisticated direct control approaches in terms of peak-load reduction and cost. First the modelpredictive control approach is presented. Second the results of cloud-based implementation of the optimization algorithm at the two demonstration commercial buildings owned by General Electric (GE) optimizer characteristics different set point trajectories and their implication with regards to peak load and comfort and observations are described. On average the savings from the indirect optimal control strategy utilized in our approach through a cloud-based control implementation architecture is shown to be comparable to previously stated savings in literature from more sophisticated direct optimal control of RTUs while the comfort levels are the same as the non-optimal strategy or slightly better in some cases. © 2021 Elsevier B.V. All rights reserved.
Day-Ahead Energy Management in Networked Microgrids
(Institute of Electrical and Electronics Engineers Inc., 2024) Polat, Sezai; Korkut, Irmak Onal; Biyik, Emrah
Citation - WoS: 25
Citation - Scopus: 27
Distributed wide-area control of power system oscillations under communication and actuation constraints
(Elsevier Ltd, 2018) Abhishek Jain; Aranya Chakrabortty; Emrah Biyik; Chakrabortty, Aranya; Biyik, Emrah; Jain, Abhishek
In this paper a distributed Model Predictive Control design is presented for inter-area oscillation damping in power systems under two critical cyber–physical constraints — namely communication constraints that lead to sparsification of the underlying communication network and actuation constraints that respect the saturation limits of generator controllers. In the current state-of-art distributed controllers in power systems are executed over fixed communication topologies that are most often agnostic of the magnitude and location of the incoming disturbance signals. This often leads to a sub-optimal closed-loop performance. In contrast the communication topology for the proposed controller is selected in real-time after a disturbance event based on event-specific correlations of the generator states with the dominant oscillation modes that are excited by that event. Since these correlations can differ from one event to another so can the choice of the communication topology. These correlations are used to identify the most important sets of generators that must exchange state information for enhancing closed-loop damping of the inter-area modal frequencies. Effectiveness of this strategy is shown via simulations on the 48-machine 140-bus model for the Northeast Power Coordinating Council. © 2018 Elsevier B.V. All rights reserved.
Citation - WoS: 100
Citation - Scopus: 117
Heat exchanger applications in wastewater source heat pumps for buildings: A key review
(ELSEVIER SCIENCE SA, 2015) Oguzhan Culha; Huseyin Gunerhan; Emrah Biyik; Orhan Ekren; Arif Hepbasli; Culha, Oguzhan; Ekren, Orhan; Hepbasli, Arif; Gunerhan, Huseyin; Biyik, Emrah
Wastewater heat recovery applications are becoming widespread in energy saving applications. A sustainable and low emissions operation in air conditioning and heating processes is achieved by harvesting the otherwise wasted energy in wastewater through specially designed heat exchangers lying at the core of heat pumps. This combined system is called wastewater source heat pump. In this study a review of wastewater heat exchangers in wastewater source heat pump applications is presented and wastewater heat exchangers are classified in detail based on multiple features including utilization and construction methodology. Also the potential of wastewater types of wastewater source heat pumps and their applications are briefly discussed. (C) 2015 Elsevier B.V. All rights reserved.
Citation - WoS: 8
Citation - Scopus: 10
Model Predictive Building Thermostatic Controls of Small-to-Medium Commercial Buildings for Optimal Peak Load Reduction Incorporating Dynamic Human Comfort Models: Algorithm and Implementation
(IEEE, 2014) Emrah Biyik; Sahika Genc; James D. Brooks; Biyik, Emrah; Brooks, James D.; Genc, Sahika
The peak kW of a typical New York State office building is thought to primarily be a function of the HVAC system often the buildings largest load but may also be influenced by occupancy and other loads. First a simple lumped parameter model with a minimum amount of building's physical input data and trained with actual thermal and electrical data is considered to approximate the thermal/electric consumption performance of the building and HVAC system on a zonal basis. Then the lumped parameter model integrated with a dynamic human comfort model is used to develop optimized zonal thermostat setpoint schedules to minimize the cooling systems contribution to the buildings peak power load while maintaining human comfort at a desired level. A 24-hour weather and occupancy forecasts are also incorporated into the optimization algorithm. The key difference of our approach compared to previous approaches that utilize model-predictive control is that a minimal set of measurement profiles are utilized to reduce the installation cost resulting in a cost effective advanced controls solution for a large number of small and medium size office buildings. The model predictive optimization approach is implemented at multiple demonstration sites. The hardware architecture and software platform installed at one of the demonstration buildings are discussed. Finally it is demonstrated that the proposed controller can effectively minimize peak cooling load on the HVAC equipment while achieving a satisfactory thermal comfort inside the building.
Model Predictive Control for a 22-Bus Agricultural Microgrid Under ANN and Statistical PV Forecasts
(Institute of Electrical and Electronics Engineers Inc., 2025) Oztura, Hacer Sekerci; Korkut, Irmak Onal; Polat, Sezai; Biyik, Emrah
Citation - WoS: 22
Citation - Scopus: 23
Multiparameter-based product energy and exergy optimizations for biomass gasification
(Elsevier Ltd, 2021) Başar Ca̧ǧlar; Duygu Tavsanci; Emrah Biyik; Caglar, Basar; Tavsanci, Duygu; Biyik, Emrah
The thermodynamic modelling of biomass gasification was studied by using Gibbs free energy minimization approach. Different from the studies using the same approach the simultaneous presence of all gasifying agents (air H2O and CO2) was considered and a multiparameter optimization was applied to determine the synergetic effect of gasifying agents for hydrogen syngas with a specific H2/CO ratio and methane production. The performance of gasification was assessed by using technical and environmental performance indicators such as product yields cold gas efficiency exergy efficiency CO2 emission and the heat requirement of the gasifier. The results show that the simultaneous presence of gasifying agents does not create considerable changes in syngas yield H2 yield methane yield CGE and exergy efficiency while it allows to tune the H2/CO ratio and the heat requirement of the gasifier. The highest syngas yield is observed at T > 1100 K and 1 bar and when SBR > 0.5 and/or CBR > 0.8 with the absence of air at which CGE changes between 114% and 122% while exergy efficiency is between 77% and 86%. The results prove that CO2 offers several advantages as a gasifying agent and suggests that CO2 recycling from gasifier outlet is a useful option for the biomass gasification. © 2021 Elsevier B.V. All rights reserved.
Citation - WoS: 19
Citation - Scopus: 20
Numerical analysis of a near-room-temperature magnetic cooling system, Analyse numérique d'un système de froid magnétique proche de la température ambiante
(Elsevier Ltd, 2017) Mehmet Akif Ezan; Orhan Ekren; Cagri A.S. Metin; Ahmet Yilanci; Emrah Biyik; Salih Murat Kara; Ekren, Orhan; Yilanci, Ahmet; Kara, Salih Murat; Ezan, Mehmet Akif; Biyik, Emrah; Metin, Cagri
In this study for a near-room-temperature magnetic cooling system a decoupled multi-physics numerical approach (Magnetism Fluid Flow and Heat Transfer) is developed using a commercial CFD solver ANSYS-FLUENT as a design tool. User defined functions are incorporated into the software in order to take into account the magnetocaloric effect. Magnetic flux density is assumed to be linear during the magnetization and demagnetization processes. Furthermore the minimum and maximum magnetic flux densities (Bmin and Bmax) are defined as 0.27 and 0.98 respectively. Two different sets of analyses are conducted by assuming an insulated cold heat exchanger (CHEX) and by defining an artificial cooling load in the CHEX. As a validation case experimental work from the literature is reproduced numerically and the results show that the current methodology is fairly accurate. Moreover parametric analyses are conducted to investigate the effect of the velocity of heat transfer fluid (HTF) and types of HTF on the performance of the magnetic cooling system. Also the performance metrics of the magnetic cooling system are investigated with regards to the temperature span of the magnetic cooling unit and the cooling load. It is concluded that reducing the cycle duration ensures reaching lower temperature values. Similarly reducing the velocity of the HTF allows reducing the outlet temperature of the HTF. In the current system the highest temperature spans are obtained numerically as around 6 K 5.2 K and 4.1 K for the cycle durations of 4.2 s 6.2 s and 8.2 s respectively. © 2017 Elsevier B.V. All rights reserved.
Citation - WoS: 5
Citation - Scopus: 6
Optimal active and reactive power scheduling for inverter-integrated PV and BESS under inverter current constraints
(ELSEVIER SCIENCE SA, 2025) Sezai Polat; Emrah Biyik; Hacer Sekerci Oztura; Şekerci Öztura, Hacer; Oztura, Hacer Sekerci; Polat, Sezai; Biyik, Emrah
The intermittent nature of renewable energy complicates grid integration requiring an efficient Energy Management System (EMS). This study addresses day-ahead EMS in distribution systems (DS) with a focus on active and reactive power scheduling utilizing the reactive power support of inverters in Photovoltaic (PV) and Battery Energy Storage Systems (BESS). A novel current-based method is proposed accounting for current limits bus voltage inverter lifetime reduction costs and inverter losses modeled as load. This method impacts load flow bus voltage and voltage-dependent loads enabling optimal decisions for compensating inverter losses via the grid BESS or PV. Simulations on the IEEE 33 test system show a 5% reduction in inverter losses with the currentbased method and 6% with the traditional power-based method. Inverter lifetime reduction costs were minimized by 42% and 58% with the current- and power-based methods respectively under summer conditions. In winter reductions reached 49% and 14%. Crucially inverter output depends on bus voltage challenging the assumption of constant rated power. At voltages below 1.00 p.u. inverters underperform achieving only 209 kVA of a 215 kVA rating. These findings emphasize the need for accurate modeling to improve EMS performance and reliability in renewable energy systems.
Citation - WoS: 4
Citation - Scopus: 8
Optimal control of microgrids - Algorithms and field implementation
(Institute of Electrical and Electronics Engineers Inc., 2014) Emrah Biyik; Ramu Sharat Chandra; Biyik, Emrah; Chandra, Ramu
A microgrid is a collection of distributed generation assets storage devices and electrical and/or thermal loads connected to each other. In this paper a generic model-predictive control algorithm for microgrids is presented. The algorithm has been implemented at Bella Coola a remote community in British Columbia Canada. The approach comprises two parts: unit commitment to decide the optimal set of distributed generators that must be switched on to meet predicted load requirements and convex optimal control to minimize operational costs once the commitment is known. The unit commitment problem is recast as a 0-1 Knapsack problem and is solved via dynamic programming while the optimal dispatch problem is posed as a sparse linear programming problem and solved via off-the-shelf software. Worst-case complexity and scalability considerations and not optimality often drive algorithm choice in industrial control settings, therefore the solution proposed in this paper is efficient and can be rigorously bounded in terms of memory and run-time. Simulation results using real field data practical considerations and details of the implementation at Bella Coola are provided. © 2014 American Automatic Control Council. © 2014 Elsevier B.V. All rights reserved.
Citation - WoS: 8
Citation - Scopus: 11
Performance evaluation of a building integrated photovoltaic (BIPV) system combined with a wastewater source heat pump (WWSHP) system
(ELSEVIER SCIENCE BV, 2017) Mustafa Araz; Arif Hepbasli; Emrah Biyik; Mehdi Shahrestani; Runming Yao; Emmanuel Essah; Li Shao; Armando C. Oliveira; Orhan Ekren; Huseyin Gunerhan; Essah, Emmanuel; Shahrestani, Mehdi; Hepbasli, Arif; Biyik, Emrah; Yao, Runming; Araz, Mustafa; Gunerhan, Huseyin; FR DAmbrosio; Alfano; L Mazzarella; P Romagnoni
This paper deals with both energetic and exergetic performance assessments of two combined systems as a whole. The first one is a Building Integrated Photovoltaic (BIPV) system while the second one is a wastewater (WW) Source Heat Pump (WWSHP) system. Both systems were installed at Yasar University Izmir Turkey within the framework of EU/FP7 and the Scientific and Technological Research Council of Turkey (TUBITAK) funded projects respectively. The BIPV system was commissioned on 8 February 2016 and has been successfully operated since then while the WWSHP system was put into operation in October 2014. The BIPV system has a total peak power of 7.44 kW and consists of a total of 48 Crystalline Silicon (c-Si) modules with a gap of 150 mm between the modules and the wall and a peak power per PV unit of 155 W-p. The WWSHP system consists of three main subsystems namely (i) a WW system (ii) a WWSHP and (iii) an end user system. Two systems considered have been separately operated while the measured values obtained from both systems have been recorded for performance assessment purposes. In this study a combined system was conceptually formed and the performance of the whole system was evaluated using actual operational data and some assumptions made. Exergy efficiency values for the WWSHP system and the whole system were determined to be 72.23% and 64.98% on product/fuel basis while their functional exergy efficiencies are obtained to be 20.93% and 11.82% respectively. It may be concluded that the methodology presented here will be very beneficial to those dealing with the design and performance analysis and evaluation of BIPV and WWHP systems. (C) 2017 The Authors. Published by Elsevier Ltd.
Citation - WoS: 1
Reduced order modeling for clearance control in turbomachinery
(Institute of Electrical and Electronics Engineers Inc., 2016) Emrah Biyik; Fernando Javier D'Amato; Arun K. Subramaniyan; Changjie Sun; Subramaniyan, Arun; Sun, Changjie; Biyik, Emrah; D'Amato, Fernando J.
Finite element models (FEMs) are extensively used in the design optimization of utility scale steam turbines. As an example by simulating multiple startup scenarios of steam power plants engineers can obtain turbine designs that minimize material utilization and at the same time avoid the damaging effects of large thermal stresses or rubs between rotating and stationary parts. Unfortunately FEMs are computationally expensive and only a limited amount of simulations can be afforded to get the final design. For this reason numerous model reduction techniques have been developed to reduce the size of the original model without a significant loss of accuracy. When the models are nonlinear as is the case for steam turbine FEMs model reduction techniques are relatively scarce and their effectiveness becomes application dependent. Although there is an abundant literature on model reduction for nonlinear systems many of these techniques become impractical when applied to a realistic industrial problem. This paper focuses in a class of nonlinear FEM characteristic of thermo-elastic problems with large temperature excursions. A brief overview of popular model reduction techniques is presented along with a detailed description of the computational challenges faced when applying them to a realistic problem. The main contribution of this work is a set of modifications to existing methods to increase their computational efficiency. The methodology is demonstrated on a steam turbine model achieving a model size reduction by four orders of magnitude with only 5% loss of accuracy with respect to the full order FEMs. These practical implementations enable the calculation of multiple additional design scenarios. © 2017 Elsevier B.V. All rights reserved.