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Records with Keyword: Optimization
Showing records 1 to 25 of 56. [First] Page: 1 2 3 Last
Gain Scheduling of a Robust Setpoint Tracking Disturbance Rejection and Aggressiveness Controller for a Nonlinear Process
Veeramani Bagyaveereswaran, Pachiyappan Arulmozhivarman
September 13, 2019 (v1)
Keywords: controller, gain scheduling, Optimization, performance criteria, PID, regulatory, servo
In this paper, a robust setpoint tracking disturbance rejection and aggressiveness (RTD-A) controller is designed and developed to control the liquid level of a conical tank process. Meta-heuristic algorithms like grey wolf optimization and the genetic algorithm are used to tune the parameters of the RTD-A controller. Its performance is later compared with that of the conventional standard proportional integral derivative controller. The gain scheduled RTD-A controller is designed and implemented on a nonlinear conical tank process. Also, various performances attributes such as the integral square error, integral absolute error, integral time absolute error, rise time, and settling time are calculated for the first-order process and conical tank process. The servo responses with RTD-A are also compared against the responses recorded from the conventional control schemes.
A Fuzzy Multicriteria Decision-Making (MCDM) Model for Sustainable Supplier Evaluation and Selection Based on Triple Bottom Line Approaches in the Garment Industry
Chia-Nan Wang, Ching-Yu Yang, Hung-Chun Cheng
September 5, 2019 (v1)
Keywords: FAHP, fuzzy logics, garment industry, Optimization, supplier selection, TOPSIS, triple bottom line
Vietnam’s garment industry is facing many challenges, including domestic competition and the global market. The free trade agreement, which Vietnam signed, includes environmental barriers, sustainable development, and green development. The agreement further requires businesses to make efforts to improve not only product quality but also the production process. In cases when enterprises cause environmental pollution in the production process and do not apply solutions to reduce waste, save energy, and natural resources, there is a risk of no longer receiving orders or orders being rejected, especially orders from the world’s major branded garment companies. In this research, the authors propose a multicriteria decision-making model (MCDM) for optimizing the supplier evaluation and selection process for the garment industry using sustainability considerations. In the first stage of this research, all criteria affecting supplier selection are determined by a triple bottom line (TBL) mode... [more]
Optimization of Post Combustion CO2 Capture from a Combined-Cycle Gas Turbine Power Plant via Taguchi Design of Experiment
Ben Alexanda Petrovic, Salman Masoudi Soltani
August 8, 2019 (v1)
Keywords: Aspen Plus, Carbon Dioxide Capture, CCGT, Minitab, Optimization, Taguchi
The potential of carbon capture and storage to provide a low carbon fossil-fueled power generation sector that complements the continuously growing renewable sector is becoming ever more apparent. An optimization of a post combustion capture unit employing the solvent monoethanolamine (MEA) was carried out using a Taguchi design of experiment to mitigate the parasitic energy demands of the system. An equilibrium-based approach was employed in Aspen Plus to simulate 90% capture of the CO2 emitted from a 600 MW natural gas combined-cycle gas turbine power plant. The effects of varying the inlet flue gas temperature, absorber column operating pressure, amount of exhaust gas recycle, and amine concentration were evaluated using signal to noise ratios and analysis of variance. The optimum levels that minimized the specific energy requirements were a: flue gas temperature = 50 °C; absorber pressure = 1 bar; exhaust gas recirculation = 20% and; amine concentration = 35 wt%, with a relative im... [more]
Global Evolution Commended by Localized Search for Unconstrained Single Objective Optimization
Rashida Adeeb Khanum, Muhammad Asif Jan, Nasser Tairan, Wali Khan Mashwani, Muhammad Sulaiman, Hidayat Ullah Khan, Habib Shah
August 8, 2019 (v1)
Subject: Optimization
Keywords: adaptive differential evolution, evolutionary computation, external archives, global search, hybridization, local search, metaheuristics, Optimization, population minimization
Differential Evolution (DE) is one of the prevailing search techniques in the present era to solve global optimization problems. However, it shows weakness in performing a localized search, since it is based on mutation strategies that take large steps while searching a local area. Thus, DE is not a good option for solving local optimization problems. On the other hand, there are traditional local search (LS) methods, such as Steepest Decent and Davidon−Fletcher−Powell (DFP) that are good at local searching, but poor in searching global regions. Hence, motivated by the short comings of existing search techniques, we propose a hybrid algorithm of a DE version, reflected adaptive differential evolution with two external archives (RJADE/TA) with DFP to benefit from both search techniques and to alleviate their search disadvantages. In the novel hybrid design, the initial population is explored by global optimizer, RJADE/TA, and then a few comparatively best solutions are shifted to the ar... [more]
A Model for Optimizing Location Selection for Biomass Energy Power Plants
Chia-Nan Wang, Tsang-Ta Tsai, Ying-Fang Huang
August 8, 2019 (v1)
Keywords: biomass energy, FAHP, FMCDM, MCDM, Optimization, site selection, TOPSIS
In addition to its potential for wave power, wind power, hydropower, and solar power, it can be said that Vietnam is a country with great potential for biomass energy derived from agricultural waste, garbage, and urban wastewater, which are resources widely available across the country. This huge amount of biomass, however, if left untreated, could become a major source of pollution and cause serious impacts on ecosystems (soil, water, and air), as well as on human health. In this research, the authors present a fuzzy multicriteria decision-making model (FMCDM) for optimizing the site selection process for biomass power plants. All of the criteria affecting location selection are identified by experts and literature reviews; in addition, the fuzzy analytic hierarchy process (FAHP) method was utilized so as to identify the weight of all of the criteria in the second stage. Furthermore, the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) is applied for ranking... [more]
Advances in Energy Systems Engineering and Process Systems Engineering in China—A Review Starting from Sargent’s Pioneering Work
Wenhan Qian, Pei Liu, Zheng Li
August 8, 2019 (v1)
Keywords: energy systems engineering, nonlinear programming, Optimization, process design, process systems engineering
Process systems engineering (PSE), after being proposed by Sargent and contemporary researchers, has been fast developing in various domains and research communities around the world in the last couple of decades, with energy systems engineering featuring a typical yet still fast propagating domain, and the Chinese PSE community featuring a typical community with its own unique challenges for applying PSE theory and methods. In this paper, development of energy systems engineering and process systems engineering in China is discussed, and Sargent’s impacts on these two fields are the main focus. Pioneering work conducted by Sargent is firstly discussed. Then, a venation on how his work and thoughts have motivated later researchers and led to progressive advances is reviewed and analyzed. It shows that Sargent’s idea of optimum design and his work on nonlinear programming and superstructure modelling have resulted in well-known methods that are widely adopted in energy systems engineeri... [more]
Sustainable Biotransformation of Oleic Acid to 10-Hydroxystearic Acid by a Recombinant Oleate Hydratase from Lactococcus garvieae
Jing Zhang, Muhammad Bilal, Shuai Liu, Jiaheng Zhang, Hedong Lu, Hongzhen Luo, Chuping Luo, Hao Shi, Hafiz M. N. Iqbal, Yuping Zhao
August 5, 2019 (v1)
Subject: Biosystems
Keywords: 10-hydroxystearic acid, bio-based process, biotransformation, Lactococcus garvieae, oleate acid, oleate hydratase, Optimization
Enzymatic hydration of oleic acid into 10-hydroxystearic acid (10-HSA) represents a theme of substantial scientific and practical interest. In this study, a fatty acid hydratase (OHase) from Lactococcus garvieae was cloned and expressed in Escherichia coli. The recombinantly expressed enzyme was identified as oleate hydratase (EC 4.2.1.53) confirming its highest hydration activity for oleic acid. The optimally yielded enzyme fraction was purified and subjected to sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE). A solitary band on SDS-PAGE confirmed the molecular weight of 65 kDa. Gas chromatography-mass spectrometry (GC-MS) analysis scrutinized the silylated hydroxy fatty acid products acquired from the hydration of oleic acid by the oleate hydratase from L. garvieae. Optimal reaction conditions for the enzymatic production of 10-HSA from oleic acid using the purified oleate hydratase were pH 7.5, 30 °C, 105.49 U/mL enzyme solution and 30 g/L oleic acid. In the pre... [more]
Optimization of Distillation Sequences with Nonsharp Separation Columns
Xi Wang, Zengzhi Du, Yunlu Zhang, Jingde Wang, Jianhong Wang, Wei Sun
August 5, 2019 (v1)
Keywords: Aspen, nonsharp distillation sequence, Optimization
Nonsharp distillation sequences are widely used in industrial separation processes; however, most current research has not discussed this topic, except in sequences with heat integration under special operating conditions, including complex columns. The sequence with nonsharp separation has the features of general distillation sequences, which are usually optimized by adjusting the separation sequence and the design/operation parameters of each column in the sequence, making the optimization a mixed integer nonlinear programming (MINLP) problem, which is usually hard to solve. With inclusion of nonsharp separation columns, the sequence optimization becomes even more complicated and computationally intensive. This work aimed to optimize the distillation sequence, including nonsharp distillation alongside simple columns and dividing wall columns. Inspired by the dynamic programing method for sharp distillation sequence, a framework for automatic optimization is proposed to decompose the... [more]
Heat Flux Estimation at Pool Boiling Processes with Computational Intelligence Methods
Erdem Alic, Mehmet Das, Onder Kaska
July 31, 2019 (v1)
Keywords: boiling, computational intelligence techniques, heat flux, Optimization
It is difficult to manually process and analyze large amounts of data. Therefore, to solve a given problem, it is easier to reach the solution by studying the data obtained from the environment of the problem with computational intelligence methods. In this study, pool boiling heat flux was estimated in the isolated bubble regime using two optimization methods (genetic and artificial bee colony algorithm) and three machine learning algorithms (decision tree, artificial neural network, and support vector machine). Six boiling mechanisms containing eighteen different parameters in the genetic and the artificial bee colony (ABC) algorithms were used to calculate overall heat flux of the isolated bubble regime. Support vector machine regression (SVMReg), alternating model tree (ADTree), and multilayer perceptron (MLP) regression only used the heat transfer equation input parameters without heat transfer equations for prediction of pool boiling heat transfer over a horizontal tube. The perf... [more]
Synthesis and Characterization of Natural Extracted Precursor Date Palm Fibre-Based Activated Carbon for Aluminum Removal by RSM Optimization
Alfarooq O. Basheer, Marlia M. Hanafiah, Mohammed Abdulhakim Alsaadi, Y. Al-Douri, M.A. Malek, Mustafa Mohammed Aljumaily, Seef Saadi Fiyadh
July 28, 2019 (v1)
Subject: Biosystems
Keywords: aluminum removal, Biomass, date palm fibre, Optimization, powder-activated carbon, wastewater treatment
The Powder-Activated Carbon (PAC) under optimum conditions from a new low-cost precursor Date Palm Fibre (DPF) biomass through a carbonization followed by KOH activation has been synthesized by response surface methodology (RSM) combined with central composite design (CCD). The special effects of activation temperature, time, and impregnation ratio on bio-PAC Aluminum (Al3+) removal and uptake capacity were examined. The optimum conditions for synthesized bio-PAC were found to be 99.4% and 9.94 mg·g−1 for Al3+ removal and uptake capacity, respectively at activation temperature 650 °C, activation time 1h and impregnation ratio 1. The optimum bio-PAC was characterized and analyzed using FESEM, FTIR, XRD, TGA, BET, and Zeta potential. RSM-CCD experimental design was used to optimize removal and uptake capacity of Al3+ on bio-PAC. Optimum conditions were found to be at bio-PAC dose of 5 mg with pH 9.48 and contact time of 117 min. Furthermore, at optimized conditions of Al3+ removal, kinet... [more]
Numerical Investigation of the Time-Dependent and the Proppant Dominated Stress Shadow Effects in a Transverse Multiple Fracture System and Optimization
Lei Zhou, Junchao Chen, Yang Gou, Wentao Feng
July 26, 2019 (v1)
Keywords: 3D numerical modeling, hydro-mechanical coupling, Optimization, time-dependent and proppant dominated stress shadow effect, transverse multiple fracture
In this paper, a numerical study is conducted to investigate the stress shadow effects (stress reorientation and change) during hydraulic fracturing in a transverse multiple fracture system. A numerical model is used for the numerical study. It is a 3D model and can simulate the fracture operation from injection begin to full closure (fracture contact). Therefore, there is no need to assume the fracture geometry for the investigation of the stress shadow effects (unlike previous studies). In the numerical study, the first and second operations in a fictive transverse multiple fracture system are simulated, meanwhile the stress shadow effects and their influences on the propagation and proppant placement of the second fracture are investigated. According to the results, the following conclusions are discerned: (1) most proppants are located in the lower part of the reservoir, even below the perforation; (2) the stress shadow effects are time-dependent and proppant dominated; (3) the str... [more]
Multi-Objective Optimization of Thin-Film Silicon Solar Cells with Metallic and Dielectric Nanoparticles
Giovanni Aiello, Salvatore Alfonzetti, Santi Agatino Rizzo, Nunzio Salerno
July 26, 2019 (v1)
Subject: Materials
Keywords: evolutionary algorithms, finite element method, nanoplamonics, Optimization, Renewable and Sustainable Energy, solar cell
Thin-film solar cells enable a strong reduction of the amount of silicon needed to produce photovoltaic panels but their efficiency lowers. Placing metallic or dielectric nanoparticles over the silicon substrate increases the light trapping into the panel thanks to the plasmonic scattering from nanoparticles at the surface of the cell. The goal of this paper is to optimize the geometry of a thin-film solar cell with silver and silica nanoparticles in order to improve its efficiency, taking into account the amount of silver. An efficient evolutionary algorithm is applied to perform the optimization with a reduced computing time.
Distilling Robust Design Principles of Biocircuits Using Mixed Integer Dynamic Optimization
Irene Otero-Muras, Julio R. Banga
June 10, 2019 (v1)
Subject: Optimization
Keywords: bio-design automation, biocircuits, computer-aided design, Optimization, robust design, synthetic biology
A major challenge in model-based design of synthetic biochemical circuits is how to address uncertainty in the parameters. A circuit whose behavior is robust to variations in the parameters will have more chances to behave as predicted when implemented in practice, and also to function reliably in presence of fluctuations and noise. Here, we extend our recent work on automated-design based on mixed-integer multi-criteria dynamic optimization to take into account parametric uncertainty. We exploit the intensive sampling of the design space performed by a global optimization algorithm to obtain the robustness of the topologies without significant additional computational effort. Our procedure provides automatically topologies that best trade-off performance and robustness against parameter fluctuations. We illustrate our approach considering the automated design of gene circuits achieving adaptation.
Using the Optimization Algorithm to Evaluate the Energetic Industry: A Case Study in Thailand
Chia-Nan Wang, Tien-Muoi Le, Han-Khanh Nguyen, Hong Ngoc-Nguyen
June 10, 2019 (v1)
Subject: Optimization
Keywords: evaluation, Optimization, performance, Thai energy
Thailand’s economy is developing rapidly, with energy being a significant factor in this development. This study uses a variety of models to assess the performance of Thailand’s energy industry in two different phases, the first being from 2013 to 2017 and the second from 2018 to 2020. The Malmquist model-one of data envelopment required input and output data that showed Thailand’s productivity index and the rate-of-change ratio, which is used to assess technical changes, change efficiency, and productivity changes of the 12 listed companies in energetic generation and distribution in Thailand. To calculate future indicators, the forecast data are generated by applying the Grey model (1,1) GM(1,1). Accuracy prediction is determined by the mean absolute percentage error (MAPE). The results show that the magnitude of the change in efficiency during the first period is stable, and some major changes in the technical level of some companies may be observed. In the future, the performance o... [more]
Model-Based Stochastic Fault Detection and Diagnosis of Lithium-Ion Batteries
Jeongeun Son, Yuncheng Du
April 15, 2019 (v1)
Keywords: fault detection and classification, lithium-ion battery, Optimization, polynomial chaos expansion, thermal management, uncertainty analysis
The Lithium-ion battery (Li-ion) has become the dominant energy storage solution in many applications, such as hybrid electric and electric vehicles, due to its higher energy density and longer life cycle. For these applications, the battery should perform reliably and pose no safety threats. However, the performance of Li-ion batteries can be affected by abnormal thermal behaviors, defined as faults. It is essential to develop a reliable thermal management system to accurately predict and monitor thermal behavior of a Li-ion battery. Using the first-principle models of batteries, this work presents a stochastic fault detection and diagnosis (FDD) algorithm to identify two particular faults in Li-ion battery cells, using easily measured quantities such as temperatures. In addition, models used for FDD are typically derived from the underlying physical phenomena. To make a model tractable and useful, it is common to make simplifications during the development of the model, which may con... [more]
Ultrasonic-Assisted Extraction and Swarm Intelligence for Calculating Optimum Values of Obtaining Boric Acid from Tincal Mineral
Bahdisen Gezer, Utku Kose
April 15, 2019 (v1)
Keywords: Artificial Intelligence, boric acid, central composite design, Optimization, swarm intelligence, tincal, ultrasound assisted extraction
The objective of this study is to focus on boric acid extraction from the mineral tincal, in order to determine the optimum conditions thanks to the ultrasonic-assisted extraction (UAE) technique (with the response surface methodology (RSM) for the first time), and artificial intelligence based swarm intelligence. Characterization of the tincal were done by using thermo-gravimetric assay (TG-DTA), X-ray diffraction (XRD), and Fourier transform infrared spectroscopy (FTIR) analyses. In detail, a central composite design (CCD) was used for determining the effects of different solvent/solid ratios, pH, extraction time, and extraction temperature on the yield, which was determined by the conductometric method. The optimum values regarding the best extraction process was calculated by using five different swarm intelligence techniques: Particle swarm optimization (PSO), cuckoo search (CS), genetic algorithms (GA), Differential evolution (DE), and the vortex optimization algorithm (VOA). In... [more]
Optimization of Reaction Selectivity Using CFD-Based Compartmental Modeling and Surrogate-Based Optimization
Shu Yang, San Kiang, Parham Farzan, Marianthi Ierapetritou
April 9, 2019 (v1)
Keywords: CFD-simulation, compartmental modeling, competing reaction system, Mixing, model order reduction, Optimization, surrogate-based optimization
Mixing is considered as a critical process parameter (CPP) during process development due to its significant influence on reaction selectivity and process safety. Nevertheless, mixing issues are difficult to identify and solve owing to their complexity and dependence on knowledge of kinetics and hydrodynamics. In this paper, we proposed an optimization methodology using Computational Fluid Dynamics (CFD) based compartmental modelling to improve mixing and reaction selectivity. More importantly, we have demonstrated that through the implementation of surrogate-based optimization, the proposed methodology can be used as a computationally non-intensive way for rapid process development of reaction unit operations. For illustration purpose, reaction selectivity of a process with Bourne competitive reaction network is discussed. Results demonstrate that we can improve reaction selectivity by dynamically controlling rates and locations of feeding in the reactor. The proposed methodology inco... [more]
FFANN Optimization by ABC for Controlling a 2nd Order SISO System’s Output with a Desired Settling Time
Aydın Mühürcü
April 9, 2019 (v1)
Keywords: ABC, buck converter, control, FFANN, Modelling, Optimization, settling time
In this study, a control strategy is aimed to ensure the settling time of a 2nd order system’s output value while its input reference value is changed. Here, Feed Forward Artificial Neural Network (FFANN) nonlinear structure has been chosen as a control algorithm. In order to implement the intended control strategy, FFANN’s normalization coefficient (K), learning coefficients (ŋ), momentum coefficients (μ) and the sampling time (Ts) were optimized by Artificial Bee Colony (ABC) but FFANN’s values of weights were chosen arbitrary on start time of control system. After optimization phase, the FFANN behaves as an adaptive optimal discrete time non-linear controller that forces the system output to take the same value with the input reference for a desired settling time (ts). The success of the optimization algorithm was proved with close loop feedback control simulations on Matlab’s Simulink platform based on 2nd order transfer functions. Also, the success was proved with a 2nd order phys... [more]
Optimization of Reducing Sugar Production from Manihot glaziovii Starch Using Response Surface Methodology
Abdi Hanra Sebayang, Masjuki Haji Hassan, Hwai Chyuan Ong, Surya Dharma, Arridina Susan Silitonga, Fitranto Kusumo, Teuku Meurah Indra Mahlia, Aditiya Harjon Bahar
March 26, 2019 (v1)
Subject: Biosystems
Keywords: alternative fuel, bioethanol, Fermentation, hydrolysis, Manihot glaziovii (M. glaziovii), Optimization
Bioethanol is known as a viable alternative fuel to solve both energy and environmental crises. This study used response surface methodology based on the Box-Behnken experimental design to obtain the optimum conditions for and quality of bioethanol production. Enzymatic hydrolysis optimization was performed with selected hydrolysis parameters, including substrate loading, stroke speed, α-amylase concentration and amyloglucosidase concentration. From the experiment, the resulting optimum conditions are 23.88% (w/v) substrate loading, 109.43 U/g α-amylase concentration, 65.44 U/mL amyloglucosidase concentration and 74.87 rpm stroke speed, which yielded 196.23 g/L reducing sugar. The fermentation process was also carried out, with a production value of 0.45 g ethanol/g reducing sugar, which is equivalent to 88.61% of ethanol yield after fermentation by using Saccharomyces cerevisiae (S. cerevisiae). The physical and chemical properties of the produced ethanol are within the specifications... [more]
Real-Time Velocity Optimization to Minimize Energy Use in Passenger Vehicles
Thomas Levermore, M. Necip Sahinkaya, Yahya Zweiri, Ben Neaves
March 26, 2019 (v1)
Keywords: dynamic programming, fuel, fuel consumption, Optimization
Energy use in internal combustion engine passenger vehicles contributes directly to CO 2 emissions and fuel consumption, as well as producing a number of air pollutants. Optimizing the vehicle velocity by utilising upcoming road information is an opportunity to minimize vehicle energy use without requiring mechanical design changes. Dynamic programming is capable of such an optimization task and is shown in simulation to produce fuel savings, on average 12%, compared to real driving data; however, in this paper it is also applied in real time on a Raspberry Pi, a low cost miniature computer, in situ in a vehicle. A test drive was undertaken with driver feedback being provided by a dynamic programming algorithm, and the results are compared to a simulated intelligent cruise control system that can follow the algorithm results precisely. An 8% reduction in fuel with no loss in time is reported compared to the test driver.
Artificial Neural Network Model for Alkali-Surfactant-Polymer Flooding in Viscous Oil Reservoirs: Generation and Application
Si Le Van, Bo Hyun Chon
February 27, 2019 (v1)
Keywords: artificial neural network, chemical flooding, enhanced oil recovery, net present value, Optimization
Chemical flooding has been widely utilized to recover a large portion of the oil remaining in light and viscous oil reservoirs after the primary and secondary production processes. As core-flood tests and reservoir simulations take time to accurately estimate the recovery performances as well as analyzing the feasibility of an injection project, it is necessary to find a powerful tool to quickly predict the results with a level of acceptable accuracy. An approach involving the use of an artificial neural network to generate a representative model for estimating the alkali-surfactant-polymer flooding performance and evaluating the economic feasibility of viscous oil reservoirs from simulation is proposed in this study. A typical chemical flooding project was referenced for this numerical study. A number of simulations have been made for training on the basis of a base case from the design of 13 parameters. After training, the network scheme generated from a ratio data set of 50%-20%-30%... [more]
Green Small Cell Operation of Ultra-Dense Networks Using Device Assistance
Gilsoo Lee, Hongseok Kim
February 27, 2019 (v1)
Keywords: belief propagation, cellular networks, Energy Efficiency, Optimization, small cell
As higher performance is demanded in 5G networks, energy consumption in wireless networks increases along with the advances of various technologies, so enhancing energy efficiency also becomes an important goal to implement 5G wireless networks. In this paper, we study the energy efficiency maximization problem focused on finding a suitable set of turned-on small cell access points (APs). Finding the suitable on/off states of APs is challenging since the APs can be deployed by users while centralized network planning is not always possible. Therefore, when APs in small cells are randomly deployed and thus redundant in many cases, a mechanism of dynamic AP turning-on/off is required. We propose a device-assisted framework that exploits feedback messages from the user equipment (UE). To solve the problem, we apply an optimization method using belief propagation (BP) on a factor graph. Then, we propose a family of online algorithms inspired by BP, called DANCE, that requires low computati... [more]
On the Reliability of Optimization Results for Trigeneration Systems in Buildings, in the Presence of Price Uncertainties and Erroneous Load Estimation
Antonio Piacentino, Roberto Gallea, Pietro Catrini, Fabio Cardona, Domenico Panno
February 27, 2019 (v1)
Keywords: buildings, cogeneration, energy loads, linear programming, Optimization, prices, sensitivity, stochastic, trigeneration, uncertainty
Cogeneration and trigeneration plants are widely recognized as promising technologies for increasing energy efficiency in buildings. However, their overall potential is scarcely exploited, due to the difficulties in achieving economic viability and the risk of investment related to uncertainties in future energy loads and prices. Several stochastic optimization models have been proposed in the literature to account for uncertainties, but these instruments share in a common reliance on user-defined probability functions for each stochastic parameter. Being such functions hard to predict, in this paper an analysis of the influence of erroneous estimation of the uncertain energy loads and prices on the optimal plant design and operation is proposed. With reference to a hotel building, a number of realistic scenarios is developed, exploring all the most frequent errors occurring in the estimation of energy loads and prices. Then, profit-oriented optimizations are performed for the examined... [more]
Local Alternative for Energy Supply: Performance Assessment of Integrated Community Energy Systems
Binod Prasad Koirala, José Pablo Chaves Ávila, Tomás Gómez, Rudi A. Hakvoort, Paulien M. Herder
February 27, 2019 (v1)
Keywords: distributed energy resources (DERs), energy communities, multi-carrier energy systems, Optimization, smart grids
Integrated community energy systems (ICESs) are emerging as a modern development to re-organize local energy systems allowing simultaneous integration of distributed energy resources (DERs) and engagement of local communities. Although local energy initiatives, such as ICESs are rapidly emerging due to community objectives, such as cost and emission reductions as well as resiliency, assessment and evaluation are still lacking on the value that these systems can provide both to the local communities as well as to the whole energy system. In this paper, we present a model-based framework to assess the value of ICESs for the local communities. The distributed energy resources-consumer adoption model (DER-CAM) based ICES model is used to assess the value of an ICES in the Netherlands. For the considered community size and local conditions, grid-connected ICESs are already beneficial to the alternative of solely being supplied from the grid both in terms of total energy costs and CO₂ emissi... [more]
Experimental Optimization of Passive Cooling of a Heat Source Array Flush-Mounted on a Vertical Plate
Antoine Baudoin, Didier Saury, Bo Zhu, Cecilia Boström
February 5, 2019 (v1)
Subject: Other
Keywords: discrete heat sources, natural convection, Optimization, source array
Heat sources, such as power electronics for offshore power, could be cooled passively—mainly by conduction and natural convection. The obvious advantage of this strategy is its high reliability. However, it must be implemented in an efficient manner (i.e., the area needs to be kept low to limit the construction costs). In this study, the placement of multiple heat sources mounted on a vertical plate was studied experimentally for optimization purposes. We chose a regular distribution, as this is likely to be the preferred choice in the construction process. We found that optimal spacing can be determined for a targeted source density by tuning the vertical and horizontal spacing between the heat sources. The optimal aspect ratio was estimated to be around two.
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