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Records with Subject: Optimization
Showing records 952 to 976 of 1630. [First] Page: 1 36 37 38 39 40 41 42 43 44 Last
Spotted Hyena Optimization Method for Harvesting Maximum PV Power under Uniform and Partial-Shade Conditions
Ezhilmaran Ranganathan, Rajasekar Natarajan
March 1, 2023 (v1)
Subject: Optimization
Keywords: maximum power point tracking (MPPT), Optimization, partial shading, perturb-and-observe algorithm (P&O), photovoltaic (PV) array, solar energy
Maximum power-point-tracking techniques applied for partially shaded photovoltaic array yield maximum power output via operating the panel at its most efficient voltage. Considering the noticeable issues existing with the available methods, including steady-state oscillations, poor tracking capability and complex procedures, a new bioinspired Spotted-Hyena Optimizer (SHO) is proposed. It follows simple implementation steps, and does not require additional controller-parameter tuning to track the optimal power point. To validate the versatility of the proposed method, the SHO algorithm is applied to track the maximum power of different string arrangements under six partial-shade conditions. Further, to authenticate SHO’s methods, its results are compared with perturb-and-observe (P&O), and particle-swarm-optimization (PSO) methods. As a result of its implementation, it is observed that the tracking speed of SHO towards the global convergence for four patterns under 4S2P are 0.34 s, 0.24... [more]
Multi-Objective RANS Aerodynamic Optimization of a Hypersonic Intake Ramp at Mach 5
Francesco De Vanna, Danilo Bof, Ernesto Benini
March 1, 2023 (v1)
Subject: Optimization
Keywords: Genetic Algorithm, hypersonic flows, multi-objective opmization
The work describes a systematic optimization strategy for designing hypersonic inlet intakes. A Reynolds-averaged Navier-Stokes database is mined using genetic algorithms to develop ideal designs for a priori defined targets. An intake geometry from the literature is adopted as a baseline. Thus, a steady-state numerical assessment is validated and the computational grid is tuned under nominal operating conditions. Following validation tasks, the model is used for multi-objective optimization. The latter aims at minimizing the drag coefficient while boosting the static and total pressure ratios, respectively. The Pareto optimal solutions are analyzed, emphasizing the flow patterns that result in the improvements. Although the approach is applied to a specific setup, the method is entirely general, offering a valuable flowchart for designing super/hypersonic inlets. Notably, because high-quality computational fluid dynamics strategies drive the innovation process, the latter accounts for... [more]
Possibilities for Deep Renovation in Multi-Apartment Buildings in Different Economic Conditions in Europe
Davor Končalović, Jelena Nikolic, Vladimir Vukasinovic, Dušan Gordić, Dubravka Živković
March 1, 2023 (v1)
Subject: Optimization
Keywords: deep renovation, mathematical optimization, multi-apartment buildings, passive house
This paper analyzes the potential for deep renovation of an apartment building to the level of a passive house in different contexts in the continental part of Europe. The examined variables include different local climatic conditions, levels of economic development, and levels of market development (energy prices, energy footprint, labor prices, etc.) as well as different energy efficiency retrofit scenarios in four different countries. The adequate methodology was developed here in order to obtain an optimal solution for deep renovation in each context. The proposed methodology was based on the interaction of energy simulation and mathematical optimization. In this model, the energy performances of a building are determined with the EnergyPlus package and the optimal solution was obtained by using a mixed-integer non-linear programming model. The results demonstrate that the optimal solution for each analyzed location cannot provide cost-effectiveness over the lifetime of a building,... [more]
Optimization of Solar/Fuel Cell Hybrid Energy System Using the Combinatorial Dynamic Encoding Algorithm for Searches (cDEAS)
Jong-Wook Kim, Heungju Ahn, Hyeon Cheol Seo, Sang Cheol Lee
March 1, 2023 (v1)
Subject: Optimization
Keywords: combinatorial dynamic encoding algorithm for searches, hybrid energy system, Optimization, power
This study proposes a computational design method for determining a hybrid power system’s sizing and ratio values that combines the national electric, solar cell, and fuel cell power sources. The inequality constraints associated with the ranges of power storage exchange and the stored energy are reflected as penalty functions in the overall cost function to be minimized. Using the energy hub model and the actual data for the solar cell power and the load of the residential sector in one Korean city for one hundred days, we optimize the ratio of fuel cell energy and solar cell energy to 0.46:0.54 through our proposed approach. We achieve an average cost-reduction effect of 19.35% compared to the cases in which the fuel-cell energy ratio is set from 0.1 to 0.9 in 0.1 steps. To optimize the sizing and the ratio of fuel-cell energy in the hybrid power system, we propose the modified version of the univariate dynamic encoding algorithm for searches (uDEAS) as a novel optimization method. T... [more]
Short-Term Combined Forecasting Method of Park Load Based on CEEMD-MLR-LSSVR-SBO
Bo Hu, Jian Xu, Zuoxia Xing, Pengfei Zhang, Jia Cui, Jinglu Liu
March 1, 2023 (v1)
Subject: Optimization
Keywords: combination model, complementary ensemble empirical mode decomposition (CEEMD), least squares support vector regression (LSSVR), multiple linear regression, satin bower bird optimization algorithm (SBO), short-term park load forecasting
To improve the accuracy of park load forecasting, a combined forecasting method for short-term park load is proposed based on complementary ensemble empirical mode decomposition (CEEMD), sample entropy, the satin bower bird optimization algorithm (SBO), and the least squares support vector regression (LSSVR) model. Firstly, aiming at the random fluctuation of park load series, the modes with different characteristic scales are divided into low-frequency and high-frequency according to the calculation of sample entropy, which is based on the decomposition of historical park load data modes by CEEMD. The low-frequency is forecast by multiple linear regression (MLR), and the high-frequency component is the training input of the LSSVR forecasting model. Secondly, the SBO algorithm is adopted to optimize the regularization parameters and the kernel function width of LSSVR. Then, the park load forecasting model of each sequence component is built. The forecast output of each sequence compone... [more]
Energy Optimization in a Paper Mill Enabled by a Three-Site Energy Cooperation
Alexander Hedlund, Olof Björkqvist, Anders Nilsson, Per Engstrand
March 1, 2023 (v1)
Subject: Optimization
Keywords: collaboration between actors, cooperation, district heating, energy optimization, energy reduction, industrial symbiosis
Although there are opportunities to reduce electrical energy demand in unit processes of mechanical pulp-based paper and paperboard production, this may not be financially beneficial. This is generally because energy optimization opportunities connected to reduced refiner electricity demand in mechanical pulping systems also results in less steam available for the drying of the paper. As modern high consistency refiner systems produce approximately one ton of steam for each MWh of electricity when producing one ton of pulp, a reduction in electric energy demand leads to increased fuel demand in steam boilers to compensate for the steam shortage. In this study, we investigated what the financial and environmental situation would look like if we were to expand the system border from a paper mill to a larger system consisting of a mechanical pulp-based paper or paperboard mill, a district heating system with an incineration boiler and a chemical pulp mill. Mechanical pulp production has a... [more]
Nested Decomposition Approach for Dispatch Optimization of Large-Scale, Integrated Electricity, Methane and Hydrogen Infrastructures
Lukas Löhr, Raphael Houben, Carolin Guntermann, Albert Moser
March 1, 2023 (v1)
Subject: Optimization
Keywords: decomposition, dispatch optimization, hydrogen infrastructure, large-scale optimization, multi-energy systems, optimal power and gas flow
Energy system integration enables raising operational synergies by coupling the energy infrastructures for electricity, methane, and hydrogen. However, this coupling reinforces the infrastructure interdependencies, increasing the need for integrated modeling of these infrastructures. To analyze the cost-efficient, sustainable, and secure dispatch of applied, large-scale energy infrastructures, an extensive and non-linear optimization problem needs to be solved. This paper introduces a nested decomposition approach with three stages. The method enables an integrated and full-year consideration of large-scale multi-energy systems in hourly resolution, taking into account physical laws of power flows in electricity and gas transmission systems as boundary conditions. For this purpose, a zooming technique successively reduces the temporal scope while first increasing the spatial and last the technical resolution. A use case proves the applicability of the presented approach to large-scale... [more]
Comparative Study of Non-Rare-Earth and Rare-Earth PM Motors for EV Applications
Yawei Wang, Nicola Bianchi, Ronghai Qu
March 1, 2023 (v1)
Subject: Optimization
Keywords: differential evolution, electromagnetic performance, flux-weakening, non-rare-earth, split ratio, synchronous reluctance machine
Recently, non-rare-earth motors are attracting more and more attention due to the booming of the electric vehicle (EV) market and, more importantly, the increasing price of the rare-earth magnet material. This paper focuses on the performance comparison among a commercial interior permanent magnet (IPM) motor and two non-rare-earth motors, including a synchronous reluctance motor (SynRM) and a permanent-magnet-assisted synchronous reluctance motor (PMaSynRM). The design procedure to develop a high-torque-density, low-torque-ripple and high-efficiency SynRM is presented. Combined with a developed automatic modeling and simulation procedure, the finite element analysis (FEA)-based differential evolution (DE) algorithm is introduced for the SynRM rotor optimization. In order to fully inspire the potential of the SynRM, a novel method to optimize the motor split ratio is proposed under the constraint of the copper loss. In addition, different slot−pole combinations are investigated to maxi... [more]
Three-Phase Unbalance Improvement for Distribution Systems Based on the Particle Swarm Current Injection Algorithm
Chien-Kuo Chang, Shih-Tang Cheng, Bharath-Kumar Boyanapalli
March 1, 2023 (v1)
Subject: Optimization
Keywords: current injection, distribution systems, Particle Swarm Optimization, power quality, three-phase unbalance
The aim of this study is to improve the three-phase unbalanced voltage at the secondary side of a distribution transformer. The proposed method involves compensation sources injecting three different single-phase currents into the connected point of a grid. The computations of optimal single-phase currents are performed using the circuit analysis method and particle swarm optimization algorithm. An unbalanced three-phase power distribution system model is constructed, including a transformer Δ−Δ connection, V−V connection, load balance, load unbalance combination, and three single-phase compensation current sources. The results show that the voltage unbalance rate of the electricity user side is improved to less than 1%, and the three-phase total compensation apparent power is approximately 0 VA. In the future, the application of the model as an auxiliary service could be achieved by adding an energy storage system.
Piezoelectric Energy Harvesting from Roadways under Open-Traffic Conditions: Analysis and Optimization with Scaling Law Method
Yangyang Zhang, Qi Lai, Ji Wang, Chaofeng Lü
March 1, 2023 (v1)
Subject: Optimization
Keywords: intelligent pavement, piezoelectric energy harvesting, scaling law method
Piezoelectric energy harvesting from roadways, which converts ambient vibration energy of roads into electric energy, has a wide range of potential applications in intelligent transportation systems. On-site open-traffic tests revealed that energy harvested by piezoelectric energy harvester (PEH) units embedded in roadways is far less than the value in laboratories, which may be because the parameters of traffic flow load (frequency, distribution, wave shape, etc.) and the road structure are significantly different from the pre-established conditions in laboratories or even on-site tests with only one vehicle passing. To address this issue, an analytical model for piezoelectric energy harvesting from roadways under open-traffic conditions was proposed to examine the mechanical response of the road structure and the electrical performance of the stack PEH units embedded in the road. The influence of all parameters in the energy-harvesting system was then obtained with the scaling law me... [more]
Effect of Gaskets Geometry on the Performance of a Reverse Electrodialysis Cell
Elier Sandoval-Sánchez, Ziomara De la Cruz-Barragán, Margarita Miranda-Hernández, Edgar Mendoza
March 1, 2023 (v1)
Subject: Optimization
Keywords: cell optimization, power density, reverse electrodialysis, salinity gradient power, spacer geometry
Salinity gradient energy (SGE) allows the difference in salt concentration in two volumes of water to be harnessed and transformed into clean energy. The most advanced SGE technology is reverse electrodialysis (RED) cells. Recent studies have focused on ways to optimize the flow distribution in the compartments containing the water, for which it is necessary to consider the characteristics of the solutions, the cell dimensions, the operating conditions, as well as their influence on the hydrodynamics and mass transport in the system. In this study, two spacers with different gasket geometry were designed, fabricated, and compared experimentally through voltage and current measurements. The power output was computed, obtaining a maximum power density of 0.14 W/m2. Results show that the geometry of the cell components directly influences the physicochemical principles governing the RED process and is closely related to the cell output parameters. In turn, it is possible to increase the p... [more]
Medium- and Long-Term Trading Strategies for Large Electricity Retailers in China’s Electricity Market
Ting Lu, Weige Zhang, Yunjia Wang, Hua Xie, Xiaowei Ding
March 1, 2023 (v1)
Subject: Optimization
Keywords: decomposition strategy of contract electricity quantity, decomposition strategy of daily load curve, electricity spot market, medium- and long-term trading strategy, particle swarm
In the rapid promotion of China’s electricity spot market, a large number of electricity retailers and large consumers participate in power trading, of which medium- and long-term power trading accounts for a large proportion. In the electricity spot market, the previous medium- and long-term transactions need to be closely combined with the current spot market transaction settlement rules. This paper analyzes the trading strategy of large retailers in the power market. In order to effectively reduce the total electricity cost, it is necessary to optimize the medium- and long-term transactions based on three aspects: electricity quantity and benchmark price decisions of medium- and long-term contracts, the daily electricity decomposition method in the day-ahead (DA) market, and the daily load curve decomposition strategy. According to load history characteristics that are extracted by the X12 method, daily electricity is decomposed from the medium- and long-term electricity quantity in... [more]
A Backwards Induction Framework for Quantifying the Option Value of Smart Charging of Electric Vehicles and the Risk of Stranded Assets under Uncertainty
Spyros Giannelos, Stefan Borozan, Goran Strbac
March 1, 2023 (v1)
Subject: Optimization
Keywords: backwards induction framework, electric vehicles, option value, smart charging of EV, Stochastic Optimization
The anticipated electrification of the transport sector may lead to significant increase in the future peak electricity demand, resulting in potential violations of network constraints. As a result, a considerable amount of network reinforcement may be required in order to ensure that the expected additional demand from electric vehicles that are to be connected will be safely accommodated. In this paper we present the Backwards Induction Framework (BIF), which we use for identifying the optimal investment decisions, for calculating the option value of smart charging of EV and the cost of stranded assets; these concepts are crystallized through illustrative case studies. Sensitivity analyses depict how the option value of smart charging and the optimal solution are affected by key factors such as the social cost associated with not accommodating the full EV capacity, the flexibility of smart charging, and the scenario probabilities. Moreover, the BIF is compared with the Stochastic Opt... [more]
Energy Performance Curves Prediction of Centrifugal Pumps Based on Constrained PSO-SVR Model
Huican Luo, Peijian Zhou, Lingfeng Shu, Jiegang Mou, Haisheng Zheng, Chenglong Jiang, Yantian Wang
March 1, 2023 (v1)
Subject: Optimization
Keywords: centrifugal pump, particle swarm, performance prediction, performance relationship, support vector regression
It is of great significance to predict the energy performance of centrifugal pumps for the improvement of the pump design. However, the complex internal flow always affects the performance prediction of centrifugal pumps, particularly under low-flow operating conditions. Relying on the data-fitting method, a multi-condition performance prediction method for centrifugal pumps is proposed, where the performance relationship is incorporated into the particle swarm optimization algorithm, and the prediction model is optimized by automatically meeting the performance constraints. Compared with the experimental results, the performance under multiple operating conditions is well predicted by introducing performance constraints with the mean absolute relative error (MARE) for the head, power and efficiency of 0.85%, 1.53%,1.15%, respectively. By comparing the extreme gradient boosting and support vector regression models, the support vector regression is more suitable for the prediction of pe... [more]
Research on Operation Optimization of LNG Submerged Pump System in LNG Receiving Terminals
Baoqing Wang, Kun Chen, Cheng Huang, Jinrui Zhao, Yaotong Zhang, Dequan Li, Lin Wang
March 1, 2023 (v1)
Subject: Optimization
Keywords: energy saving, LNG receiving terminal, LNG submerged pump, operation optimization
This paper focuses on improving the operating efficiency of the Liquified Natural Gas (LNG) submerged pump system in the LNG receiving terminals and achieve energy saving. The minimum input energy consumption of the LNG submerged pump system is taken as the objective function, and an optimization model for the operation of the LNG submerged pump system with variable frequency speed is established. LINGO18.0 optimization software is used to solve the model to get the optimal LNG submerged pump operation plan that satisfies the constraints. Taking a certain LNG receiving terminal as an example, the operation optimization of its LNG submerged pump system is carried out, and the input energy consumption of the system before and after optimization is compared. The results show that the use of variable frequency pumps can reduce the energy consumption of the LNG submerged pump system of LNG receiving terminals, and the optimization model can reduce the input power consumption of the system b... [more]
Unlocking the Flexibility of District Heating Pipeline Energy Storage with Reinforcement Learning
Ksenija Stepanovic, Jichen Wu, Rob Everhardt, Mathijs de Weerdt
March 1, 2023 (v1)
Subject: Optimization
Keywords: 4th generation district heating, combined heat and power economic dispatch, Markov decision process, mixed-integer nonlinear program, pipeline energy storage, Q-learning
The integration of pipeline energy storage in the control of a district heating system can lead to profit gain, for example by adjusting the electricity production of a combined heat and power (CHP) unit to the fluctuating electricity price. The uncertainty from the environment, the computational complexity of an accurate model, and the scarcity of placed sensors in a district heating system make the operational use of pipeline energy storage challenging. A vast majority of previous works determined a control strategy by a decomposition of a mixed-integer nonlinear model and significant simplifications. To mitigate consequential stability, feasibility, and computational complexity challenges, we model CHP economic dispatch as a Markov decision process. We use a reinforcement learning (RL) algorithm to estimate the system’s dynamics through interactions with the simulation environment. The RL approach is compared with a detailed nonlinear mathematical optimizer on day-ahead and real-tim... [more]
Pressure Drop Optimization of the Main Steam and Reheat Steam System of a 1000 MW Secondary Reheat Unit
Yanfeng Li, Jingru Liu, Guohe Huang
March 1, 2023 (v1)
Subject: Optimization
Keywords: 1000 MW secondary reheat unit, main steam and reheat steam system, pressure drop optimization
The pressure drop of a main steam and reheat steam system should be optimized during the design and operation of a thermal power plant to minimize operation costs. In this study, the pressure drop of the main steam pipe and reheat steam pipe of a 1000 MW secondary reheat unit are optimized by modulating the operation parameters and the cost of operation is explored. Optimal pipe specifications were achieved by selecting a bend pipe and optimizing the pipe specifications. The pressure loss of the main steam pipeline was optimized to 2.61% compared with the conventional pressure drop (5%), the heat consumption of steam turbine was reduced by about 0.63 kJ/(kW·h), the standard coal consumption was minimized by about 0.024 g/(kW·h), and the total income in 20 years is approximated to be CNY 217,700. The primary reheat system was optimized to 4.88%, the steam turbine heat consumption was reduced by about 7.13 kJ/(kW·h), the standard coal consumption decreased by about 0.276 g/(kW·h), and th... [more]
Rational Application of Electric Power Production Optimization through Metaheuristics Algorithm
Eliton Smith dos Santos, Marcus Vinícius Alves Nunes, Manoel Henrique Reis Nascimento, Jandecy Cabral Leite
March 1, 2023 (v1)
Subject: Optimization
Keywords: economic dispatch and combined emissions, metaheuristics, Optimization, photovoltaic solar generation, thermal unit
The aim of this manuscript is to introduce solutions to optimize economic dispatch of loads and combined emissions (CEED) in thermal generators. We use metaheuristics, such as particle swarm optimization (PSO), ant lion optimization (ALO), dragonfly algorithm (DA), and differential evolution (DE), which are normally used for comparative simulations, and evaluation of CEED optimization, generated in MATLAB. For this study, we used a hybrid model composed of six (06) thermal units and thirteen (13) photovoltaic solar plants (PSP), considering emissions of contaminants into the air and the reduction in the total cost of combustibles. The implementation of a new method that identifies and turns off the least efficient thermal generators allows metaheuristic techniques to determine the value of the optimal power of the other generators, thereby reducing the level of pollutants in the atmosphere. The results are presented in comparative charts of the methods, where the power, emissions, and... [more]
Design Optimization of a Direct-Drive Electrically Excited Synchronous Generator for Tidal Wave Energy
Serigne Ousmane Samb, Nicolas Bernard, Mohamed Fouad Benkhoris, Huu Kien Bui
March 1, 2023 (v1)
Subject: Optimization
Keywords: design optimization, direct-drive, Electrically Excited Synchronous Generators, loss minimization, lumped thermal model, tidal wave energy, working cycle
In the field of marine renewable energies, the extraction of marine currents by the use of tidal current turbines has led to many studies. In contrast to offshore wind turbines, the mass minimization is not necessarily the most important criterion. In that case, Direct-Drive Electrically Excited Synchronous Generators (EESG) can be an interesting solution in a context where the permanent magnet market is more and more stressed. In the particular case of a tidal turbine, the electric generator operates at variable torque and speed all the time. Its sizing must therefore take into account the control strategy and check that all the constraints are respected during the working cycle, particularly the thermal one because its permanent regime is never reached. There is no solution today that can completely solve such a sizing problem. The paper presents a specific solution. In particular, we will see that the method presented allows an avoidance of an oversizing of the generator compared to... [more]
A Survey of Application of Mechanical Specific Energy in Petroleum and Space Drilling
Mitra Khalilidermani, Dariusz Knez
March 1, 2023 (v1)
Subject: Optimization
Keywords: drill bit, drilling optimization, DSE, Mars, Moon, MSE, regolith, ROP, space drilling, UCS
The optimization of drilling operations is an ongoing necessity since the major proportion of the terrestrial hydrocarbon reservoirs has been exhausted. Furthermore, there is a growing tendency among the space exploration agencies to drill the subsurface formations of the remote planets, such as the Moon and Mars. To optimize the drilling efficiency in such complicated conditions, the mechanical specific energy (MSE) must be efficiently reduced. The available MSE models incorporate the different parameters related to the surface rig, drill bit, and the underlying rocks to estimate the MSE values. In this research, the current status of those MSE models is assessed, and their relevant assumptions, limitations, applications, and pros and cons are profoundly argued. From the current scrutiny, it was deduced that the available MSE models require more geomechanical parameters to be included in their formulations. Furthermore, the use of artificial intelligence (AI) techniques was identified... [more]
A Flexible-Reliable Operation Model of Storage and Distributed Generation in a Biogas Power Plant
Renata Rodrigues Lautert, Wagner da Silva Brignol, Luciane Neves Canha, Olatunji Matthew Adeyanju, Vinícius Jacques Garcia
March 1, 2023 (v1)
Subject: Optimization
Keywords: biogas, distributed generation, Energy Storage, Optimization, transactive energy
This paper presents a novel methodology for planning and operating biogas energy systems based on the transactive energy concept to determine multilevel operating regimes for distributed generation. The developed model is used to manage the production, storage, and dispatch of biogas energy systems to meet the load demands of the biogas producer and support the operation of the distribution network operator. An Integer Linear Programming (ILP) is fitted to optimize the biogas production of the biogas producer, including the operation of the biogas storage systems and their interaction with the network operator. The model’s objective is to maximize benefits for the participating agents in a transactive energy context. The model’s effectiveness is validated using seven case studies involving biogas systems having different operating ranges and modes to achieve enhanced flexibility and reliability for the system operation with a large proportion of intermittent energy resources. The simul... [more]
Heuristic Optimization Approaches for Capacitor Sizing and Placement: A Case Study in Kazakhstan
Olzhas Baimakhanov, Hande Şenyüz, Almaz Saukhimov, Oğuzhan Ceylan
March 1, 2023 (v1)
Subject: Optimization
Keywords: capacitor allocation and sizing problem, heuristic methods, Optimization, smart grid
Two methods for estimating the near-optimal positions and sizes of capacitors in radial distribution networks are presented. The first model assumes fixed-size capacitors, while the second model assumes controllable variable-size capacitors by changing the tap positions. In the second model, we limit the number of changes in capacitor size. In both approaches, the models consider many load scenarios and aim to obtain better voltage profiles by minimizing voltage deviations and active power losses. We use two recently developed heuristic algorithms called Salp Swarm Optimization algorithm (SSA) and Dragonfly algorithm (DA) to solve the proposed optimization models. We performed numerical simulations using data by modifying an actual distribution network in Almaty, Kazakhstan. To mimic various load scenarios, we start with the baseline load values and produce random variations. For the first model, the optimization algorithms identify the near-optimal positioning and sizes of fixed-size... [more]
Comprehensive Energy Demand Response Optimization Dispatch Method Based on Carbon Trading
Wenqiang Guo, Xinyi Xu
March 1, 2023 (v1)
Subject: Optimization
Keywords: carbon-trading mechanism, demand response, integrated energy system, optimal dispatch
With the increasingly prominent environmental problems in the world today, the development of an integrated energy system and the introduction of a carbon-trading mechanism have become important means to realize the low carbonization of the energy industry. Based on this, this paper introduces the carbon-trading mechanism into the research on the optimal dispatch of an integrated energy system. The mechanism of integrated energy demand response participating in low-carbon economic dispatch is analyzed. The relationship between carbon emissions and carbon-trading price in carbon-trading mechanism is described. On the basis of considering the commodity attributes of the electricity and gas load and the flexible supply characteristics of the thermal load, an incentive-type comprehensive energy demand response model is established. Finally, aiming at the lowest comprehensive operating cost, a comprehensive energy system model considering the power balance and equipment constraints of the e... [more]
Research on the Design of Auxiliary Generator for Enthalpy Reduction and Steady Speed Scroll Expander
Jiongjiong Cai, Peng Ke, Xiao Qu, Zihui Wang
March 1, 2023 (v1)
Subject: Optimization
Keywords: analytic hierarchy process, cryogenic refrigeration, maximum efficiency output, motor optimization, scroll expander
To help the reverse Brayton cycle cool the refrigerant from 100 K to 50 K, an auxiliary generator, with a housed stator, is studied and optimized, and the influences of weights in the cost- function on the results are discussed. The power demand and adiabatic characteristics of reverse Brayton cycle expansion are analyzed, after which the optimization indexes, including output rated power, efficiency, the air gap between rotor and stator, loss, and volume, are decided. The initial model of the auxiliary generator is then constructed and the parameters to be optimized are also determined. Taking the low loss and sinusoidal back-EMF as the evaluation indexes, the single parameter optimizations of the auxiliary generator are carried out. The co-simulation of the generator and its corresponding driving circuit is investigated, with which the power generation efficiency is calculated. The global optimizations of the generator parameters are carried out using a genetic algorithm. A suitable... [more]
Optimization Design of Unequal Amplitude Modulated Poles for the Bearingless PMSM
Huimin Wang, Yuting Lu, Shuang Wu, Liyan Guo
March 1, 2023 (v1)
Subject: Optimization
Keywords: bearingless PMSM, low suspension force ripple, low torque ripple, Taguchi, unequal amplitude modulation
The structural parameters of an equal amplitude modulated magnetic pole is limited by the length of the air-gap. When the modulation ratio or carrier ratio is small, the spacing of permanent magnets is too large, which will lead to a worse cogging effect, and then the torque optimization effect is not satisfying. In order to improve the operation stability of a bearingless permanent magnet synchronous motor (bearingless PMSM), an unequal amplitude modulated magnetic pole structure is proposed according to the principle of magnetic pole modulation. The Taguchi method is used to optimize the structural parameters of the unequal amplitude modulated magnetic pole with the goal of reducing the torque and suspension force fluctuation. Three kinds of magnetic pole structures, named the whole magnetic pole, the equal amplitude modulated magnetic pole and the unequal amplitude modulated magnetic pole are compared and verified. The results show that the proposed structure of the unequal amplitud... [more]
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