• Title/Summary/Keyword: Energy System Optimization

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Resource Allocation for Relay-Aided Cooperative Systems Based on Multi-Objective Optimization

  • Wu, Runze;Zhu, Jiajia;Hu, Hailin;He, Yanhua;Tang, Liangrui
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.5
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    • pp.2177-2193
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    • 2018
  • This paper studies resource allocation schemes for the relay-aided cooperative system consisting of multiple source-destination pairs and decode-forward (DF) relays. Specially, relaying selection, multisubcarrier pairing and assignment, and power allocation are investigated jointly. We consider a combinatorial optimization problem on quality of experience (QoE) and energy consumption based on relay-aided cooperative system. For providing better QoE and lower energy consumption we formulate a multi-objective optimization problem to maximize the total mean opinion score (MOS) value and minimize the total power consumption. To this end, we employ the nondominated sorting genetic algorithm version II (NSGA-II) and obtain sets of Pareto optimal solutions. Specially, two formulas are devised for the optimal solutions of the multi-objective optimization problems with and without a service priority constraint. Moreover, simulation results show that the proposed schemes are superior to the existing ones.

Techno-Economic Optimization of a Grid-Connected Hybrid Energy System Considering Voltage Fluctuation

  • Saib, Samia;Gherbi, Ahmed;Kaabeche, Abdelhamid;Bayindir, Ramazan
    • Journal of Electrical Engineering and Technology
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    • v.13 no.2
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    • pp.659-668
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    • 2018
  • This paper proposes an optimization approach of a grid-connected photovoltaic and wind hybrid energy system including energy storage considering voltage fluctuation in the electricity grid. A techno-economic analysis is carried out in order to minimize the size of hybrid system by considering the benefit-cost. Lithium-ion battery type is used for both managing the electricity selling to the grid and reducing voltage fluctuation. A new technique is developed to limit the voltage perturbation caused by the solar irradiance and the wind speed through determining the state-of-charge of battery for every hour of a day. Improved particle swarm optimization (PSO) methods, referred to as FC-VACPSO which combines Fast Convergence Particle Swarm Optimization (FCPSO) method and Variable Acceleration Coefficient Based Particle Swarm Optimization (VACPSO) method are used to solve the optimization problem. A comparative study has been performed between standard PSO method and PSO based methods to extract the best size with the benefit cost. A sensitivity analysis has been studied for different kinds and costs of batteries, by considering variable and constant state-ofcharge of battery. The simulations, performed under Matlab environment, yield good results using the FC-VACPSO method regarding the convergence and the benefit cost of the hybrid system.

A Multi-objective Optimization Method for Energy System Design Considering Initial Cost and Primary Energy Consumption (초기투자비와 1차 에너지소비량을 고려한 에너지시스템의 다중최적 설계 방법론)

  • Kong, Dong-Seok;Jang, Yong-Sung;Huh, Jung-Ho
    • Korean Journal of Air-Conditioning and Refrigeration Engineering
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    • v.26 no.8
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    • pp.357-365
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    • 2014
  • This paper proposed a multi-objective optimization method for building energy system design using primary energy consumption and initial cost. The designing of building energy systems is a complex task, because life cycle cost and efficiency of building are determined by decisions of engineer during the early stage of design. Therefore, methods such as pareto analysis that can generate various alternatives for decision making are necessary. In this study, the optimization is performed using the NSGAII and case study was carried out for feasibility of the proposed method. As a result, alternative solutions can be obtained for the optimal building energy system design.

Broadband energy harvester for varied tram vibration frequency using 2-DOF mass-spring-damper system

  • Hamza Umar;Christopher Mullen;Soobum Lee;Jaeyun Lee;Jaehoon Kim
    • Smart Structures and Systems
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    • v.32 no.6
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    • pp.383-391
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    • 2023
  • Energy harvesting in trams may become a prevalent source of passive energy generation due to the high density of vibrational energy, and this may help power structural health monitoring systems for the trams. This paper presents a broadband vibrational energy harvesting device design that utilizes a varied frequency from a tram vehicle using a 2 DOF vibrational system combined with electromagnetic energy conversion. This paper will demonstrate stepwise optimization processes to determine mechanical parameters for frequency tuning to adjust to the trams' operational conditions, and electromagnetic parameters for the whole system design to maximize power output. The initial optimization will determine 5 important design parameters in a 2 DOF vibrational system, namely the masses (m1, m2 (and spring constants (k1, k2, k3). The second step will use these parameters as initial guesses for the second optimization which will maintain the ratios of these parameters and present electrical parameters to maximize the power output from this system. The obtained values indicated a successful demonstration of design optimization as the average power generated increased from 1.475 mW to 17.44 mW (around 12 times).

A Study on ESS Optimal Operation Strategy Using Two Stage Hybrid Optimization (Two Stage Hybrid Optimization을 사용한 ESS 최적 운전 전략에 대한 연구)

  • Gong, Eun-Kyoung;Sohn, Jin-Man
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.67 no.7
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    • pp.833-839
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    • 2018
  • This paper presents an analysis and the methodology of optimal operation strategy of the ESS(Energy Storage System) for reduce electricity charges. Electricity charges consist of a basic charge based on the contract capacity and energy charge according to the power usage. In order to use electrical energy at minimal charge, these two factors are required to be reduced at the same time. QP(Quadratic Programming) is appropriate for minimization of the basic charge and LP(Linear Programmin) is adequate to minimize the energy charge. However, the integer variable have to be introduced for modelling of different charge and discharge efficiency of ESS PCS(Power Conversion System), where MILP(Mixed Integer Linear Programming) can be used. In this case, the extent to which the peak load savings is accomplished should be assumed before the energy charge is minimized. So, to minimize the electricity charge exactly, optimization is sequentially performed in this paper, so-called the Two Stage Hybird optimization, where the extent to which the peak load savings is firstly accomplished through optimization of basic charge and then the optimization of energy charge is performed with different charge and discharge efficiency of ESS PCS. Finally, the proposed method is analyzed quantitatively with other optimization methods.

Design of Fuzzy Logic Controller for Optimal Control of Hybrid Renewable Energy System (하이브리드 신재생에너지 시스템의 최적제어를 위한 퍼지 로직 제어기 설계)

  • Jang, Seong-Dae;Ji, Pyeong-Shik
    • The Transactions of the Korean Institute of Electrical Engineers P
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    • v.67 no.3
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    • pp.143-148
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    • 2018
  • In this paper, the optimal fuzzy logic controller(FLC) for a hybrid renewable energy system(HRES) is proposed. Generally, hybrid renewable energy systems can consist of wind power, solar power, fuel cells and storage devices. The proposed FLC can effectively control the entire HRES by determining the output power of the fuel cell or the absorption power of the electrolyzer. In general, fuzzy logic controllers can be optimized by classical optimization algorithms such as genetic algorithms(GA) or particle swarm optimization(PSO). However, these FLC have a disadvantage in that their performance varies greatly depending on the control parameters of the optimization algorithms. Therefore, we propose a method to optimize the fuzzy logic controller using the teaching-learning based optimization(TLBO) algorithm which does not have the control parameters of the algorithm. The TLBO algorithm is an optimization algorithm that mimics the knowledge transfer mechanism in a class. To verify the performance of the proposed algorithm, we modeled the hybrid system using Matlab Tool and compare and analyze the performance with other classical optimization algorithms. The simulation results show that the proposed method shows better performance than the other methods.

Operation optimization of auxiliary electric boiler system in HTR-PM nuclear power plant

  • Du, Xingxuan;Ma, Xiaolong;Liu, Junfeng;Wu, Shifa;Wang, Pengfei
    • Nuclear Engineering and Technology
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    • v.54 no.8
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    • pp.2840-2851
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    • 2022
  • Electric boilers (EBs) are the backup steam source for the auxiliary steam system of high-temperature gas-cooled reactor nuclear power plants. When the plant is in normal operations, the EB is always in hot standby status. However, the current hot standby operation strategy has problems of slow response, high power consumption, and long operation time. To solve these problems, this study focuses on the optimization of hot standby operations for the EB system. First, mathematical models of an electrode immersion EB and its accompanying deaerator were established. Then, a control simulation platform of the EB system was developed in MATLAB/Simulink implementing the established mathematical models and corresponding control systems. Finally, two optimization strategies for the EB hot standby operation were proposed, followed by dynamic simulations of the EB system transient from hot standby to normal operations. The results indicate that the proposed optimization strategies can significantly speed up the transient response of the EB system from hot standby to normal operations and reduce the power consumption in hot standby operations, improving the dynamic performance and economy of the system.

A many-objective optimization WSN energy balance model

  • Wu, Di;Geng, Shaojin;Cai, Xingjuan;Zhang, Guoyou;Xue, Fei
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.14 no.2
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    • pp.514-537
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    • 2020
  • Wireless sensor network (WSN) is a distributed network composed of many sensory nodes. It is precisely due to the clustering unevenness and cluster head election randomness that the energy consumption of WSN is excessive. Therefore, a many-objective optimization WSN energy balance model is proposed for the first time in the clustering stage of LEACH protocol. The four objective is considered that the cluster distance, the sink node distance, the overall energy consumption of the network and the network energy consumption balance to select the cluster head, which to better balance the energy consumption of the WSN network and extend the network lifetime. A many-objective optimization algorithm to optimize the model (LEACH-ABF) is designed, which combines adaptive balanced function strategy with penalty-based boundary selection intersection strategy to optimize the clustering method of LEACH. The experimental results show that LEACH-ABF can balance network energy consumption effectively and extend the network lifetime when compared with other algorithms.

Development of Optimization Program for the Building Energy Efficiency Improvement (건물에너지 효율향상을 위한 최적화 툴의 개발)

  • Han, Soo-Gon;Ihm, Pyeong-Chan;Huh, Jung-Ho;Kwon, Han-Sol
    • Proceedings of the SAREK Conference
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    • 2005.11a
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    • pp.223-228
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    • 2005
  • This study develops an optimization program to use optimum design of building HVAC system reducing building energy use and cost. Doe20pt developed is an interface program between DOE2 and GenOpt to perform the optimization procedure more easily. The optimum results can be used to estimate the economical efficiency concerning the building management.

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A Case Study on the Building Energy Savings through HVAC System Optimization Process (공조시스뎀 최적화를 통한 건물에너지 절감사례 연구)

  • Huh Jung-Ho;Kwon Han-Sol;Han Soo-Gon;Ihm Pyeong-Chan
    • Korean Journal of Air-Conditioning and Refrigeration Engineering
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    • v.18 no.5
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    • pp.426-433
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    • 2006
  • The requirements for the optimal building system design is numerous. However, most system designers do not take care of various design strategies. They often argue that the proper simulation tools are not existed to solve the implicated design requirements and the time to consider many alternatives of building systems are insufficient. The aim of this study is to develop the optimization interface program that considers various system design variables and eventually find both the optimal values of annual energy use and cost. Therefore, Doe2Opt is developed to easily perform simulation-optimization process based on DOE2 and GenOpt, and minimizes energy cost of small-to-medium sized building for 6.7% and that of large sized building for 3% with optimizing several HVAC system variables.