Multi-Object Optimization Research about Wind/Solar Hybrid Generation System

2014 ◽  
Vol 672-674 ◽  
pp. 337-341
Author(s):  
Zhi Huang Liu ◽  
Hai Yuan Liu ◽  
Xue Jun Gao
Keyword(s):  
Test Data ◽  
Hybrid System ◽  
Optimization Model ◽  
Cost Control ◽  
System Optimization ◽  
Optimization Method ◽  
Generation System ◽  
Hybrid Generation ◽  
Pareto Solutions

Wind/solar hybrid system optimization is a key point for cost control. Here a multi-object optimization model is raised. Then a multi-object optimization method based on GA is used to find the Pareto solutions of wind/solar hybrid system. The test data shows that this method can get a good result.

scholarly journals Sizing Optimization and Experimental Verification of a Hybrid Generation Water Pumping System in a Greenhouse

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Dan Li ◽  
Delan Zhu ◽  
Ruixin Wang ◽  
Maosheng Ge ◽  
Shoujun Wu ◽  
...  
Keyword(s):  
Power Supply ◽  
Optimization Model ◽  
Field Experiments ◽  
Irrigation Schedule ◽  
Climatic Conditions ◽  
Generation System ◽  
Hybrid Generation ◽  
Wind Generator ◽  
Pumping System ◽  
Water Pumping

In remote agricultural areas, electrical energy is usually deficient for pumping water into greenhouses. Photovoltaic (PV) panels and wind generators are considered suitable options for power supply. The reliability of hybrid generation water pumping depends primarily on the number of system components, which should be adapted to the local climatic conditions and crop irrigation schedule. In this study, a universal size optimization model is established to optimize the configuration of a hybrid PV-wind-battery (PWB) generation system. The climatic conditions and crop irrigation schedule are parameterized in the model. Minimization of the annual cost of the hybrid PWB system is the objective function. The constraints include the battery state of charge (SOC) and the power supply reliability, which consists of the loss of power supply (δLPS) and the excess energy (δEX). The numbers of PV panels and batteries, as well as the rated power of the wind generator, are the decision variables. The optimization model of the PWB generation system is solved using a particle swarm optimization (PSO) algorithm based on penalty function. The model is then applied to determine the optimal configuration of a water pumping system for a greenhouse used to grow tomatoes. Measured climatic data are used in the optimization process, which is conducted in the month of maximum irrigation water requirement (August). The optimal results for this greenhouse are two PV panels and two batteries, and the rated power of the wind generator is 375 W. Furthermore, field experiments are performed to validate the optimization model. The field experiment results show that the total output power of the PV panels and wind generator during 15 d are 41.478 kW and 6.235 kW, respectively. The total load power of the pump is 36.965 kW. The field experiments demonstrate that the optimal results are able to meet the power requirements of the water pumping system and the sizing optimization model is appropriate.

scholarly journals IGDT-Based Wind–Storage–EVs Hybrid System Robust Optimization Scheduling Model

Energies ◽  
2019 ◽  
Vol 12 (20) ◽  
pp. 3848
Author(s):  
Bo Sun ◽  
Simin Li ◽  
Jingdong Xie ◽  
Xin Sun
Keyword(s):  
Robust Optimization ◽  
Wind Power ◽  
Hybrid System ◽  
Electricity Market ◽  
Optimization Model ◽  
Probabilistic Approach ◽  
System Optimization ◽  
Stable Operation ◽  
Scheduling Model ◽  
Optimization Scheduling

Wind power has features of uncertainty. When wind power producers (WPPs) bid in the day-ahead electricity market, how to deal with the deviation between forecasting output and actual output is one of the important topics in the design of electricity market with WPPs. This paper makes use of a non-probabilistic approach—Information gap decision theory (IGDT)—to model the uncertainty of wind power, and builds a robust optimization scheduling model for wind–storage–electric vehicles(EVs) hybrid system with EV participations, which can make the scheduling plan meet the requirements within the range of wind power fluctuations. The proposed IGDT robust optimization model first transforms the deterministic hybrid system optimization scheduling model into a robust optimization model that can achieve the minimum recovery requirement within the range of wind power output fluctuation, and comprehensively considers each constraint. The results show that the wind–storage–EVs hybrid system has greater operational profits and less impact on the safe and stable operation of power grids when considering the uncertainty of wind power. In addition, the proposed method can provide corresponding robust wind power fluctuation under different expected profits of the decision-maker to the wind–storage–EVs hybrid system.

Battery Capacity Evaluation Research on Wind\Battery Hybrid Generation System

2012 ◽  
Vol 512-515 ◽  
pp. 1022-1026 ◽  
Author(s):  
Zhi Huang Liu ◽  
Jie Qiong Han ◽  
Xue Jun Gao
Keyword(s):  
Energy Conversion ◽  
Evaluation Research ◽  
System Optimization ◽  
New Method ◽  
Generation Process ◽  
Generation System ◽  
Hybrid Generation ◽  
Capacity Evaluation ◽  
Battery Capacity ◽  
Peak Value

Battery capacity evaluation is a key work in wind\battery hybrid generation system optimization. Here a research about battery capacity evaluation of wind\battery hybrid generation system is made and a new way to evaluate the capacity is given. First, common evaluation methods such as integration peak value method are introduced. Then energy conversion constraints analysis in wind\battery hybrid generation process is given. Fake charge problem existed in integration peak value method is described comprehensively. At last, a new method to evaluate the battery capacity is put out.

On Measures of Coupling Between the Artifact and Controller Optimal Design Problems

2009 ◽  
Author(s):  
Diane L. Peters ◽  
Panos Y. Papalambros ◽  
A. Galip Ulsoy
Keyword(s):  
System Optimization ◽  
Optimization Method ◽  
Ease Of Use ◽  
Control Problems ◽  
Design Problems ◽  
Sensitivity Equations ◽  
Smart Products ◽  
Two Measures ◽  
And Control ◽  
Artifact Design

Optimization of smart products requires optimizing both the artifact design and its controller. The presence of coupling between the design and control problems is an important consideration in choosing the system optimization method. Several measures of coupling have been proposed based on different viewpoints of the system. In this paper, two measures of coupling, a vector based on optimality conditions and a matrix derived from an extension of the global sensitivity equations, are shown to be related under certain conditions and to be consistent in their coupling determination. The measures’ physical interpretation and relative ease of use are discussed using the example of a positioning gantry. A further relation is derived between one measure and a modified sequential formulation that would give results sufficiently close to the true solutions.

Trajectory Optimization Applied to Space Rendezvous

2013 ◽  
Vol 756-759 ◽  
pp. 3466-3470
Author(s):  
Xu Min Song ◽  
Qi Lin
Keyword(s):  
Simulated Annealing ◽  
Optimization Model ◽  
Trajectory Optimization ◽  
Optimization Problem ◽  
Optimization Method ◽  
Nonlinear Constraints ◽  
Design Variables ◽  
Adaptive Simulated Annealing ◽  
Simulation Results

The trajcetory plan problem of spece reandezvous mission was studied in this paper using nolinear optimization method. The optimization model was built based on the Hills equations. And by analysis property of the design variables, a transform was put forward , which eliminated the equation and nonlinear constraints as well as decreaseing the problem dimensions. The optimization problem was solved using Adaptive Simulated Annealing (ASA) method, and the rendezvous trajectory was designed.The method was validated by simulation results.

Harmonic Synthesis Design Methodology for Dynamic Spring Balancing

1996 ◽  
Vol 118 (4) ◽  
pp. 733-740 ◽  
Author(s):  
Eungsoo Shin ◽  
D. A. Streit
Keyword(s):  
Dynamic System ◽  
Initial Conditions ◽  
Phase 1 ◽  
System Optimization ◽  
Optimization Method ◽  
Optimization Techniques ◽  
System Response ◽  
Two Phase ◽  
Walking Machine ◽  
Synthesis Design

A new spring balancing technique, called a two-phase optimization method, is presented. Phase 1 uses harmonic synthesis to provide a system configuration which achieves an approximation to a desired dynamic system response. Phase 2 uses results of harmonic synthesis as initial conditions for dynamic system optimization. Optimization techniques compensate for nonlinearities in machine dynamics. Example applications to robot manipulators and to walking machine legs are presented and discussed.

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