A novel arithmetic sequence pattern reconfiguration technique for line loss reduction of photovoltaic array under non-uniform irradiance

This paper presents an optimization approach for criteria setting of Renewable Distributed Generation (DG) in the Green Building Rating System (GBRS). In this study, the total line loss reduction is analyzed and set as the main objective function in the optimization process which then a reassessment of existing criteria setting for renewable energy (RE) is proposed towards lower loss outcome. Solar photovoltaic (PV)-type DG unit (PV-DG) is identified as the type of DG used in this paper. The proposed PV-DG optimization will improve the sustainable energy performance of the green building by total line losses reduction within accepted lower losses region using Artificial bee colony (ABC) algorithm. The distribution network uses bus and line data setup from selected one of each three levels of Malaysian public hospital. MATLAB simulation result shows that the PV-DG expanding capacity towards optimal scale and location provides a better outcome in minimizing total line losses within an appropriate voltage profile as compared to the current setting of PV-DG imposed in selected GBRS. Thus, reassessment of RE parameter setting and the proposed five rankings with new PV-DG setting for public hospital provides technical justification and give the best option to the green building developer for more effective RE integration.

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Analysis on Losses of Distribution Network and Countermeasures to Reduce Losses

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.960-961.1483 ◽

2014 ◽

Vol 960-961 ◽

pp. 1483-1489

Author(s):

Qian Wang ◽

Shang Ji Chen ◽

Xiao Hui Han

Keyword(s):

Distribution Network ◽

Loss Reduction ◽

Social Significance ◽

Loss Model ◽

Planning And Design ◽

Operation And Maintenance ◽

Line Loss ◽

Save Energy ◽

Current Energy ◽

Power Configuration

The thesis describes the loss model of distribution network and gives the transformer loss model and line loss model, Then it proposes some loss reduction measures at the stage of planning and design as well as operation and maintenance. Finally, according to the main problems about the loss reduction measures in China, it puts forward some countermeasures to reduce line loss . Distribution network as part of the end for power configuration which is directly connected with the users of demand side. The loss of distribution network has been high because of feeder radius, complex voltage grade and a large number of devices on the network. The line loss of distribution network represents a major component of the line loss in the whole power system, the line loss of 10kv and below distribution network accounts for about 78% in it according to statistical analysis[1-2]. So, under the current energy shortage situation, there is a great economic and social significance to adopt the reasonable measures to save energy and decrease loss in distribution network.

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Research on Electric Power with Development and Application of Line Loss Rate Forecasting Software Based on MLRM-GM

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.977.182 ◽

2014 ◽

Vol 977 ◽

pp. 182-185 ◽

Cited By ~ 1

Author(s):

Wei Dong Liu ◽

Ting Jian Zeng ◽

Tong Jun ◽

Lin Lin Shang Guan ◽

Bing Jie Li

Keyword(s):

Linear Regression ◽

Adverse Effects ◽

Electric Power ◽

Loss Rate ◽

Multiple Linear Regression Model ◽

Rate Data ◽

Loss Reduction ◽

Gray Prediction ◽

Line Loss ◽

Accuracy Of Prediction

A hybrid model is proposed which is a combination of MLRM (Multiple Linear Regression Model) and GM (Gray Prediction Model). The paper conducts a line loss rate forecast of the grid, and develops a kind of forecasting software for the line loss managers of grid enterprises to realize the analysis and forecast of factors which impact the daily loss line rate. Finally, do simulation examples with line loss rate data of a city using the software. The results demonstrate that the models selected in the software have good feasibility in line loss rate forecasting, and can overcome the adverse effects of factors on the model, improve the accuracy of prediction and provide the basis for the scientific and reasonable loss reduction plan.

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