Distributed photovoltaic integration as complementary energy: consideration of solutions for power loss and load demand growth problems

The modern power distribution network is constantly being faced with an ever-growing load demand resulting into increased burden and reduced voltage, which leads to find alternative source of energy to meet it. In Nepal, the electricity supply is based on hydropower primarily, which are situated very far from load centers and hence the generated power are to be transmitted through transmission and distributed system. Among the systems, radial distribution system is popular because of low cost and simple design, but it has power quality issues like low voltage profile and higher loss. In response to the problem of increased load demand, efforts have been made to decentralize this infrastructure through the use of distributed generators. However, the improper sizing and placement of DG unit may lead to higher power loss and power instability. The optimization problem of DG unit placement and its capacity determination were performed in this research. The study has been carried out for Thimi-Sallaghari Feeder and this feeder has low voltage profile and higher power loss. The IEEE 33 bus test system was examined as a test case to demonstrate the effectiveness of the proposed approach. The study has been carried out in MATLAB using “Backward and Forward Sweep Method” for load flow analysis and Genetic Algorithm for optimization. The number of DG unit of different size integrated was varied from one to ten. The result of this study showed that the voltage at minimum voltage node, maximum active and reactive loss reduction of Thimi-Sallaghari feeder have been improved by 3.69% (from 0.942 p.u. to 0.976 p.u), 75.88 % and 75.88 % respectively with placement of DG units at three bus locations of total 658.2019 kW and 395.873 kVAR capacity. Likewise, the voltage at minimum voltage node, maximum active and reactive loss of IEEE- 33 bus system have been improved by 6.88 %, 90.11% and 89.9% respectively with placement of DG units of total 2215.488 kW and 1176.059 kVAR at 6 different locations of the network.

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Management of Voltage Profile and Power Loss Minimization in a Grid-Connected Microgrid System Using Fuzzy-Based STATCOM Controller

Journal of Electrical and Computer Engineering ◽

10.1155/2020/2040139 ◽

2020 ◽

Vol 2020 ◽

pp. 1-13

Author(s):

Mezigebu Getinet Yenealem ◽

Livingstone M. H. Ngoo ◽

Dereje Shiferaw ◽

Peterson Hinga

Keyword(s):

Distribution System ◽

Power Loss ◽

Power Flow ◽

Fossil Fuels ◽

Distribution Network ◽

Voltage Profile ◽

Static Synchronous Compensator ◽

Voltage Unbalance ◽

Load Demand ◽

Power Loss Reduction

The expansion of renewable energy is continuing powerfully. Electrical system ought to transmit power with diminished loss, improved power quality, and reliability while pleasing the need of customer’s load demand. Nevertheless, owing to the exhaustion of fossil fuels and their environmental impact, the availability of quality, stable, and reliable power in developing countries is worrying. Integrating a solar-wind based microgrid to the distribution network is the more feasible and best alternative solution to gratify the customer intensifying power demand while seeing the strict environmental regulations of generating power. However, the microgrid system connected in a distribution network has diverse problems and challenges. The problems comprise the development of voltage sag and swell, voltage unbalance, and power losses because of the intermittent nature of PV and wind resources. The objective of this study is to integrate microgrid system with STATCOM (static synchronous compensator) controller to ensure the higher power flow with enhanced voltage profile and reduced power loss. MATLAB/PSAT is used to model microgrid and STATCOM controller connected to the grid. Proportional integral (PI) and fuzzy logic controllers (FLC) are also applied to control the STATCOM. The effectiveness of STATCOM with microgrid integration is tested by connecting to the main distribution system using standard IEEE 30-bus system. Finally, it was observed that STATCOM raises the capacity of the distribution line and contributes to voltage profile improvements and power loss reduction.

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Planning and Research of Distribution Feeder Automation with Decentralized Power Supply

Electronics ◽

10.3390/electronics10030362 ◽

2021 ◽

Vol 10 (3) ◽

pp. 362

Author(s):

Yen-Chih Huang ◽

Wen-Ching Chang ◽

Hsuan Hsu ◽

Cheng-Chien Kuo

Keyword(s):

Power System ◽

Power Loss ◽

Power Grid ◽

Loss Reduction ◽

Voltage Profile ◽

Distributed Energy ◽

Feeder Automation ◽

Distributed Generator ◽

Load Demand ◽

Power Loss Reduction

The high penetration of distributed generation in distributed energy systems causes the variation of power loss and makes the power grid become more complicated, so this paper takes various types of optimal algorithms into account and simulates the feeder reconfiguration on the IEEE-33 system as well as the Taiwan power system. The simulation verifies linear population size reduction of successful history-based adaptive differential evolution (L-SHADE) and particle swarm optimization (PSO) fitness in different systems and provides the recommended location of distributed energy. The proposed method keeps the voltage bound of 0.95 to 1.03 p.u. of Taiwan regulation. In the IEEE-33 system, we achieved a 52.57% power loss reduction after feeder reconfiguration, and a 70.55% power loss reduction after the distributed generator was implemented and feeder reconfiguration. Under the variation of load demand and power generation of the Taiwan power system, we establish the system models by forecasting one-day load demand. Then, we propose a one-day feeder switch operation strategy by considering the switches’ operation frequency with the reduction of 83.3% manual operation and recommend feeder automation to achieve feeder power loss reduction, voltage profile improvement and get regional power grid resilient configuration.

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Optimal Design of an On-Grid MicroGrid Considering Long-Term Load Demand Forecasting: A Case Study

Distributed Generation & Alternative Energy Journal ◽

10.13052/dgaej2156-3306.3546 ◽

2021 ◽

Author(s):

Bing Han ◽

Mingxuan Li ◽

Jingjing Song ◽

Junjie Li ◽

Jamal Faraji

Keyword(s):

Demand Forecasting ◽

Load Prediction ◽

Load Profile ◽

Demand Prediction ◽

Demand Growth ◽

Load Demand ◽

Cost Of Energy ◽

Artificial Neural Network Ann

In this article, an optimal on-grid MicroGrid (MG) is designed considering long-term load demand prediction. Multilayer Perceptron (MLP) Artificial Neural Network (ANN) has been used for time-series load prediction. Yearly demand growth has also been considered in the optimization process based on the forecasted load profile. Two case studies have been performed with the forecasted and historical load profiles, respectively. It has been shown that by applying the forecasted load profile, realistic results of net present cost (NPC), cost of energy (COE) and MG configuration would be achieved. Moreover, it has been demonstrated that utilizing battery storage systems (BSSs) are not economic in the proposed system. The introduced MG also produces lower emission compared to the system with the historical load profile.

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