Methodology for the analysis of voltage unbalance in networks with single-phase distributed generation

The distributed generation involving multiple photovoltaic sources and synthesizing high-quality ac voltage from those multiple dc sources are nascent research ambits. A host of multilevel inverters (MLIs) has been ascertained for performing above errand diligently, where the component count is obnoxious. The single phase seven-level inverter is an acquiescent compromise between the circuit complexity and the quality of the output. Further enhancement on the performance can be succored through optimizing dc link voltages and switching angles. This paper proposes a component count pruned MLI structure and also a refined genetic algorithm (RGA)-based optimization scheme for the computation of both dc link voltages and switching angles. Previous attempts for this problem have solved the switching angles with the objective of resulting minimum harmonic content in the staircase-shaped output voltage. The dc link voltage of each level is however assumed to be the same and constant. As an extension, RGA-based optimization of both dc link voltages and switching angles is triumphed. The harmonic profile of the proposed switching strategy is simulated and also corroborated by a hardware prototype. In practice, the proposed fundamental switched strategy is apposite, in which each dc voltage can be self-maintained and independently controlled. In addition, a method for designing the passive LC filter is also presented.

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Fuzzy Logic Controller Based Distributed Generation Integration Strategy for Stochastic Performance Improvement

Advances in Electrical Engineering ◽

10.1155/2016/9760538 ◽

2016 ◽

Vol 2016 ◽

pp. 1-13

Author(s):

Jagdish Prasad Sharma ◽

H. Ravishankar Kamath

Keyword(s):

Fuzzy Logic ◽

Distributed Generation ◽

Fuzzy Logic Controller ◽

Load Ratio ◽

Time Interval ◽

Distributed Generations ◽

Voltage Unbalance ◽

Load Models ◽

The Impact ◽

Zip Load

In the restructured environment, distributed generation (DG) is considered as a very promising option due to a high initial capital cost of conventional plants, environmental concerns, and power shortage. Apart from the above, distributed generation (DG) has also abilities to improve performance of feeder. Most of the distribution feeders have radial structure, which compel to observe the impact of distributed generations on feeder performance, having different characteristics and composition of time varying static ZIP load models. Two fuzzy-based expert system is proposed for selecting and ranking the most appropriated periods to an integration of distributed generations with a feeder. Madami type fuzzy logic controller was developed for sizing of distributed generation, whereas Sugeno type fuzzy logic controller was developed for the DG location. Input parameters for Madami fuzzy logic controller are substation reserve capacity, feeder power loss to load ratio, voltage unbalance, and apparent power imbalances. DG output, survivability index, and node distance from substation are chosen as input to Sugeno type fuzzy logic controller. The stochastic performance of proposed fuzzy expert systems was evaluated on a modified IEEE 37 node test feeder with 15 minutes characteristics time interval varying static ZIP load models.

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