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

Abstract

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.

LED lights of various colors for comprehending the photoelectric effects phenomena

“…In other words, if the LED being used as a light source somehow has a wavelength that is less than the wavelengths that the LED receiver would 'emit,' [29]. In our educational opportunity, for instance, pairing an amber LED with a red or amber LED enables us to check for photoemission [30]. Furthermore, the yellow LED can be coupled with the ultraviolet, blue, and green LEDs to see if photoemission happens independent of the yellow LED's brightness [31].…”

Stochastic voltage stability margin in unbalance feeder with fuzzy based distributed generation placement

“…In this paper a fuzzy expert system as depicted in figure 3 is utilized for optimum location and sizing of single DG unit, which have capacity of DG is 440 KW per phase and operated between 35 to 73 period of metering time interval [11]. It was observed that substation transformer got overloaded during 35 to 71 metering time interval and favorable to solar photovoltaic integration [6].In this expert system, mamdani fuzzy model is used for DG sizing, whereas sugenon fuzzy model utilized for finding location.…”

“…These top 15 vulnerable nodes determined by survivability index (SI), a function of voltage stability margin (VSI) and voltage deviation index (VDI) [11].The membership functions associated each crisp input/output variable and fuzzy rules shown for both fuzzy model are shown in figure 4 to 15. …”

“…In this context, voltage stability has emerged as a serious concern for an integrated distribution system and emerged as an active area for researchers. The performance indices referred in [5] are utilized for optimal siting and size of DG by fuzzy expert system [11].In order to improve voltage stability for grid integrated wind farm, an effective fuzzy logic approach proposed and results are compared with the conventional solutions [12]. J. Xu.…”