Summary
The distributed generation (DG) is getting extensively integrated in existing power distribution system because of the massive development in green energy technologies and their economical, technical, and environment benefits. However, apart from beneficial aspects, DGs also have various and complex technical limitations, major of which are loss of protection coordination among protection devices which can lead to malfunctioning of protection devices, blind protection, fuse blowing, and permanent outage of power supply due to temporary faults. In this paper, a novel curve fitting technique is designed to restore much influenced recloser‐fuse coordination using the directional properties of midline recloser for upstream and downstream protection devices coordination. It also works on fuse‐saving scheme. Using Electrical Transient Analysis Program (ETAP) Software, the proposed methodology is implemented on a real 11 kV Rajewala radial distribution feeder starting from 132 kV Eimnabad grid station, district Gujranwala, Pakistan. Present here are some key results. Different case studies are carried out and results validate the effectiveness of the proposed methodology, and the coordination among protection devices is sustained even after DGs integration in the system.
Abstract:The energy management of office buildings has been a rising concern for owners, researchers, and energy suppliers. The volatility of power load in office buildings threatens energy consumption and risks device security. This paper investigates the load fluctuation patterns in an office building based on user data, using recurrence interval analysis for different thresholds. The recurrence intervals of volatility are fitted by stretched exponential distribution, from which the probability density function is derived. Then, the short-term and long-term memory effect on the fluctuations are learned by conditional probability density function and multifractal detrended fluctuation analysis, respectively. A hazard function is further established to analyze the risk estimation of load volatility and derive the value at risk (VaR). Thus, a functional relationship has been established between average recurrence interval and threshold. The methodology and analysis results addressed in this paper help to understand load fluctuation patterns and aid in the design of energy consumption strategies in office buildings. According to the results of our research, conclusions and management suggestions are provided at the end of this paper.
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