Desh Deepak Sharma

Electrical load profile analysis and peak load assessment using clustering technique

Load profile analysis in different regions is very useful to power utilities for managing the load requirements in economic and efficient manner. For the demand side management and grid operation, the variation in demand is to be known. In this paper, classical k-means clustering approach is used for finding similar types of profiles of a practical system for demand variation analysis and energy loss estimation. For different zones, typical load profiles based on similar consumption are obtained. Primarily, the load factor represents feeder demand variation, and loss factor helps average energy loss estimation in distribution power system without load flow studies. In this paper, a concept is proposed for analysis of electricity consumption pattern on different days in particular zones based on cluster load factor and cluster loss factor. Normal and abnormal peak load requirements in cluster of similar types of profile of days of different zones are identified. Cluster loss factor helps in identifying the energy loss variation due to different load patterns.

Critical load profile estimation for sizing of battery storage system

This paper proposes a method to find the critical load profile for estimating the battery storage size. The critical load profile consists of broadest peak in annual historical load profile data and is assumed an outlier. The local outlier factor approach is implemented in finding the outliers, which are ranked according to degree of anomalies. The discharge duration in critical load profile, with consideration of percentage load growth in peak load of base year and maximum allowed demand 8.5 MW at IIT Kanpur, helps in deciding the expected size of Battery Energy Storage System (BESS). The BESS sized with this power and energy ratings is useful in daily time deferrals, load leveling and peak shaving applications.

Simulation and modeling of dielectric barrier impact on heterogeneous electric field

Non-pressurized air is extensively used as basic insulation medium in medium/high voltage equipments. An inherent property of air-insulated design is that the systems tend to become physically large. Application of dielectric barrier can increase the breakdown voltage and therefore decrease the size of the equipment. In this paper, the impact of dielectric barrier on breakdown voltage enhancement is investigated under both dc and ac applied voltages. For this purpose, two different kinds of dielectric materials as barrier are examined in high voltage electrode structures. Several simulations are carried out to investigate the effect of electric field uniformity factor on breakdown voltage enhancement with dielectric barrier in different structures. The impact of different parameters such as inter-electrodes gap, shape of electrodes, and dielectric materials on the break-down voltage are investigated with simulations and experiments for applied ac and dc voltages. Simulation studies and experimental results illustrate the effectiveness of dielectric barrier in the system.

Agent-Based Distributed Control Schemes for Distributed Energy Storage Systems Under Cyber Attacks

In this paper, the ratios of the required power exchange by the distributed energy storage systems (DESSs) to their power capacity/maximum allowed power for charging or discharging operations are used as information to be exchanged among different battery agents associated with respective to DESSs. First, a fuzzy logic-based information deviation detection scheme is proposed for detection of the effects of cyber-attacks on the information. Two distributed control schemes, based on leader-follower distributed control schemes, are proposed to decide the power exchange by DESS under cyber-attack scenarios. A consensus-based leader-follower distributed control scheme under cyber-attacks, with an arbitrary topology, is proposed while incorporating information deviation detection scheme. Furthermore, a novel agent-based secure distributed optimal control scheme is proposed for charging and discharging of distributed energy storage systems. Linear quadratic regulator-based distributed optimal control scheme is incorporated in this scheme. In both proposed control schemes, the information deviation of agents is monitored and, based on their information deviations, the control actions are taken to ensure agents’ information convergence. The electricity consumption data of a practical medium-voltage distribution system is used to validate the effectiveness of the proposed control schemes. Both control schemes are demonstrated to ensure peak shaving operations in the power distribution system, which may consist of an unreliable communication network, by DESSs.

Aberration detection in electricity consumption using clustering technique

Purpose – This paper aims to detect abnormal energy uses which relate to undetected consumption, thefts, measurement errors, etc. The detection of irregular power consumption, with variation in irregularities, helps the electric utilities in planning and making strategies to transfer reliable and efficient electricity from generators to the end-users. Abnormal peak load demand is a kind of aberration that needs to be detected. Design/methodology/approach – This paper proposes a Density-Based Micro Spatial Clustering of Applications with Noise (DBMSCAN) clustering algorithm, which is implemented for identification of ranked irregular electricity consumption and occurrence of peak and valley loads. In the proposed algorithm, two parameters, a and s, are introduced, and, on tuning of these parameters, after setting of global parameters, a varied number of micro-clusters and ranked irregular consumptions, respectively, are obtained. An approach is incorporated with the introduction of a new term Irregularity ...