State Estimation of Power Using the Whale Optimization Algorithm

In power systems, the process of attaining a better prediction from a set of variables from state variables is called state estimation (SE). These variables consist of magnitudes of bus voltage and the corresponding angles of all the buses. Because of the non-linearity and intricacy of ever-developing power systems, it has become important to apply upgraded techniques for the dissolution and supervision in practical environments. The discussed analysis evaluates the appositeness of a new metaheuristic technique called the whale optimization algorithm (WOA) which is a population-based algorithm, to reduce the measurement errors so as to gauge the optimal point of the power system when some susceptible values are inadequate. WOA displays admirable attainment in global optimization. It employs a bubble-net hunting approach and it mimics the social behaviour of humpback whales to get the best candidate solution. The approach is tested on IEEE-14, IEEE-30, and IEEE-57 bus test systems and the potency is validated by comparison with the biogeography based optimization algorithm (BBO).

Demonstration Study of Voltage Control of DC Grid Using Energy Management System Based DC Applications

This paper is about the development of the real-time direct current (DC) network analysis applications for the operation of DC power systems. The applications are located in the central energy management system (EMS) and provide the operator with the optimal solution for operation in real time. Developed DC applications are not limited by voltage level. Applications can be used at all DC voltage levels such as low voltage, medium voltage and high voltage. A program configuration and sequence for analyzing the DC distribution system are suggested. Algorithms of each program are presented and the differences when compared with the processes of the applications of the existing alternating current (AC) systems are analyzed. The DC grid demonstration site at the Korea Electric Power Corporation (KEPCO) power testing center is introduced. The details of EMS and applications installation are described. The developed DC applications were installed in the EMS of the demonstration site and verification tests have been carried out. The configuration of the test scenario for testing the voltage control of the DC network is described. The voltage control result is analyzed and the measured data and the results of the applications are verified for compatibility by comparing them with the results of an off-line simulation tool. Finally, the future direction of the development of technology for the operation of the DC grid is introduced.

False data injection attacks against state estimation in electric power grids

A power grid is a complex system connecting electric power generators to consumers through power transmission and distribution networks across a large geographical area. System monitoring is necessary to ensure the reliable operation of power grids, and state estimation is used in system monitoring to best estimate the power grid state through analysis of meter measurements and power system models. Various techniques have been developed to detect and identify bad measurements, including interacting bad measurements introduced by arbitrary, nonrandom causes. At first glance, it seems that these techniques can also defeat malicious measurements injected by attackers.

In this article, we expose an unknown vulnerability of existing bad measurement detection algorithms by presenting and analyzing a new class of attacks, called false data injection attacks , against state estimation in electric power grids. Under the assumption that the attacker can access the current power system configuration information and manipulate the measurements of meters at physically protected locations such as substations, such attacks can introduce arbitrary errors into certain state variables without being detected by existing algorithms. Moreover, we look at two scenarios, where the attacker is either constrained to specific meters or limited in the resources required to compromise meters. We show that the attacker can systematically and efficiently construct attack vectors in both scenarios to change the results of state estimation in arbitrary ways. We also extend these attacks to generalized false data injection attacks , which can further increase the impact by exploiting measurement errors typically tolerated in state estimation. We demonstrate the success of these attacks through simulation using IEEE test systems, and also discuss the practicality of these attacks and the real-world constraints that limit their effectiveness.