Design Simulation of Improvement of Voltage Profile and Loss Minimization by Efficient Placement of Distributed Generation in Grid Connected System

Electricity consumption is rapidly increasing, and the gap between generation and load is widening. The mismatch between demand and load causes a range of problems, including failure, low power, and, in certain cases, blackout. These issues will be solved by including Distributed Generation (DG) into the system. For maximum dependability, technological and economic benefits, and optimal size and capabilities of distributed generators, the  proper  distribution of  power systems,  kind of generating equipment, number of units, and so on are critical. Among these concerns, the difficulty of placing DG units in the best location and size is critical. Inadequate DG resource distribution to the power system will result in increased power losses. This problem is solved using genetic algorithms. For the conventional 15 bus radial distribution system, the load flow is generated using the backward forward sweep method. Load flow is used to assess the impact of DG size and location on system losses. Machine losses rise as a result of inappropriate DG allocation. As a result, the genetic algorithm (GA), an evolutionary process, is being researched, and an algorithm is being created to discover the appropriate size and position of the distributed generation unit in a radial distribution system. The overall active power losses are reduced, and the voltage profile is improved due to proper DG allocation. Introduces a multi-objective feature that accounts for active power losses, voltage changes, and DG costs, with each variable given a weight. Voltage limits, active power loss constraints, and DG size limitations all affect objective feature minimization. This method is utilized on the conventional 15 bus radial distribution system

A Survey on Cryptography Key Management Schemes for Smart Grid

A Smart grid is a modern electricity delivery system. It is an integration of energy systems and other necessary elements including traditional upgrades and new grid technologies with renewable generation and increased consumer storage. It uses information and communication technology (ICT) to operate, monitor and control data between the generation source and the end user. Smart grids have duplex power flow and communication to achieve high efficiency, reliability, environmental, economics, security and safety standards. However, along with unique facilities, smart grids face security challenges such as access control, connectivity, fault tolerance, privacy, and other security issues. Cyber-attacks, in the recent past, on critical infrastructure including smart grids have highlighted security as a major requirement for smart grids. Therefore, cryptography and key management are necessary for smart grids to become secure and realizable. Key management schemes are processes of key organizational frameworks, distribution, generation, refresh and key storage policies. Currently, several secure schemes, related to key management for smart grid have been proposed to achieve end-to-end secure communication. This paper presents a comprehensive survey and discussion on the current state of the key management of smart grids

Key Management Scheme for Smart Grid

A Smart Grid (SG) is a modern electricity supply system. It uses information and communication technology (ICT) to run, monitor and control data between the generation source and the end user. It comprises a set of technologies that uses sensing, embedded processing and digital communications to intelligently control and monitor an electricity grid with improved reliability, security, and efficiency. SGs are classified as Critical Infrastructures. In the recent past, there have been cyber-attacks on SGs causing substantial damage and loss of services. A recent cyber-attack on Ukraine's SG caused over 2.3 million homes to be without power for around six hours. Apart from the loss of services, some portions of the SG are yet to be operational, due to the damage caused. SGs also face security challenges such as confidentiality, availability, fault tolerance, privacy, and other security issues. Communication and networking technologies integrated into the SG require new and existing security vulnerabilities to be thoroughly investigated. Key management is one of the most important security requirements to achieve data confidentiality and integrity in a SG system. It is not practical to design a single key management scheme/framework for all systems, actors and segments in the smart grid, since the security requirements of various sub-systems in the SG vary. We address two specific sub-systems categorised by the network connectivity layer – the Home Area Network (HAN) and the Neighbourhood Area Network (NAN). Currently, several security schemes and key management solutions for SGs have been proposed. However, these solutions lack better security for preventing common cyber-attacks such as node capture attack, replay attack and Sybil attack. We propose a cryptographic key management scheme that takes into account the differences in the HAN and NAN segments of the SG with respect to topology, authentication and forwarding of data. The scheme complies with the overall performance requirements of the smart grid. The proposed scheme uses group key management and group authentication in order to address end-to-end security for the HAN and NAN scenarios in a smart grid, which fulfils data confidentiality, integrity and scalability requirements. The security scheme is implemented in a multi-hop sensor network using TelosB motes and ZigBee OPNET simulation model. In addition, replay attack, Sybil attack and node capture attack scenarios have been implemented and evaluated in a NAN scenario. Evaluation results show that the scheme is resilient against node capture attacks and replay attacks. Smart Meters in a NAN are able to authenticate themselves in a group rather than authenticating one at a time. This significant improvement over existing schemes is discussed with comparisons with other security schemes