Ant Colony Optimization Algorithm for Electrical Power Systems Applications

Optimization has been an active area of research for several decades. As many real-world optimization problems become increasingly complex, better optimization algorithms are always needed. Recently, meta-heuristic global optimization algorithms have become a popular choice for solving complex and intricate problems, which are otherwise difficult to solve by traditional methods. This chapter reviews the recent applications of ant colony optimization (ACO) algorithm in the field of electrical power systems. Also, the progress of the ACO algorithm and its recent developments are discussed. This chapter covers the aspects like (1) basics of ACO algorithm, (2) progress of ACO algorithm, (3) classification of electrical power system applications, and (4) future of ACO for modern power systems application.

Introduction to Smart Grid and Micro-Grid Systems

This chapter describes the upcoming technology for electrical power systems that gives the appropriate solution for the integration of the distributed energy resources. In this chapter, different categories of smart grids have been classified, and the advantages, weakness, and opportunities of each one, are given in addition to determining its own operating conditions. Micro-grids are the most common kind of smart grid. It has been classified under different criteria, such as architecture with different topology (connected mode, island mode, etc.) and demand criteria (simple micro grids, multi-DG, utility) and by capacity into simple micro-grid, corporate micro-grid, and independent micro-grid, and by AC/DC type to DC micro-grids, AC micro-grids, Hybrid micro-grids. Finally, most familiar Micro-grid components have been discussed such as an energy management system along with several types of control and communication systems in addition to the economic study of a micro-grids.

An Optimal Photovoltaic Conversion System for Future Smart Grids

Smart grid technology is the key for a reliable and efficient use of distributed energy resources. Amongst all the renewable sources, solar power takes the prominent position due to its availability in abundance. In this chapter, the authors present smart grid infrastructure issues and integrating solar PV-sourced electricity in the smart grid. Smart grid has many features, including reliability, flexibility on network topology, efficiency, sustainability, and market-enabling. The authors select a photovoltaic active power line conditioner as a case study. This line conditioner is a device designed to extract the maximum power of a photovoltaic (PV) system and to compensate the nonlinear and unbalanced loads of the electrical power systems. The performance of the PV conditioner with the neuro-fuzzy control designed has been analyzed through a simulation platform.

Applications of Big Data and AI in Electric Power Systems Engineering

The production, transmission, and distribution of energy can only be made stable and continuous by detailed analysis of the data. The energy demand needs to be met by a number of optimization algorithms during the distribution of the generated energy. The pricing of the energy supplied to the users and the change for investments according to the demand hours led to the formation of energy exchanges. This use costs varies for active or reactive powers. All of these supply-demand and pricing plans can only be achieved by collecting and analyzing data at each stage. In the study, an electrical power line with real parameters was modeled and fault scenarios were created, and faults were determined by artificial intelligence methods. In this study, both the power flow of electrical power systems and the methods of meeting the demands were investigated with big data, machine learning, and artificial neural network approaches.

Determine the Optimum Efficiency of Transformer Cores Using Comparative Study Method

The transformer is one of the most discussed and important components of electrical power systems because of its reliability, durability and energy conversion capability. It is also useful in load sharing, which reduces system burden, but is also responsible for a sufficient number of losses, as it is used in different types of electric appliances that require voltage conversion. The no-load losses of transformers have gained much attention from research perspective because of its operating cost throughout its lifetime. Many studies were carried out to achieve the highest possible efficiency, decreasing certain losses by using different methods and materials. However, the local market in Pakistan is far behind in the field of efficient core material manufacturing of transformers, which is why consumers are unable to obtain efficient electric appliances. Due to these loss-making appliances, the overall residential load increases and the consumers are charged with heavy electricity bills. This proposed study discusses core losses, different core comparisons, T/F efficiency and advancement in the core material. To accomplish a core comparison, two locally available core materials are used to fabricate two different T/F, and some tests such as open-circuit and short-circuit tests are performed to discover their losses, thermal degradation, and output efficiencies.

Application of Marine Predator Algorithm in Solving the Problem of Directional Overcurrent Relay in Electrical Power System

In electrical power systems, directional overcurrent relay (DOCR) coordination is assumed to be an essential component of the system for protection purposes. To diminish and reduce power losses, the coordination between these relays ought to be kept at an ideal value to minimalize the overall operating time of all primary-relay shortcoming situations. The coordination of DOCR is a complex and profoundly compelling nonlinear problem. The objective function is to minimalize the overall total operating time of all essential relays to minimize inordinate breakdown and interference. Coordination is performed using the marine predator algorithm (MPA), inspired by a widespread foraging strategy, namely Lévy and Brownian movements, to search for global optimal solutions in order to resolve the DOCRs coordination issue. The results acquired from MPA are equated with other state-of-the-art algorithms, and it was observed that the proposed algorithm outperforms other algorithms.