Classical and Recent Aspects of Power System Optimization

Ahmed F. Zobaa, Shady Abdel Aleem, Almoataz Youssef Abdelaziz

• Publisher: Academic Press
• Year: 2018
• Print ISBN: 9780128124413
• eBook ISBN: 9780128124420
• Topic: Technology & Engineering
• Subtopic: Electrical Engineering & Telecommunications
• Index: Technology & Engineering

Classical and Recent Aspects of Power System Optimization presents conventional and meta-heuristic optimization methods and algorithms for power system studies. The classic aspects of optimization in power systems, such as optimal power flow, economic dispatch, unit commitment and power quality optimization are covered, as are issues relating to distributed generation sizing, allocation problems, scheduling of renewable resources, energy storage, power reserve based problems, efficient use of smart grid capabilities, and protection studies in modern power systems. The book brings together innovative research outcomes, programs, algorithms and approaches that consolidate the present state and future challenges for power.- Analyzes and compares several aspects of optimization for power systems which has never been addressed in one reference- Details real-life industry application examples for each chapter (e.g. energy storage and power reserve problems)- Provides practical training on theoretical developments and application of advanced methods for optimum electrical energy for realistic engineering problems

Chapter 1

Optimization Methods Applied to Power Systems: Current Practices and Challenges

Jeremy Lin⁎; Fernando Magnago^†; Juan Manuel Alemany^{† ⁎} DNV-GL Energy Advisory Group, Dallas, TX, United States
^† National University of Rio Cuarto, Rio Cuarto, Argentina

Abstract

Optimization tools applied in power system areas are becoming increasingly essential to support the complex task of efficiently providing electricity to the grid. The power system areas where these optimization tools are needed include power system operation, analysis, scheduling, and energy management. The problems in these areas require the study of the objective function and constraints in different ways. This chapter is primarily focused on the review of the various optimization methods and their applications to these types of problems. Furthermore, the most pressing challenges emerging in this area are also discussed.

This chapter is intended for both first-year graduate students and senior-year undergraduate students who would like to improve their knowledge of power system optimization and who would like to study the fundamental and advanced topics related to power system optimization tools.

A good understanding of these fundamental concepts and the emerging challenges in this area is necessary to further enhance the knowledge of the complex operation of power systems and electricity markets.

Keywords

Unit commitment; Economic dispatch; Optimal power flow; Fuel scheduling; Deterministic methods; Decomposition methods; Stochastic programming

1 Introduction

Planning and decision-making in energy, in general, involve the allocation of a large amount of resources which significantly impacts all the actors in an economy. The main objective of planning in power systems is to define an appropriate strategy with regards to generation and transmission to efficiently utilize the system. In a general framework for energy efficiency, optimization applied to the efficient use of electric resources is essential. In the case of power systems, applied optimization is related to the planning and scheduling of the resources to aid in the system operation [1].

In this chapter, we will begin by outlining the key problems in power systems that are naturally suitable for applications of classical optimization methods to solve these problems. For example, unit commitment (UC), economic dispatch (ED), and optimal power flow (OPF) are three key problems which are critical to the economically efficient operation of the power system.

UC is a large-scale, nonconvex, mixed-integer programming problem which requires effective and efficient numerical methods to obtain its solution. ED is a step that needs to be done after completing the UC process, while the OPF solves the ED by adding additional constraints to the optimization problem [2].

In all these activities, the optimization methods emanating from the operations research field play a significant role in the decision-making process associated with UC, ED, and OPF. After outlining these problems, the optimization methods that are currently employed in solving these problems are presented. Mathematically, the optimization methods employed in these formulations are linear programming, mixed-integer programming, decomposition methods and stochastic approaches. These methods constitute a core set of optimization methods that are currently applied [3].

After presenting these optimization problems and solution methods, we will attempt to present some of the emerging challenges we face in current and future power systems. It is believed that the future grid will face some challenging developments such as the smart grid, microgrid, distributed energy resources (DER), and massive amounts of renewable energy sources (RES), to name just a few. These new developments will pose very different kinds of problems to the existing power systems.

In the final section of the chapter, we will present some of these challenges in detail and discuss the optimization methods currently being used to solve these problems. The problems described will be focused on practical applications to the real large-scale systems, including time-coupling constraints, network constraints, size and variation of the control variables, or stochastic nature of renewable resources. Because these are the frontier areas of research with uncertain results, we will also provide some speculations in terms of applications of potential optimization methods. Some innovations that incorporate energy efficiency in to the planning and operation of power systems with high renewables penetration will also be described. New concepts and techniques necessary to manage uncertainty in the models and algorithms that are commonly developed for deterministic conditions will be included as well.

2 Key Scheduling Problems in Power System Operation

From a general perspective, the power system economic operation involves the operation of generation, transmission, and distribution subsystems with the objective of operating these subsystems efficiently and fulfilling the requirement of maintaining the balance between generation and load at all times. Moreover, the voltage at each system node and the system frequency must remain within prespecified limits. This combination of economic and technical requireme...

Table of contents

• Cover image
• Title page
• Table of Contents
• Copyright
• Dedication
• Contributors
• Preface
• Chapter 1: Optimization Methods Applied to Power Systems: Current Practices and Challenges
• Chapter 2: Application of Robust Optimization Method to Power System Problems
• Chapter 3: Application of New Fast, Efficient-Self adjusting PSO-Search Algorithms in Power Systems' Studies
• Chapter 4: Implementation of Radial Movement Optimization (RMO) Algorithm for Solving Economic Dispatch and Fixed Head Hydrothermal Generation Scheduling
• Chapter 5: An Intelligent Approach Based on Metaheuristic for Generator Maintenance Scheduling
• Chapter 6: Decomposition Methods for Distributed Optimal Power Flow: Panorama and Case Studies of the DC Model
• Chapter 7: Optimal Power Flow Using Recent Optimization Techniques
• Chapter 8: Optimal Conductor Selection of Radial Distribution Feeders: An Overview and New Application Using Grasshopper Optimization Algorithm
• Chapter 9: Classical and Recent Aspects of Active Power Filters for Power Quality Improvement
• Chapter 10: Optimization-Based Power Capacitor Model Parameterization for Decision Support in Power Distribution Systems
• Chapter 11: Two-Level Multidimensional Enhanced Melody Search Algorithm for Dynamic Planning of MV Open-Loop Distribution Networks
• Chapter 12: Demand-Side Management—Recent Aspects and Challenges of Optimization for an Efficient and Robust Demand-Side Management
• Chapter 13: Demand-Side Management in Micro-Grids and Distribution Systems: Handling System Uncertainties and Scalabilities
• Chapter 14: Impact of Integrated Optimization of Independent Energy Carriers on Power Systems
• Chapter 15: Optimal Management of Hydrothermal-Based Micro-Grids Employing Robust Optimization Method
• Chapter 16: Geomagnetically Induced Currents: A Threat to Modern Power Systems
• Chapter 17: Application of Evolutionary Algorithm for Multiobjective Transformer Design Optimization
• Chapter 18: A Multiobjective Teaching-Learning Algorithm for Power Losses Reduction in Power Systems
• Index