Optimum design and analysis study of stand-alone residential solar PV microgrid

Today’s power system network has become more complex and it has more responsibilities and challenges to provide secure, reliable and quality energysupply to the communities. A small entity of electrical network known as Microgrid (MG) is more popular nowadays to enhance reliablity and secure level of energy supply, in case of any energy crisis in the utility network. The MG can also provide clean energy supply by integrating renewable energy sources effectively. TheMG with small scale solar photovoltaic (PV) power system is more suitable to provide reliable and clean energy supply for remote or urban communities in residential level. This paper presents the basic analysis study of stand-alone solar photovoltaic (PV) MG power system which has been developed with the aid of Matlab - Simulink software, on the basis of residential load profile and solar exposure level in a particular area of Geelong, Victoria State. The simulation result depicts the control behavior of MG power system with optimum sizing of PV (4.385 kW)and battery storage (480Ah/48V) facility, fulfills daily energy needs in residential load level. This study provides a good platform to develop an effective and reliable stand-alone MG power system for the remote communities in the near future.

Agent-based smart grid protection and security

The vision of a smart grid is to provide a modern, resilient, and secure electric power grid as it boasts up with a highly reliable and efficient environment through effective use of its information and communication technology (ICT). Generally, the control and operation of a smart grid which integrate the distributed energy resources (DERs) such as, wind power, solar power, energy storage, etc., largely depends on a complex network of computers, softwares, and communication infrastructure superimposed on its physical grid architecture facilitated with the deployment of intelligent decision support system applications. In recent years, multi-agent system (MAS) has been well investigated for wide area power system applications and specially gained a significant attention in smart grid protection and security due to its distributed characteristics. In this chapter, a MAS framework for smart grid protection relay coordination is proposed, which consists of a number of intelligent autonomous agents each of which are embedded with the protection relays. Each agent has its own thread of control that provides it with a capability to operate the circuit breakers (CBs) using the critical clearing time (CCT) information as well as communicate with each other through high speed communication network. Besides physical failure, since smart grid highly depends on communication infrastructure, it is vulnerable to several cyber threats on its information and communication channel. An attacker who has knowledge about a certain smart grid communication framework can easily compromise its appliances and components by corrupting the information which may destabilize a system results a widespread blackout. To mitigate such risk of cyber attacks, a few innovative counter measuring techniques are discussed in this chapter.

A multi-agent approach for enhancing transient stability of smart grids

Transient stability, an important issue to avoid the loss of synchronous operation in power systems, can be achieved through proper coordination and operation of protective devices within the critical clearing time (CCT). In view of this, the development of an intelligent decision support system is useful for providing better protection relay coordination. This paper presents an intelligent distributed agent-based scheme to enhance the transient stability of smart grids in light of CCT where a multi-agent framework (MAF) is developed and the agents are represented in such a way that they are equipped with protection relays (PRs). In addition to this, an algorithm is developed which assists the agents to make autonomous decision for controlling circuit breakers (CBs) independently. The proposed agents are responsible for the coordination of protection devices which is done through the precise detection and isolation of faults within the CCT. The agents also perform the duty of reclosing CBs after the clearance of faults. The performance of the proposed approach is demonstrated on a standard IEEE 39-bus test system by considering short-circuit faults at different locations under various load conditions. To further validate the suitability of the proposed scheme a benchmark 16-machine 68-bus power system is also considered. Simulation results show that MAF exhibits full flexibility to adapt the changes in system configurations and increase the stability margin for both test systems.

A review on artificial intelligence based load demand forecasting techniques for smart grid and buildings

Electrical load forecasting plays a vital role in order to achieve the concept of next generation power system such as smart grid, efficient energy management and better power system planning. As a result, high forecast accuracy is required for multiple time horizons that are associated with regulation, dispatching, scheduling and unit commitment of power grid. Artificial Intelligence (AI) based techniques are being developed and deployed worldwide in on Varity of applications, because of its superior capability to handle the complex input and output relationship. This paper provides the comprehensive and systematic literature review of Artificial Intelligence based short term load forecasting techniques. The major objective of this study is to review, identify, evaluate and analyze the performance of Artificial Intelligence (AI) based load forecast models and research gaps. The accuracy of ANN based forecast model is found to be dependent on number of parameters such as forecast model architecture, input combination, activation functions and training algorithm of the network and other exogenous variables affecting on forecast model inputs. Published literature presented in this paper show the potential of AI techniques for effective load forecasting in order to achieve the concept of smart grid and buildings.

Nonlinear excitation control of synchronous generators based on adaptive backstepping method

n this paper, the design of a nonlinear excitation control of a synchronous generator is presented where the generator is connected to a single machine infinite bus (SMIB) system. An adaptive backstepping method is used to design the excitation controller with an objective of enhancing the overall dynamic stability of the SMIB system under different contingencies. In this paper, two types of contingencies are considered- i) unknown parameters and physical quantities during the controller design process and ii) controller performance evaluation under different system configurations such as three-phase short circuit faults. The adaption law, which is mainly based on the formulation of Lyapunov function, is used to estimate the unknown parameters which guarantee the convergence of different physical quantities of synchronous generators, e.g., the relative speed, terminal voltage, etc. The effectiveness of the proposed scheme is evaluated under different system configurations as mentioned in the second contingency and compared to that of an existing adaptive backstepping controller and a conventional power system stabilizer (PSS). Simulation results demonstrate the superiority of the proposed control scheme over the existing controllers.

Integration of renewable generation uncertainties into stochastic unit commitment considering reserve and risk: a comparative study

The uncertainties of renewable energy have brought great challenges to power system commitment, dispatches and reserve requirement. This paper presents a comparative study on integration of renewable generation uncertainties into SCUC (stochastic security-constrained unit commitment) considering reserve and risk. Renewable forecast uncertainties are captured by a list of PIs (prediction intervals). A new scenario generation method is proposed to generate scenarios from these PIs. Different system uncertainties are considered as scenarios in the stochastic SCUC problem formulation. Two comparative simulations with single (E1: wind only) and multiple sources of uncertainty (E2: load, wind, solar and generation outages) are investigated. Five deterministic and four stochastic case studies are performed. Different generation costs, reserve strategies and associated risks are compared under various scenarios. Demonstrated results indicate the overall costs of E2 is lower than E1 due to penetration of solar power and the associated risk in deterministic cases of E2 is higher than E1. It implies the superimposed effect of uncertainties during uncertainty integration. The results also demonstrate that power systems run a higher level of risk during peak load hours, and that stochastic models are more robust than deterministic ones.

Renewable energy integration : challenges and solutions

This book presents different aspects of renewable energy integration, from the latest developments in renewable energy technologies to the currently growing smart grids. The importance of different renewable energy sources is discussed, in order to identify the advantages and challenges for each technology. The rules of connecting the renewable energy sources have also been covered along with practical examples. Since solar and wind energy are the most popular forms of renewable energy sources, this book provides the challenges of integrating these renewable generators along with some innovative solutions. As the complexity of power system operation has been raised due to the renewable energy integration, this book also includes some analysis to investigate the characteristics of power systems in a smarter way. This book is intended for those working in the area of renewable energy integration in distribution networks.

Integration of electric vehicles for load frequency output feedback H ∞ control of smart grids

This study considers a novel application of electric vehicles (EVs) to quickly help reheated thermal turbine units to provide the stability fluctuated by load demands. A mathematical model of a power system with EVs is first derived. This model contains the dynamic interactions of EVs and multiple network-induced time delays. Then, a dynamic output feedback H∞ controller for load frequency control of power systems with multiple time delays in the control input is proposed. To address the multiple time delays issue, a refined Jensen-based inequality, which encompasses the Jensen inequality, is used to derive less conservative synthesis conditions in terms of tractable linear matrix inequalities. A procedure is given to parameterise an output feedback controller to guarantee stability and H∞ performance of the closed-loop system. Extensive simulations are conducted to validate the proposed control method.

Multi-agent approach for enhancing security of protection schemes in cyber-physical energy systems

This paper presents a distributed multi-agent scheme to detect and identify cyber threats on the protection systems of power grids. The integration of information and communication technologies (ICTs) into existing power grids builds critical cyberphysical energy systems CPESs) in which digital relays are networked cyber-physical components subject to various cyber threats. Cyber attacks on protection systems may mimic real faults, cause component failure, and disable the communication links. Agents utilize both cyber and physical properties to reinforce the detection technique and further distinguish cyber attacks from physical faults. This paper also introduces the problem of secure communicationprotocols and highlights the comparative studies for enhancing thesecurity of the protection systems. The proposed scheme is validatedusing a benchmark power system under various fault and cyber attack scenarios.