Electrical energy storage and Smart Grid technologies to integrate the next generation of Renewable Power Systems

The growth of renewable power sources, distributed generation and the potential for alternative fuelled modes of transport such as electric vehicles has led to concerns over the ability of existing grid systems to facilitate such diverse portfolio mixes in already congested power systems. Internationally the growth in renewable energy sources is driven by government policy targets associated with the uncertainties of fossil fuel supplies, environmental issues and a move towards energy independence. Power grids were traditionally designed as vertically integrated centrally managed entities with fully dispatchable generating plant. Renewable power sources, distributed generation and alternative fuelled vehicles will place these power systems under additional stresses and strains due to their different operational characteristics. Energy storage and smart grid technologies are widely proposed as the tools to integrate these future diverse portfolio mixes within the more conventional power systems. The choice in these technologies is determined not only by their location on the grid system, but by the diversification in the power portfolio mix, the electricity market and the operational demands. This paper presents a high level technical and economic overview of the role and relevance of electrical energy storage and smart grid technologies in the next generation of renewable power systems.

The Impact of Regulation on a Firm's Incentives to Invest in Emergent Smart Grid Technologies

This paper analyzes the implementation of new technologies in network industries through the development of a suitable regulatory scheme. The analysis focuses on Smart Grid (SG) technologies which, among others benefits, could save operational costs and reduce the need for further conventional investments in the grid. In spite of the benefits that may result from their implementation, the adoption of SGs by network operators can be hampered by the uncertainties surrounding actual performances. A decision model has been developed to assess the firms' incentives to invest in "smart" technologies under different regulatory schemes. The model also enables testing the impact of uncertainties on the reduction of operational costs, and of conventional investments. Under certain circumstances, it may be justified to support the development and early deployment of emerging innovations that have a high potential to ameliorate the efficiency of the electricity system, but whose adoption faces many uncertainties.

Harmonic Current Injection based Powerline Communication Method for Grid Connected Single Phase Inverters in Domestic Microgrids

The following paper presents a Powerline Communication (PLC) Method for Single Phase interfaced inverters in domestic microgrids. The PLC method is based on the injection of a repeating sequence of a specific harmonic, which is then modulated on the fundamental component of the grid current supplied by the inverters to the microgrid. The power flow and information exchange are simultaneously accomplished by the grid interacting inverters based on current programmed vector control, hence there is no need for dedicated hardware. Simulation results have been shown for inter-inverter communication under different operating conditions to propose the viability. These simulations have been experimentally validated and the corresponding results have also been presented in the paper.

Impact of Cyber-Security Issues on Smart Grid

Greater complexity and interconnectivity across systems embracing Smart Grid technologies has meant that cyber-security issues have attracted significant attention. This paper describes pertinent cyber-security requirements, in particular cyber attacks and countermeasures which are critical for reliable Smart Grid operation. Relevant published literature is presented for critical aspects of Smart Grid cyber-security, such as vulnerability, interdependency, simulation, and standards. Furthermore, a preliminary study case is given which demonstrates the impact of a cyber attack which violates the integrity of data on the load management of real power system. Finally, the paper proposes future work plan which focuses on applying intrusion detection and prevention technology to address cyber-security issues. This paper also provides an overview of Smart Grid cyber-security with reference to related cross-disciplinary research topics.

Otimização energética em redes óticas de próxima geração Flex-grid vs Fixed-grid

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia de Eletrónica e Telecomunicações

Grid computing solutions for distributed repositories of protein folding and unfolding simulations

The P-found protein folding and unfolding simulation repository is designed to allow scientists to perform analyses across large, distributed simulation data sets. There are two storage components in P-found: a primary repository of simulation data and a data warehouse. Here we demonstrate how grid technologies can support multiple, distributed P-found installations. In particular we look at two aspects, first how grid data management technologies can be used to access the distributed data warehouses; and secondly, how the grid can be used to transfer analysis programs to the primary repositories --- this is an important and challenging aspect of P-found because the data volumes involved are too large to be centralised. The grid technologies we are developing with the P-found system will allow new large data sets of protein folding simulations to be accessed and analysed in novel ways, with significant potential for enabling new scientific discoveries.

P-found: grid-enabling distributed repositories of protein folding and unfolding simulations for data mining

The P-found protein folding and unfolding simulation repository is designed to allow scientists to perform data mining and other analyses across large, distributed simulation data sets. There are two storage components in P-found: a primary repository of simulation data that is used to populate the second component, and a data warehouse that contains important molecular properties. These properties may be used for data mining studies. Here we demonstrate how grid technologies can support multiple, distributed P-found installations. In particular, we look at two aspects: firstly, how grid data management technologies can be used to access the distributed data warehouses; and secondly, how the grid can be used to transfer analysis programs to the primary repositories — this is an important and challenging aspect of P-found, due to the large data volumes involved and the desire of scientists to maintain control of their own data. The grid technologies we are developing with the P-found system will allow new large data sets of protein folding simulations to be accessed and analysed in novel ways, with significant potential for enabling scientific discovery.

Simulation in NS-2 of DNP3 protocol encapsulated over TCP/IP in smart grid applications

In dealing with computer networks, these allow the flow of information through the resources of various equipment's. This work describes the implementation through the encapsulation of Protocol DNP3, usually employed in Smart Grid communication, in a simulator of discrete events. The NS-2 is a simulator in open source of network events, that facilitate the development of communication networks scenarios considering the protocols involved, in wireless or wired technologies. The objective of this work is to develop the DNP3 protocol encapsulation over a TCP/IP in the in the discrete event Simulator NS-2, allowing an analysis of behavior of a middle or large network sized in Smart Grid applications. © 2013 IEEE.

Optimising market share and profit margin:SMDP-based tariff pricing under the smart grid paradigm

Smart grid technologies have given rise to a liberalised and decentralised electricity market, enabling energy providers and retailers to have a better understanding of the demand side and its response to pricing signals. This paper puts forward a reinforcement-learning-powered tool aiding an electricity retailer to define the tariff prices it offers, in a bid to optimise its retail strategy. In a competitive market, an energy retailer aims to simultaneously increase the number of contracted customers and its profit margin. We have abstracted the problem of deciding on a tariff price as faced by a retailer, as a semi-Markov decision problem (SMDP). A hierarchical reinforcement learning approach, MaxQ value function decomposition, is applied to solve the SMDP through interactions with the market. To evaluate our trading strategy, we developed a retailer agent (termed AstonTAC) that uses the proposed SMDP framework to act in an open multi-agent simulation environment, the Power Trading Agent Competition (Power TAC). An evaluation and analysis of the 2013 Power TAC finals show that AstonTAC successfully selects sell prices that attract as many customers as necessary to maximise the profit margin. Moreover, during the competition, AstonTAC was the only retailer agent performing well across all retail market settings.

A flexible protection scheme for an islanded Multi-Microgrid

Multi-Microgrids (MMGs) have been proposed to connect distributed generators (DG), microgrids (MG), and medium-voltage (MV) loads with the distribution system. A flexible protection scheme that enables an islanded MMG to continue operation during fault conditions is yet to be developed. In this paper, a protection scheme for an islanded MMG that utilises MG controllers and communication links is proposed. The MMG model used includes two MGs connected to the distribution system. Each MG consists of diesel, wind, and photovoltaic (PV) microsources. The effectiveness of the proposed protection scheme is evaluated by simulation.

An improved protection strategy for microgrids

Microgrids (MG) enable the integration of low capacity renewable energy resources with distribution systems. A recently proposed protection scheme for MGs utilising undervoltage, High Impedance Fault (HIF) detection, directional protection modules, and communication links significantly reduces the fault clearing time compared to previous schemes. In this paper, the effect of replacing undervoltage protection with differential protection in a scheme that also contains HIF and directional protection modules is studied. The MG model used in this study includes a diesel, wind, and two photovoltaic (PV) microsources. The alternative protection schemes are evaluated by simulation. It is found that the protection scheme consisting of differential, HIF detection, and directional protection modules is more effective compared to the alternative in protecting the MG from some fault conditions such as the phase-A-to-ground, phase-B-to-C, and phase-B-to-C-to-ground.

Multi-agent systems for modeling high penetration photovoltaic system impacts in distribution networks

This paper reviews the use of multi-agent systems to model the impacts of high levels of photovoltaic (PV) system penetration in distribution networks and presents some preliminary data obtained from the Perth Solar City high penetration PV trial. The Perth Solar City trial consists of a low voltage distribution feeder supplying 75 customers where 29 consumers have roof top photovoltaic systems. Data is collected from smart meters at each consumer premises, from data loggers at the transformer low voltage (LV) side and from a nearby distribution network SCADA measurement point on the high voltage side (HV) side of the transformer. The data will be used to progressively develop MAS models.

Consumer phase identification in a three phase unbalanced LV distribution network

A new technique is presented for automatically identifying the phase connection of domestic customers. Voltage information from a reference three phase house is correlated with voltage information from other customer electricity meters on the same network to determine the highest probability phase connection. The techniques are purely based upon a time series of electrical voltage measurements taken by the household smart meters and no additional equipment is required. The method is demonstrated using real smart meter datasets to correctly identify the phase connections of 75 consumers on a low voltage distribution feeder.