Establishment of stackable community networks

Uma das áreas de investigação em Telecomunicações de interesse crescente prende-se com os futuros sistemas de comunicações móveis de 4a geração e além destes. Nos últimos anos tem sido desenvolvido o conceito de redes comunitárias, no qual os utilizadores se agregam de acordo com interesses comuns. Estes conceitos têm sido explorados de uma forma horizontal em diferentes camadas da comunicação, desde as redes comunitárias de comunicação (Seattle Wireless ou Personal Telco, p.ex.) até às redes de interesses peer-to-peer. No entanto, estas redes são usualmente vistas como redes de overlay, ou simplesmente redes de associação livre. Na prática, a noção de uma rede auto-organizada, completamente orientada ao serviço/comunidade, integralmente suportada em termos de arquitetura, não existe. Assim este trabalho apresenta uma realização original nesta área de criação de redes comunitárias, com uma arquitetura subjacente orientada a serviço, e que suporta integralmente múltiplas redes comunitárias no mesmo dispositivo, com todas as características de segurança, confiança e disponibilização de serviço necessárias neste tipo de cenários (um nó pode pertencer simultaneamente a mais do que uma rede comunitária). Devido à sua importância para os sistemas de redes comunitárias, foi dado particular atenção a aspetos de gestão de recursos e controlo de acessos. Ambos realizados de uma forma descentralizada e considerando mecanismos dotados de grande escalabilidade. Para isso, é apresentada uma linguagem de políticas que suporta a criação de comunidades virtuais. Esta linguagem não é apenas utilizada para o mapeamento da estrutura social dos membros da comunidade, como para, gerir dispositivos, recursos e serviços detidos pelos membros, de uma forma controlada e distribuída.

Communication between nodes for autonomic and distributed management

Over the last decade, the most widespread approaches for traditional management were based on the Simple Network Management Protocol (SNMP) or Common Management Information Protocol (CMIP). However, they both have several problems in terms of scalability, due to their centralization characteristics. Although the distributed management approaches exhibit better performance in terms of scalability, they still underperform regarding communication costs, autonomy, extensibility, exibility, robustness, and cooperation between network nodes. The cooperation between network nodes normally requires excessive overheads for synchronization and dissemination of management information in the network. For emerging dynamic and large-scale networking environments, as envisioned in Next Generation Networks (NGNs), exponential growth in the number of network devices and mobile communications and application demands is expected. Thus, a high degree of management automation is an important requirement, along with new mechanisms that promote it optimally and e ciently, taking into account the need for high cooperation between the nodes. Current approaches for self and autonomic management allow the network administrator to manage large areas, performing fast reaction and e ciently facing unexpected problems. The management functionalities should be delegated to a self-organized plane operating within the network, that decrease the network complexity and the control information ow, as opposed to centralized or external servers. This Thesis aims to propose and develop a communication framework for distributed network management which integrates a set of mechanisms for initial communication, exchange of management information, network (re) organization and data dissemination, attempting to meet the autonomic and distributed management requirements posed by NGNs. The mechanisms are lightweight and portable, and they can operate in di erent hardware architectures and include all the requirements to maintain the basis for an e cient communication between nodes in order to ensure autonomic network management. Moreover, those mechanisms were explored in diverse network conditions and events, such as device and link errors, di erent tra c/network loads and requirements. The results obtained through simulation and real experimentation show that the proposed mechanisms provide a lower convergence time, smaller overhead impact in the network, faster dissemination of management information, increase stability and quality of the nodes associations, and enable the support for e cient data information delivery in comparison to the base mechanisms analyzed. Finally, all mechanisms for communication between nodes proposed in this Thesis, that support and distribute the management information and network control functionalities, were devised and developed to operate in completely decentralized scenarios.

Dependable wireless real-time communications for open environments

Wireless communication technologies have become widely adopted, appearing in heterogeneous applications ranging from tracking victims, responders and equipments in disaster scenarios to machine health monitoring in networked manufacturing systems. Very often, applications demand a strictly bounded timing response, which, in distributed systems, is generally highly dependent on the performance of the underlying communication technology. These systems are said to have real-time timeliness requirements since data communication must be conducted within predefined temporal bounds, whose unfulfillment may compromise the correct behavior of the system and cause economic losses or endanger human lives. The potential adoption of wireless technologies for an increasingly broad range of application scenarios has made the operational requirements more complex and heterogeneous than before for wired technologies. On par with this trend, there is an increasing demand for the provision of cost-effective distributed systems with improved deployment, maintenance and adaptation features. These systems tend to require operational flexibility, which can only be ensured if the underlying communication technology provides both time and event triggered data transmission services while supporting on-line, on-the-fly parameter modification. Generally, wireless enabled applications have deployment requirements that can only be addressed through the use of batteries and/or energy harvesting mechanisms for power supply. These applications usually have stringent autonomy requirements and demand a small form factor, which hinders the use of large batteries. As the communication support may represent a significant part of the energy requirements of a station, the use of power-hungry technologies is not adequate. Hence, in such applications, low-range technologies have been widely adopted. In fact, although low range technologies provide smaller data rates, they spend just a fraction of the energy of their higher-power counterparts. The timeliness requirements of data communications, in general, can be met by ensuring the availability of the medium for any station initiating a transmission. In controlled (close) environments this can be guaranteed, as there is a strict regulation of which stations are installed in the area and for which purpose. Nevertheless, in open environments, this is hard to control because no a priori abstract knowledge is available of which stations and technologies may contend for the medium at any given instant. Hence, the support of wireless real-time communications in unmanaged scenarios is a highly challenging task. Wireless low-power technologies have been the focus of a large research effort, for example, in the Wireless Sensor Network domain. Although bringing extended autonomy to battery powered stations, such technologies are known to be negatively influenced by similar technologies contending for the medium and, especially, by technologies using higher power transmissions over the same frequency bands. A frequency band that is becoming increasingly crowded with competing technologies is the 2.4 GHz Industrial, Scientific and Medical band, encompassing, for example, Bluetooth and ZigBee, two lowpower communication standards which are the base of several real-time protocols. Although these technologies employ mechanisms to improve their coexistence, they are still vulnerable to transmissions from uncoordinated stations with similar technologies or to higher power technologies such as Wi- Fi, which hinders the support of wireless dependable real-time communications in open environments. The Wireless Flexible Time-Triggered Protocol (WFTT) is a master/multi-slave protocol that builds on the flexibility and timeliness provided by the FTT paradigm and on the deterministic medium capture and maintenance provided by the bandjacking technique. This dissertation presents the WFTT protocol and argues that it allows supporting wireless real-time communication services with high dependability requirements in open environments where multiple contention-based technologies may dispute the medium access. Besides, it claims that it is feasible to provide flexible and timely wireless communications at the same time in open environments. The WFTT protocol was inspired on the FTT paradigm, from which higher layer services such as, for example, admission control has been ported. After realizing that bandjacking was an effective technique to ensure the medium access and maintenance in open environments crowded with contention-based communication technologies, it was recognized that the mechanism could be used to devise a wireless medium access protocol that could bring the features offered by the FTT paradigm to the wireless domain. The performance of the WFTT protocol is reported in this dissertation with a description of the implemented devices, the test-bed and a discussion of the obtained results.

Desenvolvimento de um ambiente virtual de aprendizagem em regime de b-learning num curso de educação e formação de operadores de informática

Trabalho de projeto de mestrado, Educação (Área de Especialização em Educação e Tecnologias Digitais), Universidade de Lisboa, Instituto de Educação, 2014

Virtual power producers integration into MASCEM

All over the world Distributed Generation is seen as a valuable help to get cleaner and more efficient electricity. Under this context distributed generators, owned by different decentralized players can provide a significant amount of the electricity generation. To get negotiation power and advantages of scale economy, these players can be aggregated giving place to a new concept: the Virtual Power Producer. Virtual Power Producers are multi-technology and multi-site heterogeneous entities. Virtual Power Producers should adopt organization and management methodologies so that they can make Distributed Generation a really profitable activity, able to participate in the market. In this paper we address the integration of Virtual Power Producers into an electricity market simulator –MASCEM – as a coalition of distributed producers.

Energy resource scheduling in a real distribution network managed by several virtual power players

Smart Grids (SGs) appeared as the new paradigm for power system management and operation, being designed to integrate large amounts of distributed energy resources. This new paradigm requires a more efficient Energy Resource Management (ERM) and, simultaneously, makes this a more complex problem, due to the intensive use of distributed energy resources (DER), such as distributed generation, active consumers with demand response contracts, and storage units. This paper presents a methodology to address the energy resource scheduling, considering an intensive use of distributed generation and demand response contracts. A case study of a 30 kV real distribution network, including a substation with 6 feeders and 937 buses, is used to demonstrate the effectiveness of the proposed methodology. This network is managed by six virtual power players (VPP) with capability to manage the DER and the distribution network.

Remuneration and tariffs in the context of virtual power players

Power systems have been through deep changes in recent years, namely with the operation of competitive electricity markets in the scope and the increasingly intensive use of renewable energy sources and distributed generation. This requires new business models able to cope with the new opportunities that have emerged. Virtual Power Players (VPPs) are a new player type which allows aggregating a diversity of players (Distributed Generation (DG), Storage Agents (SA), Electrical Vehicles, (V2G) and consumers), to facilitate their participation in the electricity markets and to provide a set of new services promoting generation and consumption efficiency, while improving players` benefits. A major task of VPPs is the remuneration of generation and services (maintenance, market operation costs and energy reserves), as well as charging energy consumption. This paper proposes a model to implement fair and strategic remuneration and tariff methodologies, able to allow efficient VPP operation and VPP goals accomplishment in the scope of electricity markets.

Energy and reserve provision dispatch considering distributed generation and demand response

In competitive electricity markets with deep concerns at the efficiency level, demand response programs gain considerable significance. In the same way, distributed generation has gained increasing importance in the operation and planning of power systems. Grid operators and utilities are taking new initiatives, recognizing the value of demand response and of distributed generation for grid reliability and for the enhancement of organized spot market´s efficiency. Grid operators and utilities become able to act in both energy and reserve components of electricity markets. This paper proposes a methodology for a joint dispatch of demand response and distributed generation to provide energy and reserve by a virtual power player that operates a distribution network. The proposed method has been computationally implemented and its application is illustrated in this paper using a 32 bus distribution network with 32 medium voltage consumers.

Virtual power producers market strategies

This paper presents MASCEM - a multi-agent based electricity market simulator. MASCEM uses game theory, machine learning techniques, scenario analysis and optimisation techniques to model market agents and to provide them with decision-support. This paper mainly focus on the MASCEM ability to provide the means to model and simulate Virtual Power Producers (VPP). VPPs are represented as a coalition of agents, with specific characteristics and goals. The paper detail some of the most important aspects considered in VPP formation and in the aggregation of new producers and includes a case study.

Multi-agent electricity market simulation with dynamic strategies & virtual power producers

Distributed energy resources will provide a significant amount of the electricity generation and will be a normal profitable business. In the new decentralized grid, customers will be among the many decentralized players and may even help to co-produce the required energy services such as demand-side management and load shedding. So, they will gain the opportunity to be more active market players. The aggregation of DG plants gives place to a new concept: the Virtual Power Producer (VPP). VPPs can reinforce the importance of these generation technologies making them valuable in electricity markets. In this paper we propose the improvement of MASCEM, a multi-agent simulation tool to study negotiations in electricity spot markets based on different market mechanisms and behavior strategies, in order to take account of decentralized players such as VPP.

Distributed generation producers' reserve management

Sustainable development concerns are being addressed with increasing attention, in general, and in the scope of power industry, in particular. The use of distributed generation (DG), mainly based on renewable sources, has been seen as an interesting approach to this problem. However, the increasing of DG in power systems raises some complex technical and economic issues. This paper presents ViProd, a simulation tool that allows modeling and simulating DG operation and participation in electricity markets. This paper mainly focuses on the operation of Virtual Power Producers (VPP) which are producers’ aggregations, being these producers mainly of DG type. The paper presents several reserve management strategies implemented in the scope of ViProd and the results of a case study, based on real data.

LMP triggered real time demand response events

Recent changes in power systems mainly due to the substantial increase of distributed generation and to the operation in competitive environments has created new challenges to operation and planning. In this context, Virtual Power Players (VPP) can aggregate a diversity of players, namely generators and consumers, and a diversity of energy resources, including electricity generation based on several technologies, storage and demand response. Demand response market implementation has been done in recent years. Several implementation models have been considered. An important characteristic of a demand response program is the trigger criterion. A program for which the event trigger depends on the Locational Marginal Price (LMP) used by the New England Independent System operator (ISO-NE) inspired the present paper. This paper proposes a methodology to support VPP demand response programs management. The proposed method has been computationally implemented and its application is illustrated using a 32 bus network with intensive use of distributed generation. Results concerning the evaluation of the impact of using demand response events are also presented.

LMP based bid formation for virtual power players operating in smart grids

Power system organization has gone through huge changes in the recent years. Significant increase in distributed generation (DG) and operation in the scope of liberalized markets are two relevant driving forces for these changes. More recently, the smart grid (SG) concept gained increased importance, and is being seen as a paradigm able to support power system requirements for the future. This paper proposes a computational architecture to support day-ahead Virtual Power Player (VPP) bid formation in the smart grid context. This architecture includes a forecasting module, a resource optimization and Locational Marginal Price (LMP) computation module, and a bid formation module. Due to the involved problems characteristics, the implementation of this architecture requires the use of Artificial Intelligence (AI) techniques. Artificial Neural Networks (ANN) are used for resource and load forecasting and Evolutionary Particle Swarm Optimization (EPSO) is used for energy resource scheduling. The paper presents a case study that considers a 33 bus distribution network that includes 67 distributed generators, 32 loads and 9 storage units.

ANN based support for distributed energy resources scheduling in smart grids

The future scenarios for operation of smart grids are likely to include a large diversity of players, of different types and sizes. With control and decision making being decentralized over the network, intelligence should also be decentralized so that every player is able to play in the market environment. In the new context, aggregator players, enabling medium, small, and even micro size players to act in a competitive environment, will be very relevant. Virtual Power Players (VPP) and single players must optimize their energy resource management in order to accomplish their goals. This is relatively easy to larger players, with financial means to have access to adequate decision support tools, to support decision making concerning their optimal resource schedule. However, the smaller players have difficulties in accessing this kind of tools. So, it is required that these smaller players can be offered alternative methods to support their decisions. This paper presents a methodology, based on Artificial Neural Networks (ANN), intended to support smaller players’ resource scheduling. The used methodology uses a training set that is built using the energy resource scheduling solutions obtained with a reference optimization methodology, a mixed-integer non-linear programming (MINLP) in this case. The trained network is able to achieve good schedule results requiring modest computational means.

Multilevel negotiation in smart grids for VPP management of distributed resources

A multilevel negotiation mechanism for operating smart grids and negotiating in electricity markets considers the advantages of virtual power player management.