Distributed energy resource short-term scheduling using signaled particle swarm optimization

Distributed Energy Resources (DER) scheduling in smart grids presents a new challenge to system operators. The increase of new resources, such as storage systems and demand response programs, results in additional computational efforts for optimization problems. On the other hand, since natural resources, such as wind and sun, can only be precisely forecasted with small anticipation, short-term scheduling is especially relevant requiring a very good performance on large dimension problems. Traditional techniques such as Mixed-Integer Non-Linear Programming (MINLP) do not cope well with large scale problems. This type of problems can be appropriately addressed by metaheuristics approaches. This paper proposes a new methodology called Signaled Particle Swarm Optimization (SiPSO) to address the energy resources management problem in the scope of smart grids, with intensive use of DER. The proposed methodology’s performance is illustrated by a case study with 99 distributed generators, 208 loads, and 27 storage units. The results are compared with those obtained in other methodologies, namely MINLP, Genetic Algorithm, original Particle Swarm Optimization (PSO), Evolutionary PSO, and New PSO. SiPSO performance is superior to the other tested PSO variants, demonstrating its adequacy to solve large dimension problems which require a decision in a short period of time.

Adaptable control for electrical generation at irregural wind speeds

The main aims of this work are the development and the validation of one generic algorithm to provide the optimal control of small power wind generators. That means up to 40 kW and blades with fixed pitch angle. This algorithm allows the development of controllers to fetch the wind generators at the desired operational point in variable operating conditions. The problems posed by the variable wind intensity are solved using the proposed algorithm. This is done with no explicit measure of the wind velocity, and so no special equipment or anemometer is required to compute or measure the wind velocity.

Genetic algorithm methodology applied to intelligent house control

In recent years the use of several new resources in power systems, such as distributed generation, demand response and more recently electric vehicles, has significantly increased. Power systems aim at lowering operational costs, requiring an adequate energy resources management. In this context, load consumption management plays an important role, being necessary to use optimization strategies to adjust the consumption to the supply profile. These optimization strategies can be integrated in demand response programs. The control of the energy consumption of an intelligent house has the objective of optimizing the load consumption. This paper presents a genetic algorithm approach to manage the consumption of a residential house making use of a SCADA system developed by the authors. Consumption management is done reducing or curtailing loads to keep the power consumption in, or below, a specified energy consumption limit. This limit is determined according to the consumer strategy and taking into account the renewable based micro generation, energy price, supplier solicitations, and consumers’ preferences. The proposed approach is compared with a mixed integer non-linear approach.

Particle swarm optimization applied to integrated demand response resources scheduling

The concept of demand response has a growing importance in the context of the future power systems. Demand response can be seen as a resource like distributed generation, storage, electric vehicles, etc. All these resources require the existence of an infrastructure able to give players the means to operate and use them in an efficient way. This infrastructure implements in practice the smart grid concept, and should accommodate a large number of diverse types of players in the context of a competitive business environment. In this paper, demand response is optimally scheduled jointly with other resources such as distributed generation units and the energy provided by the electricity market, minimizing the operation costs from the point of view of a virtual power player, who manages these resources and supplies the aggregated consumers. The optimal schedule is obtained using two approaches based on particle swarm optimization (with and without mutation) which are compared with a deterministic approach that is used as a reference methodology. A case study with two scenarios implemented in DemSi, a demand Response simulator developed by the authors, evidences the advantages of the use of the proposed particle swarm approaches.

Contexts-management strategy in considering the security in urban computing based on urban design

Urban Computing (UrC) provides users with the situation-proper information by considering context of users, devices, and social and physical environment in urban life. With social network services, UrC makes it possible for people with common interests to organize a virtual-society through exchange of context information among them. In these cases, people and personal devices are vulnerable to fake and misleading context information which is transferred from unauthorized and unauthenticated servers by attackers. So called smart devices which run automatically on some context events are more vulnerable if they are not prepared for attacks. In this paper, we illustrate some UrC service scenarios, and show important context information, possible threats, protection method, and secure context management for people.

Intelligent SCADA for load control

A supervisory control and data acquisition (SCADA) system is an integrated platform that incorporates several components and it has been applied in the field of power systems and several engineering applications to monitor, operate and control a lot of processes. In the future electrical networks, SCADA systems are essential for an intelligent management of resources like distributed generation and demand response, implemented in the smart grid context. This paper presents a SCADA system for a typical residential house. The application is implemented on MOVICON™11 software. The main objective is to manage the residential consumption, reducing or curtailing loads to keep the power consumption in or below a specified setpoint, imposed by the costumer and the generation availability.

The darmstadt challenge (the turing test revisited)

Significant work has been done in the areas of Pervcomp/Ubicomp Smart Environments with advances on making proactive systems, but those advances have not made these type of systems accurately proactive. On the other hand a great deal is needed to make systems more sensible/sensitive and trustable (both in terms of reliability and privacy). We put forward the thesis that a more integral and social-aware sort of intelligence is needed to effectively interact, decide and act on behalf of people’s interest and that a way to test how effective systems are achieving these desirable behaviour is needed as a consequence. We support our thesis by providing examples on how to measure effectiveness in variety of different environments.

Estudo de tecnologias domóticas e a sua aplicação em projectos

Actualmente a área da domótica (automação de casas e edifícios) encontra-se em franca expansão, com principal relevância nos países mais desenvolvidos, com um crescimento de mercado de mais de 10% ao ano. Existem inúmeras razoes para a crescente implantação da domótica em edifícios, entre as quais a maior eficiência energética, o aumento da segurança e a redução do custo de aquisição das tecnologias. No que diz respeito as habitações particulares, acrescenta-se essencialmente o aumento do conforto devido ao grau de automação trazido pela domótica. Apesar da domótica não ser uma área cientifico-tecnológica recente, a rápida evolução das tecnologias associadas, nomeadamente a nível das redes de comunicação com e sem fios, foi uma das razoes fundamentais para a elaboração desta Tese. Acresce o facto de o candidato estar actualmente envolvido profissionalmente na área, pelo qual esta Tese assume uma particular importância. Realizou-se um estudo comparativo das tecnologias de domótica mais relevantes, escolhidas quer pelas suas características técnicas quer pela sua implantação de mercado e potencial futuro - KNX/EIB, LonWorks, HomePlug, ZigBee e Z-Wave. Destas, comprovou-se que as duas primeiras são aquelas que, actualmente, tem maior adequabilidade para serem aplicadas em projectos de domótica. Foi por isso efectuado um estudo mais elaborado das tecnologias LonWorks e KNX/EIB, incluindo a forma pratica de instalação/programação, a elaboração de dois demonstradores e de dois projectos (de acordo com um caderno de encargos real), usando as duas tecnologias. Concluiu-se que a tecnologia LonWorks apresenta vantagens no que respeita a escalabilidade (dimensão) dos sistemas. Em termos futuros, prevê-se a necessidade da interoperabilidade entre os nos/redes cablados (tradicionais) com nos/redes sem fio, seguindo a tendência para os ambientes inteligentes (“ambient intelligence/assisted living”, “smart spaces”, “ubiquitous computing).

Integração da tecnologia Near Field Communications nas telecomunicações móveis

O telemóvel tem-se transformado numa ferramenta essencial no nosso dia-a-dia, constantemente são lançadas novas tecnologias que potenciam o uso do telemóvel nas tarefas do nosso quotidiano. Atualmente a grande tendência passa por fazer o download de aplicações com o objetivo de obter mais e diferentes tipos de informação, existe o desejo de ler de forma simples e intuitiva o mundo que nos rodeia, como se cada elemento fosse um objeto sobre o qual conseguiremos obter informação através do telemóvel. A tecnologia Near Field Communication (NFC) ajuda a transformar este desejo ou necessidade numa realidade de simples alcance. Podemos anexar “identificadores” nos objetos e “ver” estes identificadores através do telemóvel recorrendo a aplicações que fazem a ponte com os sistemas que nos permitem obter mais informação, por exemplo, internet. O NFC especifica um padrão de comunicação de redes sem fios, que permite a transferência de dados entre dois dispositivos separados por uma distância máxima de 10cm. NFC foi desenhado para ser integrado em telemóveis, que podem comunicar com outros telemóveis equipados com NFC ou ler informação de cartões ou tags. A dissertação avalia as oportunidades que a tecnologia NFC oferece ao mundo das telecomunicações móveis, nomeadamente na realidade do operador Vodafone Portugal, principalmente numa relação Empresa - Cliente. Esta tecnologia reúne o interesse dos fabricantes dos telemóveis, dos operadores e de parceiros críticos que vão ajudar a potenciar o negócio, nomeadamente entidades bancárias e interbancárias. A tecnologia NFC permite utilizar o telemóvel como um cartão de crédito/debito, ticketing, ler informação de posters (Smart Poster) que despoletem navegação contextualizada para outras aplicações ou para a internet para obter mais informação ou concretizar compras, estes são alguns cenários identificados que mais valor o NFC consegue oferecer. A dissertação foca-se na avaliação técnica do NFC na área de Smart Posters e resulta na identificação num conjunto de novos cenários de utilização, que são especificados e complementados com o desenvolvimento de um protótipo.

Nanohybrid materials as transducer surfaces for electrochemical sensing applications

A nanohybrid electrochemical transducer surface was developed using carbon and gold nanomaterials. The strategy relayed on casting multiwalled carbon nanotubes or carbon nanofibers onto a screen-printed carbon electrode surface, followed by in situ generation of gold nanoparticles by electrochemical deposition of ionic gold, in a reproducible manner. These transducers, so fabricated, were characterized using both electrochemical and microscopic techniques. Biofunctionality was evaluated using the streptavidin-biotin interaction system as the biological reaction model. These platforms allow to achieve low detection limits (in the order of pmoles), are reproducible and stable at least for a month after their preparation, being a perfect candidate to be used as transducer of different sensor devices.

Distribution system operation supported by contextual energy resource management based on intelligent SCADA

Future distribution systems will have to deal with an intensive penetration of distributed energy resources ensuring reliable and secure operation according to the smart grid paradigm. SCADA (Supervisory Control and Data Acquisition) is an essential infrastructure for this evolution. This paper proposes a new conceptual design of an intelligent SCADA with a decentralized, flexible, and intelligent approach, adaptive to the context (context awareness). This SCADA model is used to support the energy resource management undertaken by a distribution network operator (DNO). Resource management considers all the involved costs, power flows, and electricity prices, allowing the use of network reconfiguration and load curtailment. Locational Marginal Prices (LMP) are evaluated and used in specific situations to apply Demand Response (DR) programs on a global or a local basis. The paper includes a case study using a 114 bus distribution network and load demand based on real data.

Application-specific modified particle swarm optimization for energy resource scheduling considering vehicle-to-grid

This paper presents a modified Particle Swarm Optimization (PSO) methodology to solve the problem of energy resources management with high penetration of distributed generation and Electric Vehicles (EVs) with gridable capability (V2G). The objective of the day-ahead scheduling problem in this work is to minimize operation costs, namely energy costs, regarding he management of these resources in the smart grid context. The modifications applied to the PSO aimed to improve its adequacy to solve the mentioned problem. The proposed Application Specific Modified Particle Swarm Optimization (ASMPSO) includes an intelligent mechanism to adjust velocity limits during the search process, as well as self-parameterization of PSO parameters making it more user-independent. It presents better robustness and convergence characteristics compared with the tested PSO variants as well as better constraint handling. This enables its use for addressing real world large-scale problems in much shorter times than the deterministic methods, providing system operators with adequate decision support and achieving efficient resource scheduling, even when a significant number of alternative scenarios should be considered. The paper includes two realistic case studies with different penetration of gridable vehicles (1000 and 2000). The proposed methodology is about 2600 times faster than Mixed-Integer Non-Linear Programming (MINLP) reference technique, reducing the time required from 25 h to 36 s for the scenario with 2000 vehicles, with about one percent of difference in the objective function cost value.

Data gathering approach in dense sensor networks

Sensor/actuator networks promised to extend automated monitoring and control into industrial processes. Avionic system is one of the prominent technologies that can highly gain from dense sensor/actuator deployments. An aircraft with smart sensing skin would fulfill the vision of affordability and environmental friendliness properties by reducing the fuel consumption. Achieving these properties is possible by providing an approximate representation of the air flow across the body of the aircraft and suppressing the detected aerodynamic drags. To the best of our knowledge, getting an accurate representation of the physical entity is one of the most significant challenges that still exists with dense sensor/actuator network. This paper offers an efficient way to acquire sensor readings from very large sensor/actuator network that are located in a small area (dense network). It presents LIA algorithm, a Linear Interpolation Algorithm that provides two important contributions. First, it demonstrates the effectiveness of employing a transformation matrix to mimic the environmental behavior. Second, it renders a smart solution for updating the previously defined matrix through a procedure called learning phase. Simulation results reveal that the average relative error in LIA algorithm can be reduced by as much as 60% by exploiting transformation matrix.

A scalable and efficient approach for obtaining measurements in CAN-Based control systems

The availability of small inexpensive sensor elements enables the employment of large wired or wireless sensor networks for feeding control systems. Unfortunately, the need to transmit a large number of sensor measurements over a network negatively affects the timing parameters of the control loop. This paper presents a solution to this problem by representing sensor measurements with an approximate representation-an interpolation of sensor measurements as a function of space coordinates. A priority-based medium access control (MAC) protocol is used to select the sensor messages with high information content. Thus, the information from a large number of sensor measurements is conveyed within a few messages. This approach greatly reduces the time for obtaining a snapshot of the environment state and therefore supports the real-time requirements of feedback control loops.

Modified particle swarm optimization for day-ahead distributed energy resources scheduling including vehicle-to-grid

Mestrado em Engenharia Electrotécnica – Sistemas Eléctricos de Energia