Development of a community-based framework to manage prosumers in smart grid

This dissertation proposes frameworks to address key research challenges of managing prosumers in smart grid in the form of prosumer community groups (PCGs) namely PCG definition and characterization, new prosumer recruitment, multiple goals management and mutual goal definition and member assessment and ranking. The existing literature has very little to offer, by way of either reviewing the related concepts of PCGs or resolving the associated challenges, making our work novel within the research field

Research trends on microgrid systems: a bibliometric network analysis

The numeral of academic publications in the microgrid system field has rapidly grown. A microgrid system is a group of interconnected distributed generation, loads, and energy storage operating as a single controllable entity. Many published articles recently focused on distributed generation, system control, system stability, power quality, architectures, and broader focus areas. This work analyzes microgrid: alternating current (AC), direct current (DC), and hybrid AC/DC microgrid systems with bibliometric network analysis through descriptive analysis, authors analysis, sources analysis, words analysis, and evolutionary path based on the Scopus database between 2010 and 2021. The finding helps find out the top authors and most impact sources, most relevant and frequently used in the research title, abstract, and keyword, graphically mapping the research evolved and identifying trend topic

Wide-Area Time-Synchronized Closed-Loop Control of Power Systems And Decentralized Active Distribution Networks

The rapidly expanding power system grid infrastructure and the need to reduce the occurrence of major blackouts and prevention or hardening of systems against cyber-attacks, have led to increased interest in the improved resilience of the electrical grid. Distributed and decentralized control have been widely applied to computer science research. However, for power system applications, the real-time application of decentralized and distributed control algorithms introduce several challenges. In this dissertation, new algorithms and methods for decentralized control, protection and energy management of Wide Area Monitoring, Protection and Control (WAMPAC) and the Active Distribution Network (ADN) are developed to improve the resiliency of the power system. To evaluate the findings of this dissertation, a laboratory-scale integrated Wide WAMPAC and ADN control platform was designed and implemented. The developed platform consists of phasor measurement units (PMU), intelligent electronic devices (IED) and programmable logic controllers (PLC). On top of the designed hardware control platform, a multi-agent cyber-physical interoperability viii framework was developed for real-time verification of the developed decentralized and distributed algorithms using local wireless and Internet-based cloud communication. A novel real-time multiagent system interoperability testbed was developed to enable utility independent private microgrids standardized interoperability framework and define behavioral models for expandability and plug-and-play operation. The state-of-theart power system multiagent framework is improved by providing specific attributes and a deliberative behavior modeling capability. The proposed multi-agent framework is validated in a laboratory based testbed involving developed intelligent electronic device prototypes and actual microgrid setups. Experimental results are demonstrated for both decentralized and distributed control approaches. A new adaptive real-time protection and remedial action scheme (RAS) method using agent-based distributed communication was developed for autonomous hybrid AC/DC microgrids to increase resiliency and continuous operability after fault conditions. Unlike the conventional consecutive time delay-based overcurrent protection schemes, the developed technique defines a selectivity mechanism considering the RAS of the microgrid after fault instant based on feeder characteristics and the location of the IEDs. The experimental results showed a significant improvement in terms of resiliency of microgrids through protection using agent-based distributed communication

Efficient Digital Management in Smart Cities

The concept of smart cities puts the citizen at the center of all processes. It is the citizen who decides what kind of city they live in. Their opinions and attitudes towards technologies and the solutions they would like to see in their cities must be listened to. With Deep Intelligence, cities will be able to create more optimal citizen-centered services as, as the tool can collect data from multiple sources, such as databases and social networks, from which valuable information on citizens’ opinions and attitudes regarding technology, smart city services and urban problems, may be extracted

Towards a European Smart Energy System - ICT innovation goals and considerations

The EU-driven integration of European energy systems and the development of a Smart Energy System involves many key players. The success of a European Smart Energy Systems relies heavily on the development of well-designed ICT solutions in all related sectors. Because such ICT solutions should be well aligned, ICT innovation goals are needed that have the support of key European players and consortia. To this end, Round Tables have been organised by EIT ICT Labs from 2013 onwards, in which key players in the European energy sector establish a common vision on and align forces in the development of a European Smart Energy System. We reflect and build upon these discussions to formulate a joint input to the European goals on ICT and Smart Energy Systems, and for the innovation activities of EIT ICT Labs

A Multi-Agent System Simulation Model for Trusted Local Energy Markets

The energy market and electric grid play a major role in everyday life. Most areas in modern society, such as: communication, health, transportation, the financial system and many others; require electrical energy to operate properly. Traditionally energy grids operate in a centralized manner. Consumers are connected to centralized utilities in the grid and energy flows from producers to Consumers. However, the rising in popularity in Renewable Energy Sources (RES) such as photovoltaic panels installed in households, small commerce and small industry wide spread the use of distributed energy generation, which the main energy grid was not designed to support. One of the possible solutions for this problem is the creation of a Local Energy Market (LeM). A LeM is a market that operates in a small physical area such as a neighborhood. Traditional consumers can become active market participants under a LeM. That is possible because the LeM is structured in such a way as to enable small-scale negotiations and energy exchanges between participants, who traditionally would only be final consumers. The LeM is capable of dealing with distributed energy generation from RES because negotiations and distribution happen at a local level, thus reducing problems with the main grid. Furthermore, the participation in the local market can reduce energy costs or even create profits for consumers, while contributing to easy the management of the grid and associated technical losses. This work explores the concept of LeM and is focused on two main objectives: designing and developing a system that allows the simulation of LeM, and designing and developing a mechanism that allows trusted negotiations in this market. To accomplish these objectives a Multi-Agent System (MAS) architecture is proposed to model and allow the simulation of LeM. Furthermore to support the market it is also proposed a trust model used to evaluate the behavior of participants and detecting faulty or malicious activities. The developed MAS models a LeM based on a Smart Grid, that is an energy grid with a cyber-physical system with smart meters and communications mechanisms. The MAS was developed with agents to model sensors, market participants and a Market Interaction Manager (MIM) agent that is responsible for managing the negotiations and for applying trust mechanisms. The trust mechanism was designed to attribute a dynamic trust value to each participant, which is reviewed during the all negotiation period. This evaluation of the participant’s trust is based on the analysis of historical data, contextual data, such as weather conditions, and by using forecasting methods to predict the participant expected behavior, allowing to penalize the ones that are exhibiting a questionable behavior in the market. A case study simulation was made with the objective of understanding how the proposed trust mechanism performed, and how the use of different forecasting methods can interfere with it. The results obtained allowed us to conclude that the trust methodology is able to update the trust of each participant, during the negotiation period, and when paired with a well performing forecasting mechanism it is able to achieve a trusted evaluation of the participants behavior. Taking into consideration these results we believe that the proposed trust methodology is capable of providing a valuable trust assessment when used by the MIM agent. This Master Thesis is developed within the scope of a project called Secure interactions and trusted Participation in local Electricity Trading (SPET), a FCT-SAICT2017 funded Research & Development project. SPET project envisions the development of a MAS that is designed to model and simulate the operations of a LeM, taking a focus on security and market trust necessary in this negotiation environment.O mercado de energia e a rede elétrica desempenham um papel importante na vida quotidiana da população. Grande parte das áreas da sociedade moderna, como é o caso da comunicação, transportes, saúde, sistema financeiro, entre outras; requer energia elétrica para funcionar corretamente. Tradicionalmente, as redes de energia operam de forma centralizada. Os consumidores estão conectados a fornecedores centralizados na rede e a energia é transferida dos produtores para os consumidores. No entanto, o aumento da popularidade das Fontes de Energia Renováveis (FER), como painéis fotovoltaicos instalados nas residências, pequeno comércio e pequena indústria, difundiu o uso da geração distribuída de energia, que a rede principal de energia não foi projetada para suportar. Uma das possíveis soluções para esse problema é a criação de um Mercado Local de Energia (MLe). Um MLe é um mercado que opera numa pequena área física, como uma vizinhança. Num MLe, os consumidores tradicionais têm a possibilidade de ser participantes ativos no mercado. Isto é possível porque o MLe está estruturado de forma a permitir negociações em pequena escala e trocas de energia entre os participantes, que tradicionalmente seriam apenas consumidores finais. O MLe é capaz de lidar com a geração de energia distribuída proveniente das FER, porque as negociações e a distribuição ocorrem a um nível local, reduzindo assim os problemas com a rede principal. Para além disso, a participação no mercado local pode reduzir os custos de energia ou até gerar lucros para os consumidores, contribuindo ainda para facilitar a gestão da rede e reduzir as perdas técnicas a ela associadas. Este trabalho explora o conceito de MLe e está focado em dois objetivos principais: projetar e desenvolver um sistema que permita a simulação de MLe, bem como um mecanismo que permita negociações confiáveis neste mercado. Para atingir estes objetivos, é proposta uma arquitetura de Sistema Multi-Agente (SMA) para modelar e permitir a simulação do MLe. Para além disso, para apoiar o mercado, também é proposto um modelo de confiança utilizado para avaliar o comportamento dos participantes e detetar falhas ou atividades maliciosas. O SMA desenvolvido modela um MLe com base numa Smart Grid, que é uma rede de energia com um sistema ciber-físico, com sensores inteligentes e mecanismos de comunicação. O SMA foi desenvolvido com agentes para modelar sensores, participantes do mercado e um agente Market Interaction Manager (MIM), responsável pela gestão das negociações e pela aplicação de mecanismos de confiança. O mecanismo de confiança foi projetado para atribuir um valor de confiança dinâmico a cada participante, que é adaptado durante todo o período de negociação. Essa avaliação da confiança do participante é baseada na análise de dados históricos, contextuais, como condições climatéricas, e no uso de métodos de previsão para antever o comportamento esperado do participante, permitindo penalizar aqueles que exibem um comportamento questionável no mercado. Foi realizada uma simulação de caso de estudo, com o objetivo de avaliar o desempenho do mecanismo de confiança proposto e de que forma é que o uso de diferentes métodos de previsão interfere neste desempenho. Os resultados obtidos permitiram concluir que a metodologia de confiança é capaz de atualizar a confiança de cada participante, durante o período de negociação e, quando combinada com um mecanismo de previsão com bom desempenho, é capaz de obter uma avaliação confiável do comportamento dos participantes. Tendo em consideração estes resultados, acreditamos que a metodologia de confiança proposta é capaz de fornecer uma avaliação de confiança valiosa quando usada pelo agente MIM. Esta tese de mestrado é desenvolvida no âmbito de um projeto chamado Secure interactions and trusted Participation in local Electricity Trading (SPET), um projeto de Investigação e Desenvolvimento (I&D) financiado pela FCT-SAICT2017. O projeto SPET tem como objetivo o desenvolvimento de um MAS para a modelação e simulação de MLe, tendo como foco a segurança e confiança necessárias neste ambiente de negociação

Transitioning power distribution grid into nanostructured ecosystem : prosumer-centric sovereignty

PhD ThesisGrowing acceptance for in-house Distributed Energy Resource (DER) installations at lowvoltage level have gained much significance in recent years due to electricity market liberalisations and opportunities in reduced energy billings through personalised utilisation management for targeted business model. In consequence, modelling of passive customers’ electric power system are progressively transitioned into Prosumer-based settings where presidency for Transactive Energy (TE) system framework is favoured. It amplifies Prosumers’ commitments into annexing TE values during market participations and optimised energy management to earn larger rebates and incentives from TE programs. However, when dealing with mass Behind-The-Meter DER administrations, Utility foresee managerial challenges when dealing with distribution network analysis, planning, protection, and power quality security based on Prosumers’ flexibility in optimising their energy needs. This dissertation contributes prepositions into modelling Distributed Energy Resources Management System (DERMS) as an aggregator designed for Prosumer-centered cooperation, interoperating TE control and coordination as key parameters to market for both optimised energy trading and ancillary services in a Community setting. However, Prosumers are primarily driven to create a profitable business model when modelling their DERMS aggregator. Greedy-optimisation exploitations are negative concerns when decisions made resulted in detrimental-uncoordinated outcomes on Demand-Side Response (DSR) and capacity market engagements. This calls for policy decision makers to contract safe (i.e. cooperative yet competitive tendency) business models for Prosumers to maximise TE values while enhancing network’s power quality metrics and reliability performances. Firstly, digitalisation and nanostructuring of distribution network is suggested to identify Prosumer as a sole energy citizen while extending bilateral trading between Prosumer-to- Prosumer (PtP) with the involvements of other grid operators−TE system. Modelling of Nanogrid environment for DER integrations and establishment of local area network infrastructure for IoT security (i.e. personal computing solutions and data protection) are committed for communal engagements in a decentralise setting. Secondly, a multi-layered Distributed Control Framework (DCF) is proposed using Microsoft Azure cloud-edge platform that cascades energy actors into respective layers of TE control and coordination. Furthermore, modelling of flexi-edge computing architecture is proposed, comprising of Contract-Oriented Sensor-based Application Platform (COSAP) employing Multi-Agent System (MAS) to enhance data-sharing privacy and contract coalition agreements during PtP engagements. Lastly, the Agents of MAS are programmed with cooperative yet competitive intelligences attributed to Reinforcement Learning (RL) and Neural Networks (NN) algorithms to solve multimodal socio-economical and uncertainty problems that corresponded to Prosumers’ dynamic energy priorities within the TE framework. To verify the DERMS aggregator operations, three business models were proposed (i.e. greedy-profit margin, collegial-peak demand, reserved-standalone) to analyse comparative technical/physical and economic/social dimensions. Results showed that the proposed TE-valued DERMS aggregator provides participation versatility in the electricity market that enables competitive edginess when utilising Behind-The-Meter DERs in view of Prosumer’s asset scheduling, bidding strategy, and corroborative ancillary services. Performance metrics were evaluated on both domestic and industrial NG environments against IEEE Standard 2030.7-2017 & 2030.8-2018 compliances to ensure deployment practicability. Subsequently, proposed in-house protection system for DER installation serves as an add-on monitoring service which can be incorporated into existing Advance Distribution Management System (ADMS) for Distribution Service Operator (DSO) and field engineers use, ADMS aggregator. It provides early fault detections and isolation processes from allowing fault current to propagate upstream causing cascading power quality issues across the feeder line. In addition, ADMS aggregator also serves as islanding indicator that distinguishes Nanogrid’s islanding state from unintentional or intentional operations. Therefore, a Overcurrent Current Relay (OCR) is proposed using Fuzzy Logic (FL) algorithm to detect, profile, and provide decisional isolation processes using specified OCRs. Moreover, the proposed expert knowledge in FL is programmed to detect fault crises despite insufficient fault current level contributed by DER (i.e. solar PV system) which conventional OCR fails to trigger