715 research outputs found

    LIPIcs, Volume 251, ITCS 2023, Complete Volume

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    LIPIcs, Volume 251, ITCS 2023, Complete Volum

    Modelação e Negociação de Flexibilidade em Comunidades de Energia Renovável

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    The progressive replacement of traditional generation resources with intermittent resources has reduced the available supply-side flexibility and increased the need to unlock flexibility on the demand-side. At the same time, the rising electricity consumption in residential buildings requires an analysis of the potential flexibility of the loads within them to contribute to the operation needs of electrical grids. Lastly, regulations governing self consumption have allowed end consumers to form energy communities based on local electricity markets. This is an additional incentive to define strategies for trading available flexibility at local level, in separate but simultaneously integrated structures within wholesale electricity markets. The proposed dissertation work focuses on studying the flexibility of energy production and consumption by prosumers within a Renewable Energy Community (REC). The objective is to investigate how residential flexibility can be determined, modeled, and aggregated for trading in a local market created for this purpose. The work to be developed will present a two-stage model that determines residential technical flexibility and establishes a local market only for its transaction. In the first stage, the optimal scheduling of domestic devices (flexible units or FUs) for each prosumer is determined, serving as a baseline for comparison, along with the technical limits of flexibility (maximum and minimum possible consumption profiles) for each FU. In the second stage, a market model is established only for flexibility exchanges. The technical flexibility determined in the first stage is offered to the Community Manager (CM) as flexibility offer, with an associated price. This entity acts as an aggregator and simultaneously as the operator of the local market. At this level, the Distribution System Operator (DSO) submits its flexibility requirements for the next day to the CM, who is responsible for executing the clearing process. The pricing of the flexibility offered by prosumers in the market is based on the base energy tariff they are subject to, which corresponds to the cost of their optimal scheduling obtained in the first stage, without considering this flexibility. Therefore, offering flexibility becomes an incentive to reduce prosumers energy costs or increase their utility, complementing their mere participation in energy markets. A case study based on a renewable energy community with a strong penetration of emerging technologies is used to validate and demonstrate the relevance of the proposed approach in terms of determining and activating residential FU flexibility. The obtained results show that participation in the local flexibility market leads to a reduction in prosumers energy costs, around 4.5%, in average. It can be an incentive for prosumers to join RECs that would not only have local energy trading structures but also mechanisms for negotiating and sharing flexibility. In addition, it was evidenced that the impact of electric vehicle chargers and battery energy storage systems on the total flexibility offered and accepted in the market is much greater than that the impact of other small loads studied. This not only constitutes an incentive for the study of the operational flexibility of these resources but also for investments in these emerging technologies.A substituição progressiva dos recursos de geração tradicionais por recursos intermitentes tem reduzido a flexibilidade disponível do lado da oferta e aumentado a necessidade de desbloqueá-la do lado da procura. Ao mesmo tempo, o aumento do consumo de eletricidade nos edifícios residenciais obriga a que seja analisada a flexibilidade potencial das cargas que o constituem, de modo a contribuir para as necessidades de operação das redes elétricas. Por último, a regulamentação do autoconsumo, tem permitido aos consumidores finais constituir comunidades energéticas baseadas em mercados locais de eletricidade. Isto torna ainda mais importante a definição de estratégias para comercializar a flexibilidade disponível a esse nível, em estruturas de mercado local separadas, mas simultaneamente integradas nos mercados grossistas de eletricidade. O trabalho proposto para dissertação assenta no estudo da flexibilidade da produção e consumo de energia por parte dos prosumidores de uma Comunidade de Energia Renovável. O objetivo é estudar como a flexibilidade residencial pode ser determinada, modelada e agregada de modo a ser transacionada num mercado local criado para esse fim. Assim, o trabalho a ser desenvolvido apresentará um modelo de dois estágios que determina a flexibilidade técnica residencial e cria um mercado local exclusivo para transaciona-la. Numa primeira fase, determina-se o escalonamento óptimo dos dispositivos domésticos (unidades flexíveis ou UF) de cada prosumidor, o que constitui uma baseline de comparação, bem como os limites técnicos de flexibilidade (perfis de consumo máximos e mínimos possíveis) de cada UF. Num segundo estágio, é estabelecido um modelo de mercado apenas para trocas de flexibilidade. A flexibilidade técnica determinada no primeiro estágio é disponibilizada ao Gestor de Comunidade (CM), enquanto oferta de flexibilidade, com um preço associado. Esta entidade desempenha as funções de agregador e simultaneamente de operador do mercado local. A este nível, o Operador do Sistema de Distribuição (ORD) submete os seus requisitos de flexibilidade, para o dia seguinte, ao CM, que é responsável pelo executar o clearing. A precificação da flexibilidade oferecida pelos prosumidores em mercado é feita com base no valor da tarifa base de energia a que estão sujeitos, que corresponde ao custo do seu escalonamento ótimo, obtido no primeiro estágio, que não considera essa mesma flexibilidade. Portanto, oferecer flexibilidade torna-se um incentivo para reduzir os custos energéticos dos prosumidores ou aumentar a sua utilidade, o que complementa a sua mera participação nos mercados de energia. Um caso de estudo baseado numa comunidade de energia com forte penetração de tecnologias emergentes é utilizado e valida a metodologia desenvolvida. Para além disso é evidenciada a relevância da abordagem proposta em termos de determinação e ativação da flexibilidade de UFs residenciais os impactos das mesmas no fecho de mercado. Os resultados evidenciam que participação no mercado local de flexibilidade induz uma redução dos custos energéticos dos prosumidores, na casa 4.5%, em média. O impacto dos carregadores de veículos elétricos e dos sistemas de armazenamento de energia em baterias na flexibilidade total oferecida e aceite em mercado é muito superior ao de outras pequenas cargas estudadas. Tudo isto pode vir a resultar num incentivo ao investimento nos recursos referidos, bem como à associação de prosumidores em comunidades de energia renovável, onde para além de estruturas locais de comercialização de energia, existam outras que permitam a negociação e partilha de flexibilidade

    Current issues of the management of socio-economic systems in terms of globalization challenges

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    The authors of the scientific monograph have come to the conclusion that the management of socio-economic systems in the terms of global challenges requires the use of mechanisms to ensure security, optimise the use of resource potential, increase competitiveness, and provide state support to economic entities. Basic research focuses on assessment of economic entities in the terms of global challenges, analysis of the financial system, migration flows, logistics and product exports, territorial development. The research results have been implemented in the different decision-making models in the context of global challenges, strategic planning, financial and food security, education management, information technology and innovation. The results of the study can be used in the developing of directions, programmes and strategies for sustainable development of economic entities and regions, increasing the competitiveness of products and services, decision-making at the level of ministries and agencies that regulate the processes of managing socio-economic systems. The results can also be used by students and young scientists in the educational process and conducting scientific research on the management of socio-economic systems in the terms of global challenges

    Designing core-selecting payment rules: a computational search approach

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    CMMI-1761163 - National Science Foundationhttps://doi.org/10.1287/isre.2022.1108Published versio

    Learning, future cost and role of offshore renewable energy technologies in the North Sea energy system

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    The pace of cost decline of offshore renewable energy technologies significantly impacts their role in the North Sea energy transition. However, a good understanding of their remains a critical knowledge gap in the literature. Therefore, this thesis aims to quantify the future role of offshore renewables in the North Sea energy transition and assess the impact of cost development on their optimal deployments. The following findings were observed in this thesis, 1) Fixed-bottom offshore wind is well established in the North Sea region and is already competitive with onshore renewables 2) Floating wind is emerging and their current costs are high, but it can reach about 40 EUR/MWh by early 2040 and would require 44 billion EUR of learning investment.3) Grid connection costs will become a major factor as wind farm moves further away. Policy actions and innovation is needed in this space to avoid increasing integration costs. 4) Offshore wind (fixed-bottom and floating) can play a significant role in the North Sea energy system, comprising 498 GW of deployments in 2050 (222 GW of fixed-bottom and 276 GW of floating wind) and contributing up to a maximum of 51% of total power generation in the North Sea power system. 5) The role of the investigated low-TRL offshore renewables, including the tidal stream, wave technology, and bioethanol, was limited in all scenarios considered, as they remain expensive compared to other mature technologies in the system

    Learning Dynamic Priority Scheduling Policies with Graph Attention Networks

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    The aim of this thesis is to develop novel graph attention network-based models to automatically learn scheduling policies for effectively solving resource optimization problems, covering both deterministic and stochastic environments. The policy learning methods utilize both imitation learning, when expert demonstrations are accessible at low cost, and reinforcement learning, when otherwise reward engineering is feasible. By parameterizing the learner with graph attention networks, the framework is computationally efficient and results in scalable resource optimization schedulers that adapt to various problem structures. This thesis addresses the problem of multi-robot task allocation (MRTA) under temporospatial constraints. Initially, robots with deterministic and homogeneous task performance are considered with the development of the RoboGNN scheduler. Then, I develop ScheduleNet, a novel heterogeneous graph attention network model, to efficiently reason about coordinating teams of heterogeneous robots. Next, I address problems under the more challenging stochastic setting in two parts. Part 1) Scheduling with stochastic and dynamic task completion times. The MRTA problem is extended by introducing human coworkers with dynamic learning curves and stochastic task execution. HybridNet, a hybrid network structure, has been developed that utilizes a heterogeneous graph-based encoder and a recurrent schedule propagator, to carry out fast schedule generation in multi-round settings. Part 2) Scheduling with stochastic and dynamic task arrival and completion times. With an application in failure-predictive plane maintenance, I develop a heterogeneous graph-based policy optimization (HetGPO) approach to enable learning robust scheduling policies in highly stochastic environments. Through extensive experiments, the proposed framework has been shown to outperform prior state-of-the-art algorithms in different applications. My research contributes several key innovations regarding designing graph-based learning algorithms in operations research.Ph.D

    Demand Response in Smart Grids

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    The Special Issue “Demand Response in Smart Grids” includes 11 papers on a variety of topics. The success of this Special Issue demonstrates the relevance of demand response programs and events in the operation of power and energy systems at both the distribution level and at the wide power system level. This reprint addresses the design, implementation, and operation of demand response programs, with focus on methods and techniques to achieve an optimized operation as well as on the electricity consumer

    Deep Contract Design via Discontinuous Networks

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    Contract design involves a principal who establishes contractual agreements about payments for outcomes that arise from the actions of an agent. In this paper, we initiate the study of deep learning for the automated design of optimal contracts. We introduce a novel representation: the Discontinuous ReLU (DeLU) network, which models the principal's utility as a discontinuous piecewise affine function of the design of a contract where each piece corresponds to the agent taking a particular action. DeLU networks implicitly learn closed-form expressions for the incentive compatibility constraints of the agent and the utility maximization objective of the principal, and support parallel inference on each piece through linear programming or interior-point methods that solve for optimal contracts. We provide empirical results that demonstrate success in approximating the principal's utility function with a small number of training samples and scaling to find approximately optimal contracts on problems with a large number of actions and outcomes

    LIPIcs, Volume 261, ICALP 2023, Complete Volume

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    LIPIcs, Volume 261, ICALP 2023, Complete Volum

    Resource allocation for dataflow applications in FANETs using anypath routing

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    Management of network resources in advanced IoT applications is a challenging topic due to their distributed nature from the Edge to the Cloud, and the heavy demand of real-time data from many sources to take action in the deployment. FANETs (Flying Ad-hoc Networks) are a clear example of heterogeneous multi-modal use cases, which require strict quality in the network communications, as well as the coordination of the computing capabilities, in order to operate correctly the final service. In this paper, we present a Virtual Network Embedding (VNE) framework designed for the allocation of dataflow applications, composed of nano-services that produce or consume data, in a wireless infrastructure, such as an airborne network. To address the problem, an anypath-based heuristic algorithm that considers the quality demand of the communication between nano-services is proposed, coined as Quality-Revenue Paired Anypath Dataflow VNE (QRPAD-VNE). We also provide a simulation environment for the evaluation of its performance according to the virtual network (VN) request load in the system. Finally, we show the suitability of a multi-parameter framework in conjunction with anypath routing in order to have better performance results that guarantee minimum quality in the wireless communications.Xunta de Galicia | Ref. ED431C 2022/04 T254Ministerio de Universidades | Ref. FPU19/01284Agencia Estatal de Investigación | Ref. PCI2020-112174Agencia Estatal de Investigación | Ref. PID2020-113795RB-C33Agencia Estatal de Investigación | Ref. PID2020-116329GB-C21Universidade de Vigo/CISU
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