An Interoperable Approach for Energy Systems Simulation: Electricity Market Participation Ontologies

Santos, Gabriel; Pinto, Tiago; Praça, Isabel; Vale, Zita

doi:10.3390/en9110878

Cited by 15 publications

(19 citation statements)

References 21 publications

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“…Its modular design eases the extension and reuse of the necessary concepts and relations. The LMO application ontology imports and extends the Call for Proposal (CfP) ontology and the Electricity Market Results (EMR) ontology [52], which already import EMO's high-level module. Table 1 presents LMO's classes, as well as their properties and facets.…”

Section: Application Ontologymentioning

confidence: 99%

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Constrained Generation Bids in Local Electricity Markets: A Semantic Approach

et al. 2020

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The worldwide investment in renewable energy sources is leading to the formation of local energy communities in which users can trade electric energy locally. Regulations and the required enablers for effective transactions in this new context are currently being designed. Hence, the development of software tools to support local transactions is still at an early stage and faces the challenge of constant updates to the data models and business rules. The present paper proposes a novel approach for the development of software tools to solve auction-based local electricity markets, considering the special needs of local energy communities. The proposed approach considers constrained bids that can increase the effectiveness of distributed generation use. The proposed method takes advantage of semantic web technologies, in order to provide models with the required dynamism to overcome the issues related to the constant changes in data and business models. Using such techniques allows the system to be agnostic to the data model and business rules. The proposed solution includes the proposed constraints, application ontology, and semantic rule templates. The paper includes a case study based on real data that illustrates the advantages of using the proposed solution in a community with 27 consumers.

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Section: Application Ontologymentioning

confidence: 99%

“…These datatype properties are agnostic to any class and vice versa, leaving the decision to use them and where to use them to the ontology engineer. Finally, the details about the remaining classes, object and datatype properties used from EMO, CfP, and EMR are available in [50,52].…”

Section: Application Ontologymentioning

confidence: 99%

Constrained Generation Bids in Local Electricity Markets: A Semantic Approach

et al. 2020

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“…In addition, to achieve interoperability between systems, different MAS use ontologies that allow the sharing of vocabulary and mapping of concepts between systems, so that they can communicate. The ontologies are formulated in OWL DL, with representation in RDF/XML and are presented in [45]. In order to allow the interoperability between the systems, ontologies enable them to speak the same language and to understand the same concepts and terms, preventing different interpretations of the same information.…”

Section: Mass Societymentioning

confidence: 99%

Multi-Agent-Based CBR Recommender System for Intelligent Energy Management in Buildings

Pinto

Faia

Navarro-Cáceres

et al. 2019

IEEE Systems Journal

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This paper proposes a novel case-based reasoning (CBR) recommender system for intelligent energy management in buildings. The proposed approach recommends the amount of energy reduction that should be applied in a building in each moment, by learning from previous similar cases. The k-nearest neighbor clustering algorithm is applied to identify the most similar past cases, and an approach based on support vector machines is used to optimize the weight of different parameters that characterize each case. An expert system composed by a set of ad hoc rules guarantees that the solution is adequate and applicable to the new case scenario. The proposed CBR methodology is modeled through a dedicated software agent, thus enabling its integration in a multi-agent systems society for the study of energy systems. Results show that the proposed approach is able to provide suitable recommendations on energy reduction, by comparing its results with a previous approach based on particle swarm optimization and with the real reduction in past cases. The applicability of the proposed approach in real scenarios is also assessed through the application of the results provided by the proposed approach on a house energy resources management system. Index Terms-Building energy management, case-based reasoning (CBR), energy efficiency, multi-agent systems (MAS).

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“…Aggregator involvement in energy markets increases the access of a small resource to them, enabling case studies to be presented for flexibility of demand [19,20]. Real-time simulations [21,22] have applications to control theory. In fact, this work analyzes the way in which the players' features are modeled, particularly in their small-scale performance, thus simplifying the simulations while preserving the quality of the results.…”

Section: Introductionmentioning

confidence: 99%

Fault-Tolerant Temperature Control Algorithm for IoT Networks in Smart Buildings

et al. 2018

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The monitoring of the Internet of things networks depends to a great extent on the availability and correct functioning of all the network nodes that collect data. This network nodes all of which must correctly satisfy their purpose to ensure the efficiency and high quality of monitoring and control of the internet of things networks. This paper focuses on the problem of fault-tolerant maintenance of a networked environment in the domain of the internet of things. Based on continuous-time Markov chains, together with a cooperative control algorithm, a novel feedback model-based predictive hybrid control algorithm is proposed to improve the maintenance and reliability of the internet of things network. Virtual sensors are substituted for the sensors that the algorithm predicts will not function properly in future time intervals; this allows for maintaining reliable monitoring and control of the internet of things network. In this way, the internet of things network improves its robustness since our fault tolerant control algorithm finds the malfunction nodes that are collecting incorrect data and self-correct this issue replacing malfunctioning sensors with new ones. In addition, the proposed model is capable of optimising sensor positioning. As a result, data collection from the environment can be kept stable. The developed continuous-time control model is applied to guarantee reliable monitoring and control of temperature in a smart supermarket. Finally, the efficiency of the presented approach is verified with the results obtained in the conducted case study.

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An Interoperable Approach for Energy Systems Simulation: Electricity Market Participation Ontologies

Cited by 15 publications

References 21 publications

Constrained Generation Bids in Local Electricity Markets: A Semantic Approach

Constrained Generation Bids in Local Electricity Markets: A Semantic Approach

Multi-Agent-Based CBR Recommender System for Intelligent Energy Management in Buildings

Fault-Tolerant Temperature Control Algorithm for IoT Networks in Smart Buildings

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