Trust Model for a Multi-agent Based Simulation of Local Energy Markets

Andrade, Rui; Pinto, Tiago; Praça, Isabel

doi:10.1007/978-3-030-51999-5_15

Cited by 6 publications

(8 citation statements)

References 9 publications

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“…The trust model was developed and improved based on a previous work [2]. The objective of the trust module is to ensure that the participant's behavior is trustful and not malicious.…”

Section: Trust Toolmentioning

confidence: 99%

“…An improvement over the initial trust formula [2] is the addition of a fixed range parameter ( f r), in case vr creates an interval smaller than the one of f r them f r is used. The addition of f r helps to evaluate submissions with low value that could get falsely rejected.…”

Section: Trust Toolmentioning

confidence: 99%

“…In this paper, we studied the kinds of attacks that jeopardize the local energy markets; and we also studied the mechanisms to mitigate and eliminate some of these possible attacks. These security mechanisms are based on a Trust model [2] that tries to detect participants with malicious activities and forecasting models which provide predictions to be used by the trust model. A case study including 18 participants with different consumption and generation profiles is proposed, and a LEM Multi-Agent simulation framework called (LEMMAS) [2] was used to simulate market trading based on realistic data.…”

Section: Introductionmentioning

confidence: 99%

“…These security mechanisms are based on a Trust model [2] that tries to detect participants with malicious activities and forecasting models which provide predictions to be used by the trust model. A case study including 18 participants with different consumption and generation profiles is proposed, and a LEM Multi-Agent simulation framework called (LEMMAS) [2] was used to simulate market trading based on realistic data. The simulation was performed with and without malicious activities, in order to evaluate how the security mechanisms act in the different scenarios.…”

Section: Introductionmentioning

confidence: 99%

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The Impact of Attacks in LEM and Prevention Measures Based on Forecasting and Trust Models

Andrade¹,

Praça²,

Wannous³

et al. 2021

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In recent years Local Energy Markets (LEM) have emerged as an innovative and versatile energy trade solution. They bring benefits when renewable energy sources are used and are more flexible for consumers. There are, however, security concerns that put the feasibility of the local energy market at risk. One of these security challenges is the integrity of data in the smart-grid that supports the local market. In this article the LEM and the types of attacks that can have a negative impact on it are presented, and a security mechanism based on a trust model is proposed. A case study is elaborated using a multi-agent system called Local Energy Market Multi-Agent System (LEMMAS), capable of simulating the LEM and testing the proposed security mechanism.

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“…The trust model was developed and improved based on a previous work [2]. The objective of the trust module is to ensure that the participant's behavior is trustful and not malicious.…”

Section: Trust Toolmentioning

confidence: 99%

Section: Trust Toolmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

The Impact of Attacks in LEM and Prevention Measures Based on Forecasting and Trust Models

Andrade¹,

Praça²,

Wannous³

et al. 2021

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“…LEMMAS follows what is called an Institutional Trust model [18], that means there exists a centralized entity responsible for applying the trust model. In the case of LEMMAS this role is played by the MIM agent that acts as the centralized institution, and enforces the Trust model [1]. 4…”

Section: Trust Evaluationmentioning

confidence: 99%

A Two Tier Architecture for Local Energy Market Simulation and Control

Andrade¹,

García-Rodríguez

Praça³

et al. 2020

Communications in Computer and Information Science

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This paper addresses energy management and security having as basis sensing and monitoring of cyber-physical infrastructure of consumers and prosumers, and their participation in the Local Energy Market (LEM). The vision is to create a layered multi-agent framework that brings a complete view of the cyber-physical system of LEM participants, and provides optimization and control of energy for said participants. The proposed system is separated into a Market layer and a Cyber-Physical layer, each of them providing dierent services. The cyber-physical layer, represented by SMARTERCtrol system, provides Data Monitoring and Optimized Energy Control of individual building resources. The Market layer, represented by LEM Multi-Agent System, provides Negotiation, Forecasting, and Trust Evaluation. Both systems work together to provide and integrate a tool for simulation and control of LEM.

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