Agent-based model for spot and balancing electricity markets

Kühnlenz, Florian; Nardelli, Pedro H. J.

doi:10.1109/iccw.2017.7962809

Cited by 5 publications

(7 citation statements)

References 13 publications

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“…In any case, our results reinforce the importance of the micro-grid aggregator as a signaler of the global system state information for a stable peer relation between prosumers in the micro-grid. We expect to further develop this simulation by adding generation capabilities in the prosumers together with a more complete market description, as indicated by our initial results [32].…”

Section: Discussion and Final Remarksmentioning

confidence: 99%

Demand Control Management in Microgrids: The Impact of Different Policies and Communication Network Topologies

Kühnlenz

Nardelli

Alves

2018

IEEE Systems Journal

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This work studies how the communication network between proactive consumers affects the power utilization and fairness in a simplified direct-current micro-grid model, composed by three coupled layers: physical (an electric circuit that represents a micro-grid), communication (a peer-to-peer network within the micro-grid) and regulatory (individual decision strategies). Our results show that, for optimal power utilization and fairness, a global knowledge about the system is needed, demonstrating the importance of a micro-grid aggregator to inform about the power consumption for different time periods.Index Terms-Communication networks, Agents-based systems, Network topology, Smart grids, Decision making. Our model is described as follows. The physical layer (a DC micro-grid) is a circuit composed by a power source and resistors in parallel. Individual agents (the proactive consumers, the "prosumers") can add, remove or keep the resistors they have. Agents' decisions aim at maximizing their own delivered power, which is a non-linear function dependent on the others' behavior, and they are based on (i) their internal state, (ii) their global state perception, (iii) the information received from their neighbors in the communication network, and (iv) a randomized selfishness related to their willingness of answering to a demand-side control request. Different peerto-peer communication network topologies and randomized communication errors in the deployment of micro-grids are important aspects to be included as in [17], [18]. But differently from other papers, we analyze here their systemic effects; for detailed results of communication network implementation in power grids using, for instance, spatial and/or temporal spectrum sharing, refer to [19]- [23].Looking at the proposed model, by individually modifying the peer-to-peer communication network topology and the demand-side management policies keeping fixed the other

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Section: Discussion and Final Remarksmentioning

confidence: 99%

Demand Control Management in Microgrids: The Impact of Different Policies and Communication Network Topologies

Kühnlenz

Nardelli

Alves

2018

IEEE Systems Journal

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“…In more systemic level, the impact of demand-side management was studied in [37], [61]- [64] following the lines presented in [28]. These results evince the existence of systemic emergent phenomena that are undesirable when operating power grids, mainly due to a combination between lack of coordination caused by poorly designed information signals.…”

Section: A Bcdc Energiamentioning

confidence: 99%

Energy Internet via Packetized Management: Enabling Technologies and Deployment Challenges

et al. 2019

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This paper investigates the possibility of building the Energy Internet via a packetized management of non-industrial loads. The proposed solution is based on the cyber-physical implementation of energy packets where flexible loads send use requests to an energy server. Based on the existing literature, we explain how and why this approach could scale up to interconnected micro-grids, also pointing out the challenges involved in relation to the physical deployment of electricity network. We then assess how machine-type wireless communications, as part of 5G and beyond systems, will achieve the low latency and ultra reliability needed by the micro-grid protection while providing the massive coverage needed by the packetized management. This more distributed grid organization also requires localized governance models. We cite few existing examples as local markets, energy communities and micro-operator that support such novel arrangements. We close the paper by providing an overview of ongoing activities that support the proposed vision and possible ways to move forward.

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“…We base our analysis on an agent-based model which was firstly introduced in [19] and will be extended with several features explained below. It includes producers, utilities and consumers, while evolving around three stages of interaction between them.…”

Section: Modelmentioning

confidence: 99%

“…Different from our previous work [19], this paper considers that users have the ability to change their electricity usage. This flexibility can be utilized to shift power consumption away from high-price times to low-price ones to minimize consumer costs.…”

Section: Flexibilitymentioning

confidence: 99%

Implementing flexible demand: Real-time price vs. market integration

Kühnlenz

Nardelli

Karhinen

et al. 2018

Energy

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This paper proposes an agent-based model that combines both spot and balancing electricity markets. From this model, we develop a multi-agent simulation to study the integration of the consumers' flexibility into the system. Our study identifies the conditions that real-time prices may lead to higher electricity costs, which in turn contradicts the usual claim that such a pricing scheme reduces cost.We show that such undesirable behavior is in fact systemic. Due to the existing structure of the wholesale market, the predicted demand that is used in the formation of the price is never realized since the flexible users will change their demand according to such established price.As the demand is never correctly predicted, the volume traded through the balancing markets increases, leading to higher overall costs. In this case, the system can sustain, and even benefit from, a small number of flexible users, but this solution can never upscale without increasing the total costs.To avoid this problem, we implement the so-called "exclusive groups". Our results illustrate the importance of rethinking the current practices so that flexibility can be successfully integrated considering scenarios with and without intermittent renewable sources. else if dif f 60(t) < −LIM IT then 43: priceH[t] ← min(price[t · 4 : t · 4 + 4]) 44: end if 45: end for 46: return priceH 47: end procedure

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Agent-based model for spot and balancing electricity markets

Cited by 5 publications

References 13 publications

Demand Control Management in Microgrids: The Impact of Different Policies and Communication Network Topologies

Demand Control Management in Microgrids: The Impact of Different Policies and Communication Network Topologies

Energy Internet via Packetized Management: Enabling Technologies and Deployment Challenges

Implementing flexible demand: Real-time price vs. market integration

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