Uncertainty-Aware Model Predictive Control for Residential Buildings Participating in Intraday Markets

Tarnate, Wilbert Rey D.; Ponci, Ferdinanda; Monti, Antonello

doi:10.1109/access.2022.3140598

Cited by 2 publications

(4 citation statements)

References 31 publications

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“…The steps to perform market trading simulations are a useful high-level overview for this paper. An uncertainty predictive control model for residential buildings to participate in intraday markets is in [16]. The paper shows how residential buildings can actively participate in an intraday market so that -and aligned with the interest of this paper -future aggregators might be able to execute market commitment even though residential buildings are often inflexible-price demands.…”

Section: Introductionmentioning

confidence: 86%

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An Intraday Market Design for Colombia’s Energy Transition

2022

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The massive promotion of intermittent renewable resources as a decarbonization strategy for economies has led to the need to reconsider current market designs in order to facilitate the integration of this kind of production technology. The intraday market has established itself as an efficient mechanism for these purposes, as has been seen in diverse international experiences, principally Europe. The Colombian electricity market is no stranger to the needs of these reforms, as the National Energy and Mining Planning Office of Colombia (UPME in Spanish) estimates that by 2034 almost 30% of the electricity generation matrix will be comprised of intermittent renewable resources. This paper develops several elements to be considered for the implementation of an intraday market in Colombia, backed with quantitative information, contrary to previous studies that have based their recommendations on qualitative elements. The number of discrete intraday sessions, the effect of changing from a sequential energy and reserve allocation scheme to a cooptimized one, as well as the adjustment mechanism -or a balance mechanism -after the gate closure are, among other aspects, analyzed in this study. The computational simulations executed with real data from two operating months with different characteristics in terms of prices, unavailable assets -a liquidity factor for the new market -and system contingencies support the design elements developed in this study. That is, the proposed design -four sections, co-optimization of energy and reserve, and an adjustment mechanism that is not based only on the use of reserves -tested with real data confirm that this proposal is more convenient than the other kind of design from an operating cost and unavailability management perspective. The results reveal market design elements that must be considered in Colombia and serve as input for other countriesparticularly Latin American countries -that are in the process of updating their electricity market designs as part of the current energy transition. INDEX TERMS electricity market reform, Colombian electricity market, intraday electricity market design, renewable energy penetrationNOMENCLATURE -Set of resources that do not modify their offer price and availability for an intraday session s B. PARAMETERS PO .,0 12

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Section: Introductionmentioning

confidence: 86%

“…This is so that the unit, by having this type of reserve allocation, has the capacity to perform the service when required. Likewise, equation (16) establishes that the unit has sufficient capacity in case it has a secondary or tertiary reserve allocation to be decreased.…”

Section: Allocation Modelmentioning

confidence: 99%

An Intraday Market Design for Colombia’s Energy Transition

2022

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“…The optimization of solar power systems has been an active area of research in recent years due to the increasing demand for renewable energy sources [7]. Various control strategies have been proposed to improve the performance and efficiency of load-connected solar deployments [8,9]. In this section, the author reviews some related work in solar power control models [10][11][12].…”

Section: Review Of Existing Control Modelmentioning

confidence: 99%

“…These features are further processed via equations ( 8) and (9), where an augmented set of forgetting (z) and retaining (r) features are estimated as follows,…”

Section: Conversion Of Collected Samples Into Multi-modal Feature Setsmentioning

confidence: 99%

EPCMSDB: Design of an ensemble predictive control model for solar PV MPPT deployments via dual bioinspired optimizations

Hole,

Das Goswami

2024

Sci. Tech. Energ. Transition

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With the increasing demand for renewable energy, solar power has emerged as a promising option for sustainable power generation. However, the effectiveness and efficiency of solar power systems rely on the ability to effectively manage their performance, making it essential to develop efficient control models. This paper proposes a novel ensemble predictive control model for solar deployments using bio-inspired optimizations to improve load-connected solar deployments’ performance. The proposed model integrates multiple control devices, including Maximum Power Point Tracker, Proportional-Integral-Derivative, Proportional-Integral, and Fuzzy Logic Controllers, to selectively control the solar Photovoltaic systems. The proposed model incorporates a predictive control operation utilizing an LSTM-GRU (Long Short-Term Memory-Gated Recurrent Unit) with the VARMA (Vector Auto-Regressive Moving Average) model, which can accurately predict the future power generation of the solar system. This feature can facilitate efficient energy management and increase the system’s performance for different use cases. Implement a SEPIC (Single Ended Primary Inductor Capacitor) converter design to improve the system’s overall efficiency levels. To validate the effectiveness of the proposed approach, the author conducted experiments using real-world data and compared the proposed results with other control strategies. The results demonstrate that the ensemble predictive control model based on bio-inspired optimizations outperforms the existing control models regarding accuracy, efficiency, and stability levels. The proposed model has the potential to significantly improve the performance of load-connected solar deployments, offering a more practical approach to solar power generation. The combination of predictive control operations with bio-inspired optimizations can facilitate the design of sustainable energy systems with higher efficiency and accuracy.

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Uncertainty-Aware Model Predictive Control for Residential Buildings Participating in Intraday Markets

Cited by 2 publications

References 31 publications

An Intraday Market Design for Colombia’s Energy Transition

An Intraday Market Design for Colombia’s Energy Transition

EPCMSDB: Design of an ensemble predictive control model for solar PV MPPT deployments via dual bioinspired optimizations

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