Electric end-user consumer profit maximization: An online approach

Alahyari, Arman; Pozo, David

doi:10.1016/j.ijepes.2020.106502

Cited by 5 publications

(4 citation statements)

References 23 publications

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“…Besides, the system resiliency index can be defined as Equation (44) and is the ratio of the total number of the formed efficient modules with the highest independency feature and maximum load provision to total consumptions of system active loads. The denominator of this fraction states that for achieving maximum resiliency in the network, each load point should be included in a separate independent module.…”

Section: Objective Functionmentioning

confidence: 99%

“…The impact of switching capability and load control options in improving system resiliency index, considering different strategies, is depicted in Figure 8. Note that resiliency metric is calculated according to Equation (44). Based on the results, in the first strategy, which only considers DG installation, for budget levels 5 to 10, no improvement is achieved.…”

Section: Case IImentioning

confidence: 99%

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A novel resource allocation model based on the modularity concept for resiliency enhancement in electric distribution networks

et al. 2021

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Paying attention to the modularity feature of electric distribution systems improves their performance against severe events and makes an outstanding opportunity for resiliency enhancement. In this paper, a novel framework based on the modularity concept is proposed in which, by deploying smart grid technologies and forming efficient modules, effective and robust energy in distribution systems is provided. Optimal placement of distributed generation (DG) resources, load control options, switching devices, and tie lines are simultaneously incorporated in the proposed linear allocation model. To consider electrical and topological characteristics in the independent functioning of the formed modules, a path-based method is employed. The effectiveness and computability of the proposed algorithm are examined by performing several simulations on two modified 37-bus and 84-bus test systems. The results demonstrate that the developed modular structure, by subdividing the system into several independent parts, creates more flexibility for the recovery process and facilitates the self-healing capabilities.

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Section: Objective Functionmentioning

confidence: 99%

Section: Case IImentioning

confidence: 99%

A novel resource allocation model based on the modularity concept for resiliency enhancement in electric distribution networks

et al. 2021

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“…Alahyari and Pozo [18] presented an approach for maximizing the profits for electricity consumers participating in a demand response program. A real-time electricity price is assumed so that the price for the next hours is not known at the time of planning the demand response actions.…”

Section: Introductionmentioning

confidence: 99%

“…The proposed framework is able to use a forecast of such a real-time price and is able to cope with uncertainties in the forecast. Thus, the approach presented in this paper could be directly exploited in the demand response optimization proposed by Alahyari and Pozo [18]. Moving to real-time spot prices, such as prices that change every 5 min, motivates a rethinking of energy management approaches to address a real-time timeframe.…”

Section: Introductionmentioning

confidence: 99%

Robust Multi-Step Predictor for Electricity Markets with Real-Time Pricing

et al. 2021

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Real-time electricity pricing mechanisms are emerging as a key component of the smart grid. However, prior work has not fully addressed the challenges of multi-step prediction (Predicting multiple time steps into the future) that is accurate, robust and real-time. This paper proposes a novel Artificial Intelligence-based approach, Robust Intelligent Price Prediction in Real-time (RIPPR), that overcomes these challenges. RIPPR utilizes Variational Mode Decomposition (VMD) to transform the spot price data stream into sub-series that are optimized for robustness using the particle swarm optimization (PSO) algorithm. These sub-series are inputted to a Random Vector Functional Link neural network algorithm for real-time multi-step prediction. A mirror extension removal of VMD, including continuous and discrete spaces in the PSO, is a further novel contribution that improves the effectiveness of RIPPR. The superiority of the proposed RIPPR is demonstrated using three empirical studies of multi-step price prediction of the Australian electricity market.

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Electric end-user consumer profit maximization: An online approach

Cited by 5 publications

References 23 publications

A novel resource allocation model based on the modularity concept for resiliency enhancement in electric distribution networks

A novel resource allocation model based on the modularity concept for resiliency enhancement in electric distribution networks

Robust Multi-Step Predictor for Electricity Markets with Real-Time Pricing

Electricity procurement of large consumers considering power-purchase agreements

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