The Experts below are selected from a list of 15579 Experts worldwide ranked by ideXlab platform
Vincent H Poor - One of the best experts on this subject based on the ideXlab platform.
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managing price uncertainty in prosumer centric energy trading a prospect theoretic stackelberg game approach
IEEE Transactions on Smart Grid, 2019Co-Authors: Georges El Rahi, Walid Saad, Narayan B. Mandayam, Rasoul S Etesami, Vincent H PoorAbstract:In this paper, the problem of energy trading between smart grid prosumers, who can simultaneously consume and produce energy, and a grid power company is studied. The problem is formulated as a single-leader, multiple-follower Stackelberg game between the power company and multiple prosumers. In this game, the power company acts as a leader who determines the pricing strategy that maximizes its profits, while the prosumers act as followers who react by choosing the amount of energy to buy or sell so as to optimize their current and future profits. The proposed game accounts for each prosumer’s subjective decision when faced with the uncertainty of profits, induced by the random future price. In particular, the Framing Effect, from the framework of prospect theory (PT), is used to account for each prosumer’s valuation of its gains and losses with respect to an individual utility reference point. The reference point changes between prosumers and stems from their past experience and future aspirations of profits. The followers’ noncooperative game is shown to admit a unique pure-strategy Nash equilibrium (NE) under classical game theory which is obtained using a fully distributed algorithm. The results are extended to account for the case of PT using algorithmic solutions that can achieve an NE under certain conditions. Simulation results show that the total grid load varies significantly with the prosumers’ reference point and their loss-aversion level. In addition, it is shown that the power company’s profits considerably decrease when it fails to account for the prosumers’ subjective perceptions under PT.
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prospect theory for enhanced smart grid resilience using distributed energy storage
arXiv: Computer Science and Game Theory, 2016Co-Authors: Georges El Rahi, Walid Saad, Narayan B. Mandayam, Anibal Sanjab, Vincent H PoorAbstract:The proliferation of distributed generation and storage units is leading to the development of local, small-scale distribution grids, known as microgrids (MGs). In this paper, the problem of optimizing the energy trading decisions of MG operators (MGOs) is studied using game theory. In the formulated game, each MGO chooses the amount of energy that must be sold immediately or stored for future emergencies, given the prospective market prices which are influenced by other MGOs' decisions. The problem is modeled using a Bayesian game to account for the incomplete information that MGOs have about each others' levels of surplus. The proposed game explicitly accounts for each MGO's subjective decision when faced with the uncertainty of its opponents' energy surplus. In particular, the so-called Framing Effect, from the framework of prospect theory (PT), is used to account for each MGO's valuation of its gains and losses with respect to an individual utility reference point. The reference point is typically different for each individual and originates from its past experiences and future aspirations. A closed-form expression for the Bayesian Nash equilibrium is derived for the standard game formulation. Under PT, a best response algorithm is proposed to find the equilibrium. Simulation results show that, depending on their individual reference points, MGOs can tend to store more or less energy under PT compared to classical game theory. In addition, the impact of the reference point is found to be more prominent as the emergency price set by the power company increases.
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prospect theory for prosumer centric energy trading in the smart grid
IEEE PES Innovative Smart Grid Technologies Conference, 2016Co-Authors: Georges El Rahi, Walid Saad, Arnold L. Glass, Narayan B. Mandayam, Vincent H PoorAbstract:In this paper, the problem of energy trading between smart grid prosumers that can simultaneously consume and produce energy is studied. The problem is formulated as a noncooperative game between prosumers whose goal is to meet their energy demands at minimum cost by optimally utilizing their storage units and renewable (wind) energy sources. In this game, each prosumer will declare the amount of energy that will be sold or bought to maximize a utility function that captures the tradeoff between the profits gained from selling energy and the penalty incurred for failing to meet the declared amount, due to the stochastic nature of wind energy. The proposed game explicitly accounts for each prosumer's subjective perceptions using the framework of prospect theory (PT). In particular, a prosumer's perception of the probability of its possible profits from trading energy is captured via the weighting Effect. In addition, the prosumer's valuation of its gains and losses with respect to its own preferences is captured via the so-called Framing Effect. To find the equilibrium of this game, a best response algorithm is proposed. Simulation results show the difference in prosumer behavior using traditional game-theoretic and prospect-theoretic analysis. In particular, the results show that probability weighting increases the sensitivity of the prosumers to penalties. Moreover, under PT, a prosumer tends to sell less energy compared to a conventional game-theoretic scenario.
Georges El Rahi - One of the best experts on this subject based on the ideXlab platform.
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managing price uncertainty in prosumer centric energy trading a prospect theoretic stackelberg game approach
IEEE Transactions on Smart Grid, 2019Co-Authors: Georges El Rahi, Walid Saad, Narayan B. Mandayam, Rasoul S Etesami, Vincent H PoorAbstract:In this paper, the problem of energy trading between smart grid prosumers, who can simultaneously consume and produce energy, and a grid power company is studied. The problem is formulated as a single-leader, multiple-follower Stackelberg game between the power company and multiple prosumers. In this game, the power company acts as a leader who determines the pricing strategy that maximizes its profits, while the prosumers act as followers who react by choosing the amount of energy to buy or sell so as to optimize their current and future profits. The proposed game accounts for each prosumer’s subjective decision when faced with the uncertainty of profits, induced by the random future price. In particular, the Framing Effect, from the framework of prospect theory (PT), is used to account for each prosumer’s valuation of its gains and losses with respect to an individual utility reference point. The reference point changes between prosumers and stems from their past experience and future aspirations of profits. The followers’ noncooperative game is shown to admit a unique pure-strategy Nash equilibrium (NE) under classical game theory which is obtained using a fully distributed algorithm. The results are extended to account for the case of PT using algorithmic solutions that can achieve an NE under certain conditions. Simulation results show that the total grid load varies significantly with the prosumers’ reference point and their loss-aversion level. In addition, it is shown that the power company’s profits considerably decrease when it fails to account for the prosumers’ subjective perceptions under PT.
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prospect theory for enhanced smart grid resilience using distributed energy storage
arXiv: Computer Science and Game Theory, 2016Co-Authors: Georges El Rahi, Walid Saad, Narayan B. Mandayam, Anibal Sanjab, Vincent H PoorAbstract:The proliferation of distributed generation and storage units is leading to the development of local, small-scale distribution grids, known as microgrids (MGs). In this paper, the problem of optimizing the energy trading decisions of MG operators (MGOs) is studied using game theory. In the formulated game, each MGO chooses the amount of energy that must be sold immediately or stored for future emergencies, given the prospective market prices which are influenced by other MGOs' decisions. The problem is modeled using a Bayesian game to account for the incomplete information that MGOs have about each others' levels of surplus. The proposed game explicitly accounts for each MGO's subjective decision when faced with the uncertainty of its opponents' energy surplus. In particular, the so-called Framing Effect, from the framework of prospect theory (PT), is used to account for each MGO's valuation of its gains and losses with respect to an individual utility reference point. The reference point is typically different for each individual and originates from its past experiences and future aspirations. A closed-form expression for the Bayesian Nash equilibrium is derived for the standard game formulation. Under PT, a best response algorithm is proposed to find the equilibrium. Simulation results show that, depending on their individual reference points, MGOs can tend to store more or less energy under PT compared to classical game theory. In addition, the impact of the reference point is found to be more prominent as the emergency price set by the power company increases.
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prospect theory for prosumer centric energy trading in the smart grid
IEEE PES Innovative Smart Grid Technologies Conference, 2016Co-Authors: Georges El Rahi, Walid Saad, Arnold L. Glass, Narayan B. Mandayam, Vincent H PoorAbstract:In this paper, the problem of energy trading between smart grid prosumers that can simultaneously consume and produce energy is studied. The problem is formulated as a noncooperative game between prosumers whose goal is to meet their energy demands at minimum cost by optimally utilizing their storage units and renewable (wind) energy sources. In this game, each prosumer will declare the amount of energy that will be sold or bought to maximize a utility function that captures the tradeoff between the profits gained from selling energy and the penalty incurred for failing to meet the declared amount, due to the stochastic nature of wind energy. The proposed game explicitly accounts for each prosumer's subjective perceptions using the framework of prospect theory (PT). In particular, a prosumer's perception of the probability of its possible profits from trading energy is captured via the weighting Effect. In addition, the prosumer's valuation of its gains and losses with respect to its own preferences is captured via the so-called Framing Effect. To find the equilibrium of this game, a best response algorithm is proposed. Simulation results show the difference in prosumer behavior using traditional game-theoretic and prospect-theoretic analysis. In particular, the results show that probability weighting increases the sensitivity of the prosumers to penalties. Moreover, under PT, a prosumer tends to sell less energy compared to a conventional game-theoretic scenario.
Scott A Huettel - One of the best experts on this subject based on the ideXlab platform.
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reason s enemy is not emotion engagement of cognitive control networks explains biases in gain loss Framing
The Journal of Neuroscience, 2017Co-Authors: David V Smith, John A Clithero, Vinod Venkatraman, Mckell R Carter, Scott A HuettelAbstract:In the classic gain/loss Framing Effect, describing a gamble as a potential gain or loss biases people to make risk-averse or risk-seeking decisions, respectively. The canonical explanation for this Effect is that frames differentially modulate emotional processes, which in turn leads to irrational choice behavior. Here, we evaluate the source of Framing biases by integrating functional magnetic resonance imaging data from 143 human participants performing a gain/loss Framing task with meta-analytic data from >8000 neuroimaging studies. We found that activation during choices consistent with the Framing Effect were most correlated with activation associated with the resting or default brain, while activation during choices inconsistent with the Framing Effect was most correlated with the task-engaged brain. Our findings argue against the common interpretation of gain/loss Framing as a competition between emotion and control. Instead, our study indicates that this Effect results from differential cognitive engagement across decision frames.SIGNIFICANCE STATEMENT The biases frequently exhibited by human decision makers have often been attributed to the presence of emotion. Using a large fMRI sample and analysis of whole-brain networks defined with the meta-analytic tool Neurosynth, we find that neural activity during frame-biased decisions was more significantly associated with default behaviors (and the absence of executive control) than with emotion. These findings point to a role for neuroscience in shaping long-standing psychological theories in decision science.
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reason s enemy is not emotion engagement of cognitive control networks explains biases in gain loss Framing
Social Science Research Network, 2017Co-Authors: David V Smith, John A Clithero, Vinod Venkatraman, Mckell R Carter, Scott A HuettelAbstract:In the classic gain/loss Framing Effect, describing a gamble as a potential gain or loss biases people to make risk-averse or risk-seeking decisions, respectively. The canonical explanation for this Effect is that frames differentially modulate emotional processes — which in turn leads to irrational choice behavior. Here, we evaluate the source of Framing biases by integrating functional magnetic resonance imaging (fMRI) data from 143 human participants performing a gain/loss Framing task with meta-analytic data from over 8000 neuroimaging studies. We found that activation during choices consistent with the Framing Effect were most correlated with activation associated with the resting or default brain, while activation during choices inconsistent with the Framing Effect most correlated with the task-engaged brain. Our findings argue against the common interpretation of gain/loss Framing as a competition between emotion and control. Instead, our study indicates that this Effect results from differential cognitive engagement across decision frames. Significance Statement: The biases frequently exhibited by human decision-makers have often been attributed to the presence of emotion. Using a large fMRI sample and analysis of whole-brain networks defined with the meta-analytic tool Neurosynth, we find that neural activity during frame-biased decisions are more significantly associated with default behaviors (and the absence of executive control) than with emotion. These findings point to a role for neuroscience in shaping longstanding psychological theories in decision science.
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reason s enemy is not emotion engagement of cognitive control networks explains biases in gain loss Framing
bioRxiv, 2017Co-Authors: David V Smith, John A Clithero, Vinod Venkatraman, Mckell R Carter, Scott A HuettelAbstract:In the classic gain/loss Framing Effect, describing a gamble as a potential gain or loss biases people to make risk-averse or risk-seeking decisions, respectively. The canonical explanation for this Effect is that frames differentially modulate emotional processes -- which in turn leads to irrational choice behavior. Here, we evaluate the source of Framing biases by integrating functional magnetic resonance imaging (fMRI) data from 143 human participants performing a gain/loss Framing task with meta-analytic data from over 8000 neuroimaging studies. We found that activation during choices consistent with the Framing Effect were most correlated with activation associated with the resting or default brain, while activation during choices inconsistent with the Framing Effect most correlated with the task-engaged brain. Our findings argue against the common interpretation of gain/loss Framing as a competition between emotion and control. Instead, our study indicates that this Effect results from differential cognitive engagement across decision frames.
Narayan B. Mandayam - One of the best experts on this subject based on the ideXlab platform.
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managing price uncertainty in prosumer centric energy trading a prospect theoretic stackelberg game approach
IEEE Transactions on Smart Grid, 2019Co-Authors: Georges El Rahi, Walid Saad, Narayan B. Mandayam, Rasoul S Etesami, Vincent H PoorAbstract:In this paper, the problem of energy trading between smart grid prosumers, who can simultaneously consume and produce energy, and a grid power company is studied. The problem is formulated as a single-leader, multiple-follower Stackelberg game between the power company and multiple prosumers. In this game, the power company acts as a leader who determines the pricing strategy that maximizes its profits, while the prosumers act as followers who react by choosing the amount of energy to buy or sell so as to optimize their current and future profits. The proposed game accounts for each prosumer’s subjective decision when faced with the uncertainty of profits, induced by the random future price. In particular, the Framing Effect, from the framework of prospect theory (PT), is used to account for each prosumer’s valuation of its gains and losses with respect to an individual utility reference point. The reference point changes between prosumers and stems from their past experience and future aspirations of profits. The followers’ noncooperative game is shown to admit a unique pure-strategy Nash equilibrium (NE) under classical game theory which is obtained using a fully distributed algorithm. The results are extended to account for the case of PT using algorithmic solutions that can achieve an NE under certain conditions. Simulation results show that the total grid load varies significantly with the prosumers’ reference point and their loss-aversion level. In addition, it is shown that the power company’s profits considerably decrease when it fails to account for the prosumers’ subjective perceptions under PT.
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prospect theory for enhanced smart grid resilience using distributed energy storage
arXiv: Computer Science and Game Theory, 2016Co-Authors: Georges El Rahi, Walid Saad, Narayan B. Mandayam, Anibal Sanjab, Vincent H PoorAbstract:The proliferation of distributed generation and storage units is leading to the development of local, small-scale distribution grids, known as microgrids (MGs). In this paper, the problem of optimizing the energy trading decisions of MG operators (MGOs) is studied using game theory. In the formulated game, each MGO chooses the amount of energy that must be sold immediately or stored for future emergencies, given the prospective market prices which are influenced by other MGOs' decisions. The problem is modeled using a Bayesian game to account for the incomplete information that MGOs have about each others' levels of surplus. The proposed game explicitly accounts for each MGO's subjective decision when faced with the uncertainty of its opponents' energy surplus. In particular, the so-called Framing Effect, from the framework of prospect theory (PT), is used to account for each MGO's valuation of its gains and losses with respect to an individual utility reference point. The reference point is typically different for each individual and originates from its past experiences and future aspirations. A closed-form expression for the Bayesian Nash equilibrium is derived for the standard game formulation. Under PT, a best response algorithm is proposed to find the equilibrium. Simulation results show that, depending on their individual reference points, MGOs can tend to store more or less energy under PT compared to classical game theory. In addition, the impact of the reference point is found to be more prominent as the emergency price set by the power company increases.
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prospect theory for prosumer centric energy trading in the smart grid
IEEE PES Innovative Smart Grid Technologies Conference, 2016Co-Authors: Georges El Rahi, Walid Saad, Arnold L. Glass, Narayan B. Mandayam, Vincent H PoorAbstract:In this paper, the problem of energy trading between smart grid prosumers that can simultaneously consume and produce energy is studied. The problem is formulated as a noncooperative game between prosumers whose goal is to meet their energy demands at minimum cost by optimally utilizing their storage units and renewable (wind) energy sources. In this game, each prosumer will declare the amount of energy that will be sold or bought to maximize a utility function that captures the tradeoff between the profits gained from selling energy and the penalty incurred for failing to meet the declared amount, due to the stochastic nature of wind energy. The proposed game explicitly accounts for each prosumer's subjective perceptions using the framework of prospect theory (PT). In particular, a prosumer's perception of the probability of its possible profits from trading energy is captured via the weighting Effect. In addition, the prosumer's valuation of its gains and losses with respect to its own preferences is captured via the so-called Framing Effect. To find the equilibrium of this game, a best response algorithm is proposed. Simulation results show the difference in prosumer behavior using traditional game-theoretic and prospect-theoretic analysis. In particular, the results show that probability weighting increases the sensitivity of the prosumers to penalties. Moreover, under PT, a prosumer tends to sell less energy compared to a conventional game-theoretic scenario.
Walid Saad - One of the best experts on this subject based on the ideXlab platform.
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managing price uncertainty in prosumer centric energy trading a prospect theoretic stackelberg game approach
IEEE Transactions on Smart Grid, 2019Co-Authors: Georges El Rahi, Walid Saad, Narayan B. Mandayam, Rasoul S Etesami, Vincent H PoorAbstract:In this paper, the problem of energy trading between smart grid prosumers, who can simultaneously consume and produce energy, and a grid power company is studied. The problem is formulated as a single-leader, multiple-follower Stackelberg game between the power company and multiple prosumers. In this game, the power company acts as a leader who determines the pricing strategy that maximizes its profits, while the prosumers act as followers who react by choosing the amount of energy to buy or sell so as to optimize their current and future profits. The proposed game accounts for each prosumer’s subjective decision when faced with the uncertainty of profits, induced by the random future price. In particular, the Framing Effect, from the framework of prospect theory (PT), is used to account for each prosumer’s valuation of its gains and losses with respect to an individual utility reference point. The reference point changes between prosumers and stems from their past experience and future aspirations of profits. The followers’ noncooperative game is shown to admit a unique pure-strategy Nash equilibrium (NE) under classical game theory which is obtained using a fully distributed algorithm. The results are extended to account for the case of PT using algorithmic solutions that can achieve an NE under certain conditions. Simulation results show that the total grid load varies significantly with the prosumers’ reference point and their loss-aversion level. In addition, it is shown that the power company’s profits considerably decrease when it fails to account for the prosumers’ subjective perceptions under PT.
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prospect theory for enhanced smart grid resilience using distributed energy storage
arXiv: Computer Science and Game Theory, 2016Co-Authors: Georges El Rahi, Walid Saad, Narayan B. Mandayam, Anibal Sanjab, Vincent H PoorAbstract:The proliferation of distributed generation and storage units is leading to the development of local, small-scale distribution grids, known as microgrids (MGs). In this paper, the problem of optimizing the energy trading decisions of MG operators (MGOs) is studied using game theory. In the formulated game, each MGO chooses the amount of energy that must be sold immediately or stored for future emergencies, given the prospective market prices which are influenced by other MGOs' decisions. The problem is modeled using a Bayesian game to account for the incomplete information that MGOs have about each others' levels of surplus. The proposed game explicitly accounts for each MGO's subjective decision when faced with the uncertainty of its opponents' energy surplus. In particular, the so-called Framing Effect, from the framework of prospect theory (PT), is used to account for each MGO's valuation of its gains and losses with respect to an individual utility reference point. The reference point is typically different for each individual and originates from its past experiences and future aspirations. A closed-form expression for the Bayesian Nash equilibrium is derived for the standard game formulation. Under PT, a best response algorithm is proposed to find the equilibrium. Simulation results show that, depending on their individual reference points, MGOs can tend to store more or less energy under PT compared to classical game theory. In addition, the impact of the reference point is found to be more prominent as the emergency price set by the power company increases.
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prospect theory for prosumer centric energy trading in the smart grid
IEEE PES Innovative Smart Grid Technologies Conference, 2016Co-Authors: Georges El Rahi, Walid Saad, Arnold L. Glass, Narayan B. Mandayam, Vincent H PoorAbstract:In this paper, the problem of energy trading between smart grid prosumers that can simultaneously consume and produce energy is studied. The problem is formulated as a noncooperative game between prosumers whose goal is to meet their energy demands at minimum cost by optimally utilizing their storage units and renewable (wind) energy sources. In this game, each prosumer will declare the amount of energy that will be sold or bought to maximize a utility function that captures the tradeoff between the profits gained from selling energy and the penalty incurred for failing to meet the declared amount, due to the stochastic nature of wind energy. The proposed game explicitly accounts for each prosumer's subjective perceptions using the framework of prospect theory (PT). In particular, a prosumer's perception of the probability of its possible profits from trading energy is captured via the weighting Effect. In addition, the prosumer's valuation of its gains and losses with respect to its own preferences is captured via the so-called Framing Effect. To find the equilibrium of this game, a best response algorithm is proposed. Simulation results show the difference in prosumer behavior using traditional game-theoretic and prospect-theoretic analysis. In particular, the results show that probability weighting increases the sensitivity of the prosumers to penalties. Moreover, under PT, a prosumer tends to sell less energy compared to a conventional game-theoretic scenario.
