The Experts below are selected from a list of 3702 Experts worldwide ranked by ideXlab platform
Luis Baringo - One of the best experts on this subject based on the ideXlab platform.
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day ahead self scheduling of a Virtual Power Plant in energy and reserve electricity markets under uncertainty
IEEE Transactions on Power Systems, 2019Co-Authors: Ana Baringo, Luis Baringo, Jose M ArroyoAbstract:This paper proposes a novel model for the day-ahead self-scheduling problem of a Virtual Power Plant trading in both energy and reserve electricity markets. The Virtual Power Plant comprises a conventional Power Plant, an energy storage facility, a wind Power unit, and a flexible demand. This multi-component system participates in energy and reserve electricity markets as a single entity in order to optimize the use of energy resources. As a salient feature, the proposed model considers the uncertainty associated with the Virtual Power Plant being called upon by the system operator to deploy reserves. In addition, uncertainty in available wind Power generation and requests for reserve deployment is modeled using confidence bounds and intervals, respectively, while uncertainty in market prices is modeled using scenarios. The resulting model is thus cast as a stochastic adaptive robust optimization problem, which is solved using a column-and-constraint generation algorithm. Results from a case study illustrate the effectiveness of the proposed approach.
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a stochastic adaptive robust optimization approach for the offering strategy of a Virtual Power Plant
IEEE Transactions on Power Systems, 2017Co-Authors: Ana Baringo, Luis BaringoAbstract:This paper proposes a novel approach for the offering strategy of a Virtual Power Plant that participates in the day-ahead and the real-time energy markets. The Virtual Power Plant comprises a conventional Power Plant, a wind-Power unit, a storage facility, and flexible demands, which participate in the day-ahead and the real-time markets as a single entity in order to optimize their energy resources. We model the uncertainty in the wind-Power production and in the market prices using confidence bounds and scenarios, respectively, which allows us to formul-ate the strategic offering problem as a stochastic adaptive robust optimization model. Results of a case study are provided to show the applicability of the proposed approach.
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strategic bidding for a Virtual Power Plant in the day ahead and real time markets a price taker robust optimization approach
IEEE Transactions on Power Systems, 2016Co-Authors: Morteza Rahimiyan, Luis BaringoAbstract:We consider an energy management system that controls a cluster of price-responsive demands. Besides these demands, it also manages a wind-Power Plant and an energy storage facility. Demands, wind-Power Plant, and energy storage facility are interconnected within a small size electric energy system equipped with smart grid technology and constitute a Virtual Power Plant that can strategically buy and sell energy in both the day-ahead and the real-time markets. To this end, we propose a two-stage procedure based on robust optimization. In the first stage, the bidding strategy in the day-ahead market is decided. In the second stage, and once the actual scheduling in the day-ahead market is known, we decide the bidding strategy in the real-time market for each hour of the day. We consider that the Virtual Power Plant behaves as a price taker in these markets. Robust optimization is used to deal with uncertainties in wind-Power production and market prices, which are represented through confidence bounds. Results of a realistic case study are provided to show the applicability of the proposed approach.
S M Moghaddastafreshi - One of the best experts on this subject based on the ideXlab platform.
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bidding strategy of Virtual Power Plant for participating in energy and spinning reserve markets part ii numerical analysis
IEEE Transactions on Power Systems, 2011Co-Authors: Elaheh Mashhour, S M MoghaddastafreshiAbstract:This paper is to evaluate the presented model in part I for bidding strategy of Virtual Power Plant (VPP) with centralized control in a joint market of energy and spinning reserve service. Two test VPPs are introduced and different scenarios are considered for markets prices. At first, the participation of VPP in only energy market is studied. Then, the spinning reserve market is taken into consideration and the bids of VPP in a joint market of energy and spinning reserve service is studied under different scenarios of markets prices and the results are analyzed. In all cases, the results show the effectiveness and the quality of the procedure and validate the proposed model.
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bidding strategy of Virtual Power Plant for participating in energy and spinning reserve markets part i problem formulation
IEEE Transactions on Power Systems, 2011Co-Authors: Elaheh Mashhour, S M MoghaddastafreshiAbstract:This paper addresses the bidding problem faced by a Virtual Power Plant (VPP) in a joint market of energy and spinning reserve service. The proposed bidding strategy is a non-equilibrium model based on the deterministic price-based unit commitment (PBUC) which takes the supply-demand balancing constraint and security constraints of VPP itself into account. The presented model creates a single operating profile from a composite of the parameters characterizing each distributed energy resources (DER), which is a component of VPP, and incorporates network constraints into its description of the capabilities of the portfolio. The presented model is a nonlinear mixed-integer programming with inter-temporal constraints and solved by genetic algorithm (GA).
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the opportunities for future Virtual Power Plant in the Power market a view point
International Conference on Clean Electrical Power, 2009Co-Authors: Elaheh Mashhour, S M MoghaddastafreshiAbstract:The share of Distributed Generator (DG) in the Power system generation is increasingly grown up. Due to the effects of DG on technical operation of the network and also considering the rapid extension of Power market in the world wide, it is necessary to contemplate both technical aspect of network operation and market transactions in DG operation. Through the concept of Virtual Power Plant (VPP), an aggregation of distributed energy resources that communicate with decentralized energy management system, the technical aspect of operation will be covered and participation of DG in the Power market will be facilitated. This paper is concentrated on market aspects of operation of DG. A general framework for future VPP is discussed which it can be included the various DG technologies in both medium and low voltage distribution networks. New market transactions at distribution level, Distribution Company (DisCo) market in which both energy and ancillary services can be traded, is discussed and participation of VPP in both DisCo and wholesale market is investigated. Moreover, the exchanging Power between wholesale market and DisCo market is briefly discussed.
Elaheh Mashhour - One of the best experts on this subject based on the ideXlab platform.
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bidding strategy of Virtual Power Plant for participating in energy and spinning reserve markets part ii numerical analysis
IEEE Transactions on Power Systems, 2011Co-Authors: Elaheh Mashhour, S M MoghaddastafreshiAbstract:This paper is to evaluate the presented model in part I for bidding strategy of Virtual Power Plant (VPP) with centralized control in a joint market of energy and spinning reserve service. Two test VPPs are introduced and different scenarios are considered for markets prices. At first, the participation of VPP in only energy market is studied. Then, the spinning reserve market is taken into consideration and the bids of VPP in a joint market of energy and spinning reserve service is studied under different scenarios of markets prices and the results are analyzed. In all cases, the results show the effectiveness and the quality of the procedure and validate the proposed model.
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bidding strategy of Virtual Power Plant for participating in energy and spinning reserve markets part i problem formulation
IEEE Transactions on Power Systems, 2011Co-Authors: Elaheh Mashhour, S M MoghaddastafreshiAbstract:This paper addresses the bidding problem faced by a Virtual Power Plant (VPP) in a joint market of energy and spinning reserve service. The proposed bidding strategy is a non-equilibrium model based on the deterministic price-based unit commitment (PBUC) which takes the supply-demand balancing constraint and security constraints of VPP itself into account. The presented model creates a single operating profile from a composite of the parameters characterizing each distributed energy resources (DER), which is a component of VPP, and incorporates network constraints into its description of the capabilities of the portfolio. The presented model is a nonlinear mixed-integer programming with inter-temporal constraints and solved by genetic algorithm (GA).
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the opportunities for future Virtual Power Plant in the Power market a view point
International Conference on Clean Electrical Power, 2009Co-Authors: Elaheh Mashhour, S M MoghaddastafreshiAbstract:The share of Distributed Generator (DG) in the Power system generation is increasingly grown up. Due to the effects of DG on technical operation of the network and also considering the rapid extension of Power market in the world wide, it is necessary to contemplate both technical aspect of network operation and market transactions in DG operation. Through the concept of Virtual Power Plant (VPP), an aggregation of distributed energy resources that communicate with decentralized energy management system, the technical aspect of operation will be covered and participation of DG in the Power market will be facilitated. This paper is concentrated on market aspects of operation of DG. A general framework for future VPP is discussed which it can be included the various DG technologies in both medium and low voltage distribution networks. New market transactions at distribution level, Distribution Company (DisCo) market in which both energy and ancillary services can be traded, is discussed and participation of VPP in both DisCo and wholesale market is investigated. Moreover, the exchanging Power between wholesale market and DisCo market is briefly discussed.
Igor Kuzle - One of the best experts on this subject based on the ideXlab platform.
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offering model for a Virtual Power Plant based on stochastic programming
Applied Energy, 2013Co-Authors: Hrvoje Pandžic, Juan M Morales, Antonio J Conejo, Igor KuzleAbstract:Abstract A Virtual Power Plant aggregates various local production/consumption units that act in the market as a single entity. This paper considers a Virtual Power Plant consisting of an intermittent source, a storage facility, and a dispatchable Power Plant. The Virtual Power Plant sells and purchases electricity in both the day-ahead and the balancing markets seeking to maximize its expected profit. Such model is mathematically rigorous, yet computationally efficient. The offering problem is cast as a two-stage stochastic mixed-integer linear programming model which maximizes the Virtual Power Plant expected profit. The uncertain parameters, including the Power output of the intermittent source and the market prices, are modeled via scenarios based upon historical data. The proposed model is applied to a realistic case study and conclusions are drawn.
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offering model for a Virtual Power Plant based on stochastic programming
Applied Energy, 2013Co-Authors: Hrvoje Pandžic, Juan M Morales, Antonio J Conejo, Igor KuzleAbstract:A Virtual Power Plant aggregates various local production/consumption units that act in the market as a single entity. This paper considers a Virtual Power Plant consisting of an intermittent source, a storage facility, and a dispatchable Power Plant. The Virtual Power Plant sells and purchases electricity in both the day-ahead and the balancing markets seeking to maximize its expected profit. Such model is mathematically rigorous, yet computationally efficient.
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Virtual Power Plant mid term dispatch optimization
Applied Energy, 2013Co-Authors: Hrvoje Pandžic, Igor Kuzle, Tomislav CapuderAbstract:Wind Power Plants incur practically zero marginal costs during their operation. However, variable and uncertain nature of wind results in significant problems when trying to satisfy the contracted quantities of delivered electricity. For this reason, wind Power Plants and other non-dispatchable Power sources are combined with dispatchable Power sources forming a Virtual Power Plant. This paper considers a weekly self-scheduling of a Virtual Power Plant composed of intermittent renewable sources, storage system and a conventional Power Plant. On the one hand, the Virtual Power Plant needs to fulfill its long-term bilateral contracts, while, on the other hand, it acts in the market trying to maximize its overall profit. The optimal dispatch problem is formulated as a mixed-integer linear programming model which maximizes the weekly Virtual Power Plant profit subject to the long-term bilateral contracts and technical constraints. The self-scheduling procedure is based on stochastic programming. The uncertainty of the wind Power and solar Power generation is settled by using pumped hydro storage in order to provide flexible operation, as well as by having a conventional Power Plant as a backup. The efficiency of the proposed model is rendered through a realistic case study and analysis of the results is provided. Additionally, the impact of different storage capacities and turbine/pump capacities of pumped storage are analyzed.
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the mixed integer linear optimization model of Virtual Power Plant operation
International Conference on the European Energy Market, 2011Co-Authors: Marko Zdrilic, Hrvoje Pandžic, Igor KuzleAbstract:The concept of Virtual Power Plant is developed for two prime reasons. First, to diversify the risk of not meeting the long-term electricity delivery contracts, and secondly to achieve better results on the electricity market. This paper regards the case in which a wind Power Plant and a solar Power Plant are joint together with a conventional gas Power Plant to act on the electricity market as a single agent. The problem is formulated as a mixed-integer linear programming model which incorporates long-term bilateral contracts with weekly forecasted hourly market prices. The aim of the optimization is to maximize the profit of the Virtual Power Plant. The efficiency of the proposed model is rendered through two case studies and detailed analysis is provided.
Ana Baringo - One of the best experts on this subject based on the ideXlab platform.
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day ahead self scheduling of a Virtual Power Plant in energy and reserve electricity markets under uncertainty
IEEE Transactions on Power Systems, 2019Co-Authors: Ana Baringo, Luis Baringo, Jose M ArroyoAbstract:This paper proposes a novel model for the day-ahead self-scheduling problem of a Virtual Power Plant trading in both energy and reserve electricity markets. The Virtual Power Plant comprises a conventional Power Plant, an energy storage facility, a wind Power unit, and a flexible demand. This multi-component system participates in energy and reserve electricity markets as a single entity in order to optimize the use of energy resources. As a salient feature, the proposed model considers the uncertainty associated with the Virtual Power Plant being called upon by the system operator to deploy reserves. In addition, uncertainty in available wind Power generation and requests for reserve deployment is modeled using confidence bounds and intervals, respectively, while uncertainty in market prices is modeled using scenarios. The resulting model is thus cast as a stochastic adaptive robust optimization problem, which is solved using a column-and-constraint generation algorithm. Results from a case study illustrate the effectiveness of the proposed approach.
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a stochastic adaptive robust optimization approach for the offering strategy of a Virtual Power Plant
IEEE Transactions on Power Systems, 2017Co-Authors: Ana Baringo, Luis BaringoAbstract:This paper proposes a novel approach for the offering strategy of a Virtual Power Plant that participates in the day-ahead and the real-time energy markets. The Virtual Power Plant comprises a conventional Power Plant, a wind-Power unit, a storage facility, and flexible demands, which participate in the day-ahead and the real-time markets as a single entity in order to optimize their energy resources. We model the uncertainty in the wind-Power production and in the market prices using confidence bounds and scenarios, respectively, which allows us to formul-ate the strategic offering problem as a stochastic adaptive robust optimization model. Results of a case study are provided to show the applicability of the proposed approach.
