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Are Optimal Day-Ahead Markets Able to Face RES Uncertainty? : Evaluating Perfect Stochastic Energy Planning Models. / Morales-España, Germán; Hobbs, Benjamin F.

2017. 1-6 Erasmus Energy Forum 2017, Rotterdam , Netherlands.

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Morales-España, G & Hobbs, BF 2017, 'Are Optimal Day-Ahead Markets Able to Face RES Uncertainty?: Evaluating Perfect Stochastic Energy Planning Models' Erasmus Energy Forum 2017, Rotterdam , Netherlands, 28/06/17 - 29/06/17, pp. 1-6.

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@conference{8ac829c9917141eea14746e1d1c33ced,
title = "Are Optimal Day-Ahead Markets Able to Face RES Uncertainty?: Evaluating Perfect Stochastic Energy Planning Models",
abstract = "Approximations made in day-ahead markets can result in suboptimal or even infeasible schedules for generating units and inaccurate predictions of actual costs and wind curtailment. Here we compare different optimal models of day-ahead markets based on unit commitment (UC) formulations, especially energy- vs. power-based UC; excluding or including startup and shutdown trajectories; and deterministic vs. “ideal” stochastic models to face wind uncertainty. The day-ahead hourly schedules are then evaluated against actual wind and load profiles using a (5-min) real-time dispatch model. We find that each simplification usually causes expected generation costs to increase by several percentage points, and results in significant understatement of expected wind curtailment and, in some cases, load interruptions",
author = "Germán Morales-España and Hobbs, {Benjamin F.}",
year = "2017",
month = "6",
pages = "1--6",

}

RIS

TY - CONF

T1 - Are Optimal Day-Ahead Markets Able to Face RES Uncertainty?

T2 - Evaluating Perfect Stochastic Energy Planning Models

AU - Morales-España,Germán

AU - Hobbs,Benjamin F.

PY - 2017/6/28

Y1 - 2017/6/28

N2 - Approximations made in day-ahead markets can result in suboptimal or even infeasible schedules for generating units and inaccurate predictions of actual costs and wind curtailment. Here we compare different optimal models of day-ahead markets based on unit commitment (UC) formulations, especially energy- vs. power-based UC; excluding or including startup and shutdown trajectories; and deterministic vs. “ideal” stochastic models to face wind uncertainty. The day-ahead hourly schedules are then evaluated against actual wind and load profiles using a (5-min) real-time dispatch model. We find that each simplification usually causes expected generation costs to increase by several percentage points, and results in significant understatement of expected wind curtailment and, in some cases, load interruptions

AB - Approximations made in day-ahead markets can result in suboptimal or even infeasible schedules for generating units and inaccurate predictions of actual costs and wind curtailment. Here we compare different optimal models of day-ahead markets based on unit commitment (UC) formulations, especially energy- vs. power-based UC; excluding or including startup and shutdown trajectories; and deterministic vs. “ideal” stochastic models to face wind uncertainty. The day-ahead hourly schedules are then evaluated against actual wind and load profiles using a (5-min) real-time dispatch model. We find that each simplification usually causes expected generation costs to increase by several percentage points, and results in significant understatement of expected wind curtailment and, in some cases, load interruptions

UR - http://resolver.tudelft.nl/uuid:8ac829c9-9171-41ee-a147-46e1d1c33ced

M3 - Other

SP - 1

EP - 6

ER -

ID: 20366779