2013 IEEE Grenoble Conference 2013
DOI: 10.1109/ptc.2013.6652496
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A stochastic economic dispatch model with renewable energies considering demand and generation uncertainties

Abstract: This paper proposes a methodology to model and solve the problem of stochastic economic dispatch incorporating renewable energies. In this context, demand and generation randomness (wind speed, solar radiation and rates of failure) are considered. Demand, wind speed, solar radiation and unavailability are modeled through Normal, Weibull, Beta and Uniform distributions respectively. The problem is therefore recognized as a stochastic process. Consequently, the cost of load shedding is considered. In order to de… Show more

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Cited by 13 publications
(9 citation statements)
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“…These authors study the distribution functions of the thermal generations. A methodology to obtain descriptive statistics for the main variables of interest considering the probabilistic nature of load and renewable energy is developed in [25]. However, [25] includes important restrictions, such as: (a) the use of linear cost functions, (b) solutions based on priority lists and rotational matrices, (c) models for wind speed distribution and irradiance, do not match the specific Chilean characteristics, (d) simple unavailability models that over penalize the wind energy contribution and (e) relatively simple outcomes consisting on means and standard deviations of the variables of interest.…”
Section: Introductionmentioning
confidence: 99%
See 1 more Smart Citation
“…These authors study the distribution functions of the thermal generations. A methodology to obtain descriptive statistics for the main variables of interest considering the probabilistic nature of load and renewable energy is developed in [25]. However, [25] includes important restrictions, such as: (a) the use of linear cost functions, (b) solutions based on priority lists and rotational matrices, (c) models for wind speed distribution and irradiance, do not match the specific Chilean characteristics, (d) simple unavailability models that over penalize the wind energy contribution and (e) relatively simple outcomes consisting on means and standard deviations of the variables of interest.…”
Section: Introductionmentioning
confidence: 99%
“…A methodology to obtain descriptive statistics for the main variables of interest considering the probabilistic nature of load and renewable energy is developed in [25]. However, [25] includes important restrictions, such as: (a) the use of linear cost functions, (b) solutions based on priority lists and rotational matrices, (c) models for wind speed distribution and irradiance, do not match the specific Chilean characteristics, (d) simple unavailability models that over penalize the wind energy contribution and (e) relatively simple outcomes consisting on means and standard deviations of the variables of interest. In order to obtain more complete results, this work includes non-linear cost functions, using a non-linear optimization algorithm with restrictions, bimodal wind speed and irradiance distributions that better match the Chilean case and the use of a binomial algorithm to model more closely the actual unavailability of NCRE plants.…”
Section: Introductionmentioning
confidence: 99%
“…Therefore, the total load demand in period t is computed as Equation (1). Also, the forecast error of load demand is assumed to fit the Gaussian distribution [28].…”
Section: Model Of Loadsmentioning
confidence: 99%
“…Arriagada et al, proposed a methodology to model and solve this problem incorporating renewable energies through Normal, Weibull, Beta and Uniform distributions for demand, wind speed, solar irradiation and unavailability respectively. In order to define the optimal power allocation for each generator, the Group SO orthogonal matrices, the marginal costs of the generators, the customer damage cost and Monte-Carlo trials are also presented [3]. Hoke et al, applied a fast and reliable linear programming approach to the problem of grid-tied micro-grids containing conventional generators, energy storage, demand response resources and renewable energy resources [4].…”
Section: Introductionmentioning
confidence: 99%