Quasi-Monte Carlo simulation based economic dispatch with wind power integrated

Gu, Bin; Chen, Z. M.; Jiv, T. Y.; Zhang, L. L.; Li, M. S.; Huang, Jinbo

doi:10.1109/isgt-asia.2016.7796396

Cited by 3 publications

(2 citation statements)

References 19 publications

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“…Another point of view, MCS is used to perform the probabilistic short-term load forecast scheduling in a power system by assuming the PDF as the system loading, the total operating cost is effectually optimized [15]. Furthermore, many similar researches have studied the effect of correlation of uncertain variables such as probabilistic appraisal of accessible load supply capability [16], POPF behavior and relationship of the wind power, load uncertainties and line parameters [17,18], PLF for solar power using percentile estimation of Weibull PDF [19], probabilistic investigation when wind and photovoltaic generation connected to system [20] PLF based on correlated series of generation, loading, and wind farm [21], probabilistic comparison and evaluation with energy management application [22], economic dispatch relied on Quasi-MCS is used to models the stochastic behaviors of wind speed and distributed loads [23], uncertainty of loads and wind speed is characterized by MCS to represent the total number of hours with overvoltage a year [24], hybrid MCS is performed to evaluate PLF when a large-scale wind power integrated to power system [25]. All these probabilistic problems and some other relevance are modelled in different purposes to balance the system loading by adjusting the add-on power generation in the power system.…”

Section: Introductionmentioning

confidence: 99%

Probabilistic Optimal Power Dispatch Considering Price-Based Real-Time Demand Response

Chhor¹,

Leeton²,

Chayakulkheeree³

2019

IJIES

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In this paper, a probabilistic optimal power dispatch (POPD) using linear programming (LP) is proposed for solving the power generation dispatch with price-based real-time demand response (PRDR). The expected shortterm load forecast is represented by a probabilistic distribution function. The simulation result has prosperously shown that the proposed method could handle the POPD solutions for real power dispatch considering PRDR by using probabilistic Truncated normal distribution function (PTNF). The PTNF is used in a vigorous part of the framework to eject the infeasible results during the computation. This would lead the results to the high degree of accuracy comparing to the normal sampling methods. The simulation results showed that the proposed method can efficiently and effectively minimize the total power generation cost while trading off the PRDR cost in the POPD problem with load uncertainty.

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Section: Introductionmentioning

confidence: 99%

Probabilistic Optimal Power Dispatch Considering Price-Based Real-Time Demand Response

Chhor¹,

Leeton²,

Chayakulkheeree³

2019

IJIES

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show abstract

“…Simulation results showed that this method is superior to the existing robust optimization model in cost and reliability [9]. In references [10][11][12], the uncertainty of wind power output is dealt with by using stochastic simulation technology. Xiong Hu et al took the output and load of a large-scale intermittent power supply as fuzzy parameters, and studied the clear equivalence class of fuzzy opportunity constraints with multiple fuzzy parameters, which was used to deal with the opportunity constraints [13].…”

Section: Introductionmentioning

confidence: 99%

Multi-Objective Economic Dispatch of Cogeneration Unit with Heat Storage Based on Fuzzy Chance Constraint

et al. 2018

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With the increasing expansion of wind power, its impact on economic dispatch of power systems cannot be ignored. Adding a heat storage device to a traditional cogeneration unit can break the thermoelectric coupling constraint of the cogeneration unit and meet the economic and stable operation of a power system. In this paper, an economy-environment coordinated scheduling model with the lowest economic cost and the lowest pollutant emissions is constructed. Economic costs include the cost of conventional thermal power generating units, the operating cost of cogeneration units, and the operating cost of wind power. At the same time, green certificate costs are introduced into the economic costs to improve the absorption of wind power. Pollutant emissions include SO2 and NOx emissions from conventional thermal power units and cogeneration units. The randomness and uncertainty of wind power output are fully considered, and the prediction error of wind power is fuzzy treated according to the fuzzy random theory, and the electric power balance and spinning reserve fuzzy opportunity conditions are established, which are converted into the explicit equivalent. The improved multi-objective particle swarm optimization (MOPSO) was used to solve the model. With this method, the validity of the model is verified by taking a system with 10 machines as an example.

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Uncertainty quantification of wind penetration and integration into smart grid: A survey

Nair

Ranganathan

Salehfar

et al. 2017

2017 North American Power Symposium (NAPS)

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Quasi-Monte Carlo simulation based economic dispatch with wind power integrated

Cited by 3 publications

References 19 publications

Probabilistic Optimal Power Dispatch Considering Price-Based Real-Time Demand Response

Probabilistic Optimal Power Dispatch Considering Price-Based Real-Time Demand Response

Multi-Objective Economic Dispatch of Cogeneration Unit with Heat Storage Based on Fuzzy Chance Constraint

Uncertainty quantification of wind penetration and integration into smart grid: A survey

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