A New Biobjective Probabilistic Risk-Based Wind-Thermal Unit Commitment Using Heuristic Techniques

Bavafa, Farhad; Niknam, Taher; Azizipanah‐Abarghooee, Rasoul; Terzija, Vladimir

doi:10.1109/tii.2016.2616109

Cited by 37 publications

(12 citation statements)

References 27 publications

(52 reference statements)

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“…In the first part of numerical simulation, in order to show the capability of proposed method, a comparison between the obtained result of MIWO algorithm and those reported in the literature including PSO [1], BGSA [13], TLBO [8], QOTLBO [8], GHS-JGT [14] and BSA [15] algorithms, for Case I are provided in TABLE I. According to this table, it is obvious that the proposed algorithm can converge to a better solution comparing to the other optimization algorithms.…”

Section: 19mentioning

confidence: 99%

A novel reliability oriented bi-objective unit commitment problem

Azizivahed

Ghavidel

Ghadi

et al. 2017

2017 Australasian Universities Power Engineering Conference (AUPEC)

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This paper presents a new solution to unit commitment for single-objective and multi-objective frameworks. In the first step, the total expected energy not supplied (TEENS) is proposed as a separate reliability objective function and at the next step, the multi-objective Pareto front strategy is implemented to simultaneously optimize the cost and reliability objective functions. Additionally, an integer based codification of initial solutions is added to reduce the dimension of ON/OFF status variables and also to eliminate the negative influence of penalty factor. The modified invasive weed optimization (MIWO) algorithm is also developed to optimally solve the proposed problem. The obtained solutions are compared with results in the literature which confirms the applicability and superiority of the proposed algorithm for a 10-unit system and 24-hour scheduling horizon. Index Term-Unit commitment, bi-objective optimization, the total expected energy not supplied (TEENS), invasive weed optimization (MIWO) algorithm.

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Section: 19mentioning

confidence: 99%

A novel reliability oriented bi-objective unit commitment problem

Azizivahed

Ghavidel

Ghadi

et al. 2017

2017 Australasian Universities Power Engineering Conference (AUPEC)

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“…In such cases, wind power becomes cost-ineffective or even ineffective for air pollutant dispersion control. Second, here robust optimization [21]- [23], [38] is more appropriate compared to deterministic and stochastic optimization methods [39]- [40]. If the distribution information of uncertainties is available, which is often not the case, stochastic optimization can be preferable.…”

Section: B Constraintsmentioning

confidence: 99%

Unit Commitment Incorporating Spatial Distribution Control of Air Pollutant Dispersion

Lei

Hou

et al. 2017

IEEE Trans. Ind. Inf.

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Air pollution problems are attracting increasing attention, especially among developing countries with frequent haze events. Renewable energy sources such as wind power are expected to help relieve such environmental concerns. However, air pollution issues under such a changing energy structure receive inadequate attention. Mostly, constraints for total pollutant emissions are considered in unit commitment (UC) and economic dispatch (ED) problems. In this paper, we propose a UC model with wind power that considers the dispersion of air pollutants. The dispersion process is described by models involving meteorological conditions and the system's geographical distribution, to estimate the spatial distribution of air pollutants, i.e. the concentration of ground-level air pollutants at monitored locations such as load centers. A penalty cost is introduced based on this estimation. Particulate matter 2.5 micrometers or less in diameter, the major air pollutant concerning most developing countries, is selected as the focus of this work. To properly estimate and sufficiently utilize the benefits of wind power for air pollutant dispersion control, robust optimization is applied to accommodate wind power uncertainty. Case studies justify this consideration of air pollutant dispersion, and demonstrate the effectiveness of the proposed model for improving load centers' air pollution control and utilizing wind power benefits. Index Terms-Air pollutant dispersion, Gaussian plume model, robust optimization, unit commitment, wind power. NOMENCLATURE A. Indices: i Index of thermal units, i=1, … , NG w Index of wind farms, w=1, … , NW j Index of loads, j=1, … , ND l Index of transmission lines, l=1, … , NL t Index of time intervals, t=1, … , T

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“…If we take the sensitivity of temperature to energy into account, the constraints for water heater can also be expressed as (8)- (10). As the water heater cannot release energy, constraint (9) need to be replaced by (12):…”

Section: Mathematical Formulationmentioning

confidence: 99%

Research on Stochastic Optimal Operation Strategy of Active Distribution Network Considering Intermittent Energy

2017

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Active distribution networks characterized by high flexibility and controllability are an important development mode of future smart grids to be interconnected with large scale distributed generation sources including intermittent energies. However, the uncertainty of intermittent energy and the diversity of controllable devices make the optimal operation of distribution network a challenging issue. In this paper, we propose a stochastic optimal operation strategy for distribution networks with the objective function considering the operation state of the distribution network. Both distributed generations and flexible loads are taken into consideration in our strategy. The uncertainty of the intermittent energy is considered in this paper to obtain an optimized operation and an efficient utilization of intermittent energy under the worst scenario. Then, Benders decomposition is used in this paper to solve the two-stage max-min problem for stochastic optimal operation. Finally, we test the effectiveness of our strategy under different scenarios of the demonstration project of active distribution network located in Guizhou, China.

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A New Biobjective Probabilistic Risk-Based Wind-Thermal Unit Commitment Using Heuristic Techniques

Cited by 37 publications

References 27 publications

A novel reliability oriented bi-objective unit commitment problem

A novel reliability oriented bi-objective unit commitment problem

Unit Commitment Incorporating Spatial Distribution Control of Air Pollutant Dispersion

Research on Stochastic Optimal Operation Strategy of Active Distribution Network Considering Intermittent Energy

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