Multi-objective optimal scheduling for hydro-thermal-wind power system

Han, Zhonghui; Cheng, Tao; Zhou, Yifan; Zhang, Peng

doi:10.1109/tencon.2015.7372768

Cited by 6 publications

(4 citation statements)

References 4 publications

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“…These parameters depend upon height, location and some geographical features. Wind speed is modeled by using the Weibull PDF, and it is described as (Han et al, 2015),…”

Section: Characterization Of Wind Speedmentioning

confidence: 99%

Optimal Wind-Thermal Coordination Scheduling Considering Reserve Requirement

Jung¹,

Salkuti²

2019

Int J Math, Eng, Manag Sci

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This paper proposes an optimal coordination scheduling methodology for a wind-thermal power system by considering the intermittent behavior of wind power and load demands. The optimum amount of spinning reserves (SRs) needed to handle the uncertain nature of hybrid power system with wind generators is determined by using the probability analysis. The proposed model demonstrates the error in wind power and load forecasts by using the probability distribution functions for over and under estimations of load and wind power. In this work, two objectives, i.e., total operating cost and risk level are considered, which handles both economical and reliability issues, simultaneously. This problem is solved by using the meta-heuristic based Cuckoo search algorithm. The reactive power capability limits of synchronous generators and variable speed doubly fed induction generators are considered in this paper. Simulations have been carried out on IEEE 300 bus system.

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“…These parameters depend upon height, location and some geographical features. Wind speed is modeled by using the Weibull PDF, and it is described as (Han et al, 2015),…”

Section: Characterization Of Wind Speedmentioning

confidence: 99%

Optimal Wind-Thermal Coordination Scheduling Considering Reserve Requirement

Jung¹,

Salkuti²

2019

Int J Math, Eng, Manag Sci

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“…Thus, we need to modify Q j;t to meet the constraints such as Eqs. (18), (20) and (21). In this paper, a novel heuristic approach based on the compressing decision space [27] is designed to handle practical operational constraints.…”

Section: Repairing Constraints Of Hydropower Stationmentioning

confidence: 99%

“…These papers are mainly aimed to realizing joint operation of wind power and thermal power, but the integration of wind power with hydrothermal power system is rarely reported in literature. Therefore, HTWCS is a problem that is worth discussing, and the related work are also carried out in succession recently [18][19][20].…”

Section: Introductionmentioning

confidence: 99%

Short-term hydro-thermal-wind complementary scheduling considering uncertainty of wind power using an enhanced multi-objective bee colony optimization algorithm

Zhou

Peng

et al. 2016

Energy Conversion and Management

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“…In [6], a Gray coded genetic algorithm is proposed for the economic dispatch (ED) problem of wind-thermal power system, and to determine the optimal power dispatch method for the proper utilization of wind power. A multi-objective optimized scheduling for power system composed of thermal, hydro and wind power is proposed in [7] considering the system operation cost, pollutant emission of thermal power and the net loss of power system as the multiple objectives. An approach for solving the ED problem in the presence of RERs is presented in [8].…”

Section: Introductionmentioning

confidence: 99%

Multi-objective optimal power flow in the presence of intermittent renewable energy sources

Reddy

2018

IJET

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This paper solves a multi-objective optimal power flow (MO-OPF) problem in a wind-thermal power system. Here, the power output from the wind energy generator (WEG) is considered as the schedulable, therefore the wind power penetration limits can be determined by the system operator. The stochastic behavior of wind power and wind speed is modeled using the Weibull probability density function. In this paper, three objective functions i.e., total generation cost, transmission losses and voltage stability enhancement index are selected. The total generation cost minimization function includes the cost of power produced by the thermal and WEGs, costs due to over-estimation and the under-estimation of available wind power. Here, the MO-OPF problems are solved using the multi-objective glowworm swarm optimiza-tion (MO-GSO) algorithm. The proposed optimization problem is solved on a modified IEEE 30 bus system with two wind farms located at two different buses in the system.

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Multi-objective optimal scheduling for hydro-thermal-wind power system

Cited by 6 publications

References 4 publications

Optimal Wind-Thermal Coordination Scheduling Considering Reserve Requirement

Optimal Wind-Thermal Coordination Scheduling Considering Reserve Requirement

Short-term hydro-thermal-wind complementary scheduling considering uncertainty of wind power using an enhanced multi-objective bee colony optimization algorithm

Multi-objective optimal power flow in the presence of intermittent renewable energy sources

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