Economic dispatch in view of the Clean Air Act of 1990

El-Keib, A.A.; Ma, H.; Hart, Jonathan

doi:10.1109/59.317648

Cited by 166 publications

(57 citation statements)

References 10 publications

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“…The total emission E (P G ) in (ton/h) of atmospheric pollutants such as sulphur oxides SO x and nitrogen oxides NO x caused by the operation of fossil -fueled thermal generation can be expressed as (3) Where α i ,β i ,γ i , and λ i are the coefficients of the i th generator emission characteristics.…”

Section: Minimization Of Emissionmentioning

confidence: 99%

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Optimization Of Combined Economic and Emission Dispatch Problem – A Comparative Study for 30 Bus Systems

Kumar¹

2012

IOSRJEEE

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Section: Minimization Of Emissionmentioning

confidence: 99%

“…[3] Generally the coal used in thermal plants is of poor quality and high ash. Sulphur dioxide (SO2) and oxides of nitrogen (NOx) are the major emissions from thermal plants due to the combustion of coal which will cause ill effects on human beings as well as on plants and on animals.…”

Section: Introductionmentioning

confidence: 99%

Optimization Of Combined Economic and Emission Dispatch Problem – A Comparative Study for 30 Bus Systems

Kumar¹

2012

IOSRJEEE

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“…When the only goal of scheduling the generation units is to minimize operation cost, this problem is usually referred to as the well-known unit commitment problem. Due to increased concern for environmental protection, U.S. electric power plant operators have the obligation to reduce atmospheric emissions of the thermal power plants, such as sulfur dioxide (SO 2 ) and nitrogen oxides (NO x ), beyond the levels called for in the Clean Air Act Amendments of 1990 (CAAA90) [1]. As a short-term alternative to achieve the emission targets without investment for new pollutant cleaning equipment, emission dispatching is an effective strategy to keep the emission below a certain level.…”

Section: Introductionmentioning

confidence: 99%

Two-phase multi-objective evolutionary approaches for optimal generation scheduling with environmental considerations

Das

Pahwa

2009

41st North American Power Symposium

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Abstract-This paper presents novel two-phase multi-objective evolutionary approaches for solving the optimal generation scheduling problem with environmental considerations. Two different multi-objective evolutionary algorithms (MOEA) based on Strength Pareto Evolutionary Algorithm 2 (SPEA2) and Archived Multi-objective Simulated Annealing (AMOSA) are presented in the paper. In the first phase, this approach formulates the hourly optimal generation scheduling problem as a multi-objective optimization problem which simultaneously minimizes operation cost and emission, while satisfying constraints such as power balance, spinning reserve and power generation limits. Results of the first phase are compared and SPEA2, which provided better results, is used for the second phase to obtain the optimal schedules for the 24 hours. The minimum up/down time and ramp up/down rate constraints are incorporated in the second phase. A case study for a 10-unit test system is carried out to illustrate the application and the effectiveness of the proposed approach.

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“…With the increasing awareness of environmental protection in recent years, Economic Emission Dispatch (EED) is proposed as an alternative to achieve simultaneously the minimization of fuel costs and pollutant emissions [8]. However, minimizing the emission and cost are usually two conflicting objectives.…”

Section: Introductionmentioning

confidence: 99%

Combined Economic and Emission Dispatch with Valve-point loading of Thermal Generators using Modified NSGA-II

Rajkumar¹,

Mahadevan²,

Kannan³

et al. 2013

Journal of Electrical Engineering and Technology

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-This paper discusses the application of evolutionary multi-objective optimization algorithms namely Non-dominated Sorting Genetic Algorithm-II (NSGA-II) and Modified NSGA-II (MNSGA-II) for solving the Combined Economic Emission Dispatch (CEED) problem with valvepoint loading. The valve-point loading introduce ripples in the input-output characteristics of generating units and make the CEED problem as a non-smooth optimization problem. IEEE 57-bus and IEEE 118-bus systems are taken to validate its effectiveness of NSGA-II and MNSGA-II. To compare the Pareto-front obtained using NSGA-II and MNSGA-II, reference Pareto-front is generated using multiple runs of Real Coded Genetic Algorithm (RCGA) with weighted sum of objectives. Furthermore, three different performance metrics such as convergence, diversity and Inverted Generational Distance (IGD) are calculated for evaluating the closeness of obtained Pareto-fronts. Numerical results reveal that MNSGA-II algorithm performs better than NSGA-II algorithm to solve the CEED problem effectively.

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Economic dispatch in view of the Clean Air Act of 1990

Cited by 166 publications

References 10 publications

Optimization Of Combined Economic and Emission Dispatch Problem – A Comparative Study for 30 Bus Systems

Optimization Of Combined Economic and Emission Dispatch Problem – A Comparative Study for 30 Bus Systems

Two-phase multi-objective evolutionary approaches for optimal generation scheduling with environmental considerations

Combined Economic and Emission Dispatch with Valve-point loading of Thermal Generators using Modified NSGA-II

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