Optimization of the triple-pressure combined cycle power plant

Alus, Muammer; Petrović, Milan V.

doi:10.2298/tsci120517137a

Cited by 16 publications

(7 citation statements)

References 15 publications

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“…The reference year was assumed to be 2013 and the Chemical Engineering Plant Cost Indices (CEPCI) [41] were used for the cost update. Notably, correction factor (R) of 3.0 was employed for the combined cycle to incorporate the cost of balance of plant (BOP) and plant construction [42]. The estimated value of PEC for each component was updated to the value of the reference year using the cost index.…”

Section: Calculation Of Life-cycle Costmentioning

confidence: 99%

Life-Cycle Cost Minimization of Gas Turbine Power Cycles for Distributed Power Generation Using Sequential Quadratic Programming Method

et al. 2018

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The life-cycle cost reduction of medium-class gas turbine power plants was investigated using the mathematical optimization technique. Three different types of gas turbine power cycles-a simple cycle, a regenerative cycle, and a combined cycle-were examined, and their optimal design conditions were determined using the sequential quadratic programming (SQP) technique. As a modeling reference, the Siemens SGT-700 gas turbine was chosen and its technical data were used for system simulation and validation. Through optimization using the SQP method, the overall costs of the simple cycle, regenerative cycle, and combined cycle were reduced by 7.4%, 12.0%, and 3.9%, respectively, compared to the cost of the base cases. To examine the effect of economic parameters on the optimal design condition and cost, different values of fuel costs, interest rates, and discount rates were applied to the cost calculation, and the optimization results were analyzed and compared. The values were chosen to reflect different countries' economic situations: South Korea, China, India, and Indonesia. For South Korea and China, the optimal design condition is proposed near the upper bound of the variation range, implying that the efficiency improvement plays an important role in cost reduction. For India and Indonesia, the optimal condition is proposed in the middle of the variation ranges. Even for India and Indonesia, the fuel cost has the largest contribution to the total cost, accounting for more than 60%.Energies 2018, 11, 3511 2 of 21As an alternative to large-scale, centralized power plants, small-scale power plants located at or near the consumer sites can supply electricity; these small power generators are called distributed (or decentralized) power generation (DPG). The use of DPG is increasing; it was responsible for 21% of the global electricity generation in 2000, and it is projected to account for approximately 40% of the global electricity increase in 2020 [5].Among several available technologies such as photovoltaic panels, wind turbines, internal combustion engines, and fuel cells [6,7], gas turbines were recognized as the most attractive option from the technological and economic standpoints [5]. However, power generation using small-or medium-sized gas turbines still remains expensive compared to the large-scale power generators [8] due to the relatively higher investment costs and lower electrical efficiencies. Therefore, reducing the operating costs of gas turbines by means of the mathematical optimization is crucial, particularly in distributed power generation areas. As shown in Table 1, several commercial gas turbine products exist that are suitable for use in large factories and urban buildings [8][9][10][11].

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Section: Calculation Of Life-cycle Costmentioning

confidence: 99%

Life-Cycle Cost Minimization of Gas Turbine Power Cycles for Distributed Power Generation Using Sequential Quadratic Programming Method

et al. 2018

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“…Generally in optimization studies such as [15][16][17] the environmental conditions, e. g., inlet air temperature are assumed to be constant but the effect of variation of these conditions on the performance may be more than 25% which is not a negligible amount [18]. There are satisfactory amount of publications in the literature which relates the output power of the gas turbine and ambient temperature [19,20].…”

Section: Pp S809-s817mentioning

confidence: 99%

A novel method for prediction of gas turbine power production: Degree-day method

2018

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Gas turbines are widely used in the energy production. The quantity of the operating machines requires a special attention for prediction of power production in the energy marketing sector. Thus, the aim of this paper is to support the sector by making the prediction of power production more computable. By using the data from an operating power plant, correlation and regression analysis are performed and linear equation obtained for calculating useful power production vs atmospheric air temperature and a novel method, the gas turbine degree day method, was developed. The method has been addressed for calculating the isolation related issues for buildings so far. But in this paper, it is utilized to predict the theoretical maximum power production of the gas turbines in various climates for the first time. The results indicated that the difference of annual energy production capacity between the best and the last province options was calculated to be 7500 MWh approximately.

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“…Three pressure CCGT optimizations were carried out by Alus and Petrovi. While optimizing Alus and Petrovi, they aimed to minimize the cost of electricity generation at the CCGT plants [14]. Alobaid et al with real power plant data, three pressure HRSGs were created in detail in a digital model with Aspen Plus.…”

Section: Introductionmentioning

confidence: 99%

Modelling, Sensitivity and Exergy Analysis of Triple-Pressure Heat Recovery Steam Generator

Mert

Özçelik

Kök

2020

MANAS Journal of Engineering

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Related to the increasing demand for environmental pollution and electrical energy, combined cycle power plants (CCPP) are increasingly important. So, It is necessary that increasing the performance of power plants, reducing carbon emissions and rising energy production. Any change related to the heat recovery steam generator design is important for essential components of the CCPP because of directly affects the performance of it. In this study, it has explained that the modelling, sensitivity and exergy analysis of a Heat Recovery Steam Generator (HRSG) in a CCPP. In the analyzes, three-pressure HRSG was modelled with the Aspen Plus simulation program. In addition to, sensitivity analyzes were done and evaluated. Also, energy and exergy analyzes were done for each component in the CCPP.

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Optimization of the triple-pressure combined cycle power plant

Cited by 16 publications

References 15 publications

Life-Cycle Cost Minimization of Gas Turbine Power Cycles for Distributed Power Generation Using Sequential Quadratic Programming Method

Life-Cycle Cost Minimization of Gas Turbine Power Cycles for Distributed Power Generation Using Sequential Quadratic Programming Method

A novel method for prediction of gas turbine power production: Degree-day method

Modelling, Sensitivity and Exergy Analysis of Triple-Pressure Heat Recovery Steam Generator

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