Dynamic R-Curve analysis and optimization of steam power plant solar repowering

https://doi.org/10.1016/j.applthermaleng.2021.117218Get rights and content

Highlights

  • Integration of Solar PTC, MED, and MSF desalination with a real steam power plant.

  • Development of the Dynamic R-Curve and novel graphical tool.

  • Using Artificial Neural Network with Genetic Programing to reduce computation time.

  • Multi-Objectives Optimization with Water Cycle and the Genetic Algorithms.

Abstract

Installing solar collectors to preheat boiler feedwater is one of the most economical methods of repowering steam power plants. The production of freshwater in repowered plants can increase their productivity. The present study aimed at integrating the Bandar Abbas steam power plant's repowered cycles with desalination units and subsequently analyzing the cycles using the R-Curve tool. Three scenarios are were considered for repowering: In the first scenario, parallel collectors were used instead of the low-pressure feedwater heaters, while in the second and third scenarios, parallel solar collectors were used instead of low-pressure feedwater heaters integrated with multi-effect and multi-stage flash desalination units, respectively. The dynamic development of the R-Curve, as well as the use of a combination of artificial intelligence and genetic algorithm programming to optimize the complex cycles of the multi-generation of power, heat, and freshwater, are the most important issues presented in this study. Results show that the Bandar Abbas steam power plant in operation has an R-ratio equal to 1.21 and a cogeneration efficiency of 36.5 percent. In the first scenario of repowering, the R-ratio is equal to 1.21, and in most months, the cogeneration efficiency varies between 35 and 45 percent. In the second and third scenarios, however, cogeneration efficiency is 50 percent at its lowest level. Moreover, with the introduction of the new conceptual graphical curves, it was found that using more solar energy and adding desalination units increase the cogeneration efficiency throughout the year. Optimization of repowered cycles integrated with multi-effect and multi-stage flash desalination units increased freshwater production by 178 and 42 percent, respectively.

Introduction

Iran is one of the best regions to implement projects related to solar energy repowering. In the southern and central areas of Iran, due to the appropriate amount of solar radiation, it is possible to develop solar energy [1]. Statistics show that in most parts of Iran, the average number of sunny days in a year is more than 280 [2]. Due to the considerable oil and gas resources in Iran, the development of power plants that work with renewable energy, such as solar energy, is very slow. For this reason, the country's steam cycle power plants using fossil fuels have become a primary source of carbon dioxide production and environmental pollution [3], [4]. According to this information, Iran has a strong potential to use solar energy in power plants. The country’s short-term development plan shows that by 2030, the power plant generation capacity should reach 139 MW, while the renewable energies should have a share of about 2% [5].

Repowering is one way of increasing old steam power plants’ efficiency [6], [7]. There are several methods for repowering [8]:

  • Use of auxiliary boilers (Supply boilers)

  • Use of auxiliary feedwater heaters (FWHs repowering)

  • Hot wind box

  • Full repowering (replacement of a combined cycle with an old steam cycle)

The cheapest way of repowering is that of FWHs repowering. This method's cost has been reported to be 90–110 $/kW in enormous power generation plants [9], [10].

  • only to preheat the boiler feed water. Therefore, the collector operating fluid operates at a lower temperature, which increases the efficiency of the solar system [11].

  • The efficiency of the solar system can be improved by adjusting the temperature difference between hot and cold flow in the heat exchanger. In this method, due to the low operating temperature, the difference between hot and cold flows in the heat exchanger parallel to the solar collector can be reduced, which increases the efficiency [11].

  • No need for auxiliary equipment such as boiler or heat storage source and in the absence of solar radiation, the steam cycle works using FWHs [11].

  • When using a solar collector, the initial energy conversion efficiency of the fuel remains constant [11].

In 1975, Zoschak and Wu [12], for the first time, tested seven different forms of solar receivers to provide some of the heat that thermal power plants needed. Pai [13] showed that solar collectors installed before FWHs could reduce fuel consumption in thermal power plants. The conclusion was that by using solar energy, the amount of fuel consumption would be reduced by 24.5 percent. Pierce et al. [14] compared solar-aided power plants and standalone solar power plants. They found that solar-aided power plants generate 25 percent more power than the standalone solar kinds. Reddy et al. [15] used Fresnel solar collectors (CLFR) to repower a steam power plant. It was found that when the required heat of all low-pressure and high-pressure heaters is provided by solar energy, the production capacity approximately increases by 20%. Kane et al. [16] investigated partial repowering by replacing feedwater heaters with solar collectors for a 300 MW steam power plant. In their study, high-pressure FWHs were replaced with solar collectors for the first time, the result of which was that the steam cycle efficiency increased by 71%. Wang et al. [17] investigated the repowering of a coal-fired power generation cycle using solar energy. It was found that the efficiency varied in the range of 15 to 20% during the year, and the price of power generation would be in the range of 0.7 to 1 Euro per kWh. Ahmadi et al. [18], [19] investigated the Isfahan power plant's cycle repowering using solar collectors in parallel with high-pressure FWHs. The results show that with this repowering, the cycle's exergy efficiency increased by about 18%.

In different articles, the combination of power and freshwater production units has been discussed. A combination of a reciprocating motor and desalination units is used [20]. A cogeneration cycle is connected to different water desalination units, which improves efficiency and cheap fresh water production [21]. An economic and environmental on the integration of the combined cycle with desalination units is presented [21], [22]. The results of all these articles show that the integration of a power generation unit and a water desalination unit will improve the technical, economic and environmental performance of the power plant [23], [24]. But this article tries to investigate the impact of adding a freshwater production unit to a repowered power plant. The integration of a cogeneration unit with solar energy repowering and drinking water production unit is the most important issue in this article.

In many industrial units, energy is the most crucial part affecting the entire site's operating costs. To increase the profitability of each unit, reducing energy costs is of prime importance. Reducing energy consumption also reduces the production of air pollutants, thus helping protect the environment. Dhole and Linhoff [25] introduced a graphical-based method to analyze the total site plants, which was then improved by Raissi [26]. Temperature-enthalpy diagrams were presented to enhance the cogeneration plant, as well as to reduce fuel consumption. Nishio et al. [27] and Chou and Shih [28] introduced a method based on thermodynamic principles to design a total site plant. In this method, maximizing thermal efficiency is the goal of the design. Nishio and Johnson [29] proposed a formulation based on linear programming to optimize a fixed-load total site system for different steam levels. Colmenares and Seider [30] designed a total site system through nonlinear programming. Mavromais [31], [32] proposed developing a steam turbine network based on numerical programming methods. Moreover, Makwana et al. [33] introduced a top-level analysis for modifying the site's energy sector and developed a method for analyzing total site systems. The technique first examines the total site system and then finally considers changes that can be made to the processes. This method is in contrast to the traditional method of analysis. The concept of the R-curve was first introduced by Kenney [34] to analyze the potential for the simultaneous generation of power and heat in a site. However, it is quite challenging to apply this basic concept to complex systems because the original R-curve is based on a simple total site system structure. Furthermore, in this method, the efficiency of the components has not been considered. Kimura and Zhou [35] developed a new R-curve called “retrofit R-curve” and “grassroots R-curve” to overcome the old R-curve method limitations. These new R-curves express maximum energy efficiency in the form of the efficiency of cogeneration against changes in heat demand and site power, while they also consider the limitations and complex structure of total site systems and the system components’ thermal efficiency. Analyzing the R-curve is the most reliable way to minimize operating costs, along with improved energy system planning. The R-curve can also evaluate options for making improvements to the site. Karim Kashi et al. [36] used the R-Curve concepts in an entire site. In addition, they examined the amount of heat and power generation capacity in general and operational modes. For the first time, another curve was presented in this work which was based on the total annual cost. The results show that with increasing production capacity, or, in other words, increasing R, the total yearly cost also increases, but in different structures, the cost rates will be different. Subsequent studies [37], [38], examined the effects of fuel consumption changes in the total site on the total annual costs and annual emissions using the development of the R-Curve concept. The results showed that with the change of fuel, there would be no significant change in the R-curve, but with natural gas, the annual costs will be maximum.

Furthermore, Ghaebi et al. [39] developed R-Curve concepts in the new cycle by adding a chiller unit to the previous cogeneration unit. The results showed an increase in cogeneration efficiency and an increase in annual costs in the new trigeneration cycle compared to the previous cycle cogeneration. Khoshgoftar Manesh et al. [40] developed the optimization concepts in a cogeneration system of heat and power. They optimized cogeneration efficiency with the R-Curve ideas and top-level analysis. For the first time, they combined the R-Curve concept with pictures of exergy and exergy destruction. The results showed an increase in exergy destruction with increases in the R parameter. In the following year, they [41] introduced a new method for optimizing a cogeneration system of heat and power. In this original method, steam distribution at low-pressure levels and steam turbines were taken into consideration. This optimization method also included properties and concepts such as enthalpy, entropy, and irreversibility. Bani Asadi et al. [42] integrated renewable energy into a cogeneration system of power and heat and examined the impact of this renewable energy on cogeneration efficiency with R-Curve concepts. The drawn R-curve was static, and no dynamic concepts were developed. The results showed an increase of up to about 15% in cogeneration efficiency when using renewable energy in the cogeneration system. Salimi et al. [43] examined cogeneration efficiency changes by adding the MED-TVC and RO desalination units to a cogeneration system. The presented results show an increase ranging between 4 and 12% in cogeneration efficiency. Ghorbani et al. [44]proposed a tri-generation system of power, heating, and freshwater by application of solar flat plate collectors, Kalina power cycle, and multi-stage desalination unit. In the other research, Ghorbani et al. investigated a novel trigeneration system for desalinated water & LNG production by hybrid refrigeration systems [45].

An integrated water desalination, oxy-fuel power generation and CO2 liquefaction system has been proposed by Ghorbani et al. Liquefaction of carbon dioxide gas from the power plant with an absorption refrigeration cycle has been investigated [46].

Moradi et al. investigated a hybrid power generation system integrated with a MED. Heat recovery from outlet gases of solid oxide fuel cell for using in Stirling engine. In the proposed system, the power output and the system efficiency are increased by 2.63 kW and 11.7 [47].

Due to the lower costs of steam cycle repowering compared to the construction of a new solar power plant, attempts have been made to repower the plant using solar thermal collectors. According to the previous literatures, the R-Curve analysis of the cogeneration system has been performed by Ghaebi et al. [39], the optimization of which has been reported by Khoshgoftarmanesh et al. [40]. Moreover, Bani Asadi et al. [42] integrated the cogeneration system with renewable energies, and Salimi et al. [43] integrated the cogeneration system with the desalination unit. Nevertheless, what has not yet been studied is the effect of repowering on cogeneration efficiency in a power generation unit. Besides, the dynamic analysis of the R-curve is one of the most critical issues that has not been studied so far. In this paper, with tools such as the R-curve and new parameters introduced instead of R, the effect of using solar energy to repower a cogeneration unit is investigated. These new parameters, called PDR and SFR, indicate the amount of heat required per unit of water desalination and the power output relative to the process heat needed and the ratio of heat received from the sun to the heat obtained from the fossil fuel, respectively. By these two parameters, the performance of the repowered cycle can be evaluated with better and more accurate graphic tools. The use of artificial intelligence and genetic algorithm programming in combination to optimize the complex processes of the multi-generation of power, heat and freshwater is the most important issue presented in this study. Optimization using a genetic algorithm and a water cycle algorithm has been used at the end of this work to improve the performance of power, heat, and freshwater production cycles. The reason for not using solar system to supply the steam needed by the electricity and freshwater production units is that the Bandar Abbas power plant is a real case, and the main purpose of this research is the repowering of this power plant through the use of a renewable kind of energy, namely solar energy. It should also be said that setting up a solar power plant imposes higher costs on investors than repowering an existing power plant. Therefore, due to the economic benefits of repowering and the use of clean energies such as solar energy, this method is preferable.

Section snippets

Case studies

The Bandar Abbas thermal power plant has about 1280 MW, which includes four 320 MW units. This power plant is one of Iran's largest power plants that use natural gas, diesel, and heavy fuel as a thermal energy source in the boiler. There are three steam turbines at different pressure levels and six feedwater heaters in the power plant. In the condenser cooling tower, seawater is used to cool the cycle steam [48].

The use of solar collectors in parallel with FWHs is one of the most economical

Methodology

The thermodynamic, exergy, exergoeconomic, and exergoenvironmental analysis of the base thermal power plant and repowering scenarios were all illustrated in a previous study [49]. The solar feedwater heater repowering dynamic and economical method of the design were also introduced in previous studies [49]. In this study, the thermodynamic of the desalination units has been investigated, after which economic and R-Curve analysis were introduced, and a multi-objective optimization was performed

The thermodynamic results

Validation of the results concerning the thermodynamic simulation of the Bandar Abbas steam cycle is shown in Table 8. The obtained results have been compared with those of the article by Nikbakht Nasserabad et al. [54]. The results include temperature, pressure, and flow of each of the main steam cycle streams, which shows an acceptable amount of simulation error. The solar collectors were designed in parallel with low-pressure and high-pressure FWHs so that the amount of feedwater temperature

Conclusion

In other research studies carried out so far, the R-Curve analysis of the cogeneration system was performed by Ghaebi et al. [39]. At the same time, its optimization was reported by Khoshgoftar Manesh et al. [40]. Moreover, Bani Asadi et al. [42] integrated the cogeneration system with renewable energies, while Salimi et al. [43] integrated the cogeneration system with the desalination unit. In this paper, the Bandar Abbas steam power plant's repowered cycles were integrated with desalination

CRediT authorship contribution statement

S. Kabiri: Formal analysis, Visualization, Data curation, Investigation Software: implementation of the computer code and supporting algorithms for simulation, analyses, and optimization for each component and overall system; transient analysis; testing of existing code components; Writing. M.H. Khoshgoftar Manesh: Conceptualization: Ideas - review and editing- Implementation of the advanced algorithm. Formal analysis, Validation: Verification and reproducibility of results; Supervision. M.

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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