Viability of a concentrated solar power system in a low sun belt prefecture

Abstract

Concentrating solar power (CSP) is considered as a comparatively economical, more efficient, and large capacity type of renewable energy technology. However, CSP generation is found restricted only to high solar radiation belt and installed where high direct normal irradiance is available. This paper examines the viability of the adoption of the CSP system in a low sun belt region with a lower direct normal irradiance (DNI). Various critical analyses and plant economics have been evaluated with a lesser DNI state. The obtained results out of the designed system, subjected to low DNI are not found below par, but comparable to some extent with the performance results of such CSP plants at a higher DNI. The analysis indicates that incorporation of the thermal energy storage reduces the levelized cost of energy (LCOE) and augments the plant capacity factor. The capacity factor, the plant efficiency, and the LCOE are found to be 32.50%, 17.56%, and 0.1952 $/kWh, respectively.

Graphical abstract

Keywords

concentrated solar power / direct normal irradiance / plant performance / plant economics / thermal energy storage

1 Introduction

Energy is a crucial factor in economic development. With the rising standard of living and the growing world population, the global energy demand is steadily increasing [1]. To meet the growing global energy demand in an environmentally sustainable manner, greater importance is being given to the dissemination and development of renewable energy technologies. Solar energy is a vital renewable energy source which is expected to play a significant role in the future energy supply mix [2]. Solar power can be harnessed either through photovoltaic (PV) or solar thermal technology. Presently, PV technology for power generation is adopted widely in all parts of the globe. According to the 2016 energy report of the International Renewable Energy Agency, the PV solar power constitutes 98.35% of the total solar energy, while solar thermal power generation amounts to only 1.65% of the total solar energy [3]. Despite the enormous promises of solar energy, it is factual that both technology routes are primarily dependent on the availability of solar radiation. For the efficient functioning of the concentrated solar power plant, it requires high direct normal irradiance (DNI) whereas the PV systems can use the DNI as well as diffuse solar radiation for solar power generation [2]. High sun belt zone corresponds to daily DNI≥5 kWh/m² while low sun belt is indicated by daily DNI of 3–4 kWh/m² [4]. Solar thermal power generation is found restricted only to the high solar radiation belt. It is believed that a place with a high annual DNI is the best location to install a solar thermal power plant and can only be installed where the DNI≥5.5 kWh/(m²·d) [5,6]. The threshold values of annual DNI for concentrated solar power generation are suggested to be 1800 kWh/(m²·d) and 2000 kWh/(m²·d) by few researchers [1,7–9].

1.1 Scope of this study

The authors of this paper believe that the success of solar power generation is largely dependent on dissemination of both solar PV as well as solar thermal power generation technology. In recent times the solar thermal power industry has faced increasing competition from the PV industry as PV manufacturing costs are decreasing rapidly due to mass manufacturing and associated learning curves [10]. Considering the present situation, solar thermal accounts for a minuscule segment in the global solar power generation scenario. Thus solar thermal power generation technology is required to be focused more if land is not a constraint as solar thermal power generation has some inherent advantages like higher efficiencies, energy dispatchability through thermal storage, lower investment costs, better hybrid operation competence compared with other fuels, etc [11]. It is generally presumed that concentrated solar energy plants require a large amount of direct sunlight and best constructed in arid or semi-arid regions, globally known as high sun belt [12]. However, a literature review evidently indicates that no study has been conceived yet to investigate the viability of a solar thermal power system under low DNI. The present work tries to examine the possible performance of solar thermal power generation and its feasible scope in a low sun belt region with the average daily DNI of 3.78 kWh/m². The results of performance of concentrated solar power in the low sun belt zone have not been presented anywhere before. This study is investigative toward the viability of the technology in a low sun belt prefecture against normal convention. The quintessence of this study is universal and it is expected to be helpful and indicative toward dissemination of the technology in various other parts of the world excluding the high sun belt.

1.2 Location and topography of the study site

India is situated in the equatorial belt of the earth and receiving an ample amount of radiant energy from the sun. There are about 5000 trillion kWh per year incident over India’s land area with the most of the parts receiving DNI of 4–5 kWh/(m²·d) [13]. However, the north-eastern region (NER) of India is an agglomeration of eight states and located in monsoon prone climatic condition [14] with limited DNI component in solar radiation over the year [13]. The present study is conceived for one of the small north-eastern states, Tripura. The land area of Tripura is 10491 km² and having an international boundary with Bangladesh in the north, south, west and south-west. On the east, the neighboring Indian states of Assam and Mizoram are located. As per 2011 population census, Tripura constitutes 0.3% of the country’s population. The physiography of Tripura is characterized by plains, valleys, and hill ranges. Due to the south-west monsoon, Tripura receives a seasonal heavy rain, with an average rainfall from 1980 mm to 2746 mm and a temperature from 13°C to 27°C in winter and 24°C to 36°C in summer [15]. Tripura is situated in the biogeographic zone of 9B-north-east hills and owns extremely rich biodiversity [16].

1.3 Brief literature review

Hang et al. [17] studied the concentrating solar power (CSP) potential in China and strategies to promote the development of this technology. Charabi and Gastli [18] made an assessment of a large CSP plant in Wilay at Duqum in Oman which receives a very high solar radiation over the year. Purohit and Purohit [1] made an economic assessment of CSP generation for a few selected locations in India. Arora [12] studied the potential of CSP plants in Thar Desert of Rajasthan, India. Kuravi et al. [19] reviewed different methodologies for the thermal energy storage system design for CSP plants. Ramdé et al. [4] presented the results of the potential assessment of CSP plants for electricity generation in West Africa. Benammar et al. [20] investigated the impact of receiver surface area and temperature on the receiver efficiency of solar tower power plants. Turchi and Ma [21] designed a gas turbine/ solar trough hybrid model to increase the solar-to-electric efficiency while decreasing the gas heat rate. Yu et al. [22] developed a strategy for improving the distribution of the concentrated solar flux inside the cavity receiver based on multi-focal points of heliostat solar field. Boudaoud et al. [23] carried out a techno-economical analysis for the feasible execution of a molten salt cavity receiver thermal power plant in Algeria. Liu et al. [24] conducted a dynamic simulation of a 1 MW CSP tower plant implemented with two-level thermal storage with the control system. Mutuberria et al. [25] examined the performance of heliostat solar field layout performances of central receiver based CSP plant by applying number of algorithms. Sharma et al. [2] assessed the utilization potential of solar thermal power generation in India for threshold DNI values of 1800 kWh/m² and 2000 kWh/m². Santos et al. [26] did a performance analysis of a solar-gas turbine power plant and performed a seasonal thermodynamic prediction when the solar irradiance was high enough. Trabelsi et al. [27] studied the performance of CSP parabolic trough plants in the high DNI desert region of the southern part of Tunisia. Astolfi et al. [28] compared different types of optimization approaches for the minimization of peak heat flux on the surface of a central tower receiver of a solar thermal plant located in Seville, Spain. Bishoyi and Sudhakar [5] evaluated the performance of a 100 MW parabolic trough CSP plant receiving an annual DNI of 2248.17 kWh/m² in Rajasthan, Indian. Luo et al. [29] evaluated the impacts of solar multiple on the performance of a 100 MW direct steam generation solar power tower plant with integrated thermal storage. Polo et al. [30] analyzed the impact of DNI on CSP plant yield by simulating the plant model in one meteorological year and by simulating the model using multi-year meteorological data sets. Arrif et al. [31] analyzed the optical performance and efficiency of six different shapes of cavity receivers mostly used in solar tower power plant systems. Chen et al. [32] studied the combined effects of design DNI, TES (thermal energy storage) hours and SM (solar multiple) on the performance of the solar tower power plant and also determined the relationship between the DNI and the optimal choice of TES hours and SM. Sorgulu and Dincer [33] analyzed the performance of the TES integrated solar tower power system to supply both fresh water and electricity. Fares and Abderafi [34] analyzed the water consumption of a particular year considering every hour of the day for electricity production of a Moroccan CSP power station using the system advisor model (SAM). Alonso-Montesinos et al. [35] presented an energy forecasting analysis in solar tower power plants using the SAM. Hafez et al. [36] analyzed the techno-economical feasibility of utility-scale PV and CSP solar power plants in Saudi Arabia.

2 Concentrated solar thermal power generation

The present study is conceived with a solar tower power plant as being a promising CSP technology. The capacity of the designed plant is 10 MW which is considered to be operational under the meteorological climate of Agartala (capital of Tripura) in north-east India. Figure 1 explains the operation of the power plant and Table 1 provides the design characteristics considered for plant profiling. The considered solar thermal power tower plant is primarily divided into four segments viz. a heliostat solar field division, a central receiver division, a steam generator division, and a power cycle division. The solar field consists of a number of mirrors for concentrating the solar ray toward the receiver which is situated at the top of the tower. The mirrors are ideally focused by using the one-axis heliostat canting method. The receiver is of an external cylindrical type and molten salt is used as the heat transfer fluid (HTF) with a composition of 60% of NaNO₃ and 40% of KNO₃. The amount of solar radiation focused on the surface of the receiver produces a high temperature to heat the molten salt (HTF) which is used to transfer the thermal energy from the receiver to the steam generator subsystem. After passing through the steam generator, the molten salt temperature falls down to around 290°C which is then pumped back to the receiver to start the next thermal cycle [20].

3 Materials and methods

3.1 Solar radiation data

High temporal and spatial resolution solar resource information is critical for each phase of a solar energy conversion project, ranging from conceptual definition to routine solar power plant operations. Solar resource and meteorological data are also used as inputs to various performance and economic models, such as the system advisor model (SAM). The national renewable energy laboratory (NREL) of US Department of Energy has been developing, updating, and disseminating the modeled national solar radiation database (NSRDB) during the last two decades. The data set is publicly available and has been the flagship source of solar resource and surface meteorological information for many renewable energy applications. The NSRDB has comprised the best available data from ground measurement stations and modeled solar irradiance data based on surface meteorological observations (e.g., cloud cover) or, more recently, satellite remote sensing methods for retrieving properties of the atmosphere. The DNI data of the NSRDB which are available from 1998 to 2015 at a half-hourly temporal resolution and a 4-km by 4-km spatial resolution were analyzed in this study. The present version of the NSRDB (1998–2015) was established using the physical solar model (PSM), which follows a physics-based approach wherein cloud and other atmospheric properties are retrieved from the geostationary operational environmental satellite data and used as inputs to a radiative transfer model to compute the surface radiation [38]. This multiyear data set is analyzed in order to calculate typical meteorological year (TMY) which contains one year of hourly data that best represent weather conditions over a multiyear period. The TMY data in CSV format are incorporated into system advisory model (SAM) software libraries. Figure 2 shows the DNI profile of the location. It can be observed in Fig. 2 that the highest DNI values are around solar noon in March, October and November. Another critical atmospheric parameter is the ambient temperature of the site which has an impact on the performance of the CSP plant. Figure 3 depicts the average ambient temperature in various months of the year. From the measurement, it is recorded that the ambient temperature of the location studied is about 25°C–36°C.

3.2 Simulation

In the present work the technical formulation of the solar thermal electricity generation power plant has been carried out in SAM which is developed by the National Renewable Energy Laboratory (NREL), the US Department of Energy for predicting hourly energy production for renewable energy systems. System performance and an economic model designed using SAM can provide vigorous analysis capabilities for energy researchers. SAM presents the most common software platform for the simulation of CSP systems. This databank gives comprehensive information to facilitate users to define the configurations of a complete project. The model consists of components that interrelate with each other. Besides, each component is described by a number of factors and time variant inputs which generates a number of time variant outputs. The output of a particular component can be used as input to itself or to other components [27].

3.3 Mathematical formulation and parameterization

3.3.1 Modeling of the solar power plant system

The solar tower power plant is divided into four subsystems: the heliostat field, the central receiver, steam generator, and the power block.

Heliostat field subsystem

The heliostat solar field contains a large number of mirrors. The incident sunlight is reflected from the heliostat mirror and concentrated onto the central receiver. A fraction Q _re of the incident solar radiation Q _h is transmitted to the receiver by the heliostat field, while the remaining fraction Q _o is lost to the environment due to various loss mechanisms [20].

The energy balance equation for the heliostat solar field subsystem is described as

(1) Q_{\mathrm{h}}=Q_{\mathrm{re}}+Q_{\mathrm{o}}.

The performance of the heliostat solar field is characterized by its field optical efficiency ƞ _opt. The overall heliostat field optical efficiency is [20]

(2) {\eta }_{\mathrm{opt}}={\eta }_{\cos }{\eta }_{\mathrm{block}}{\eta }_{\mathrm{shadow}}{\eta }_{\mathrm{atten}}{\eta }_{\mathrm{ref}}{\eta }_{\mathrm{spill}},

where η _cos is cosine efficiency, η _block is blocking efficiency, η _shadow is shadow efficiency, η _atten is atmospheric attenuation efficiency, η _ref is mirror reflective efficiency, and η _spill is spillage efficiency.

The optical efficiency of the solar field is also defined as the ratio of the net power absorbed by the receiver surface (Q _rec) and the total solar power incident on the heliostat solar field [23].

(3) {\eta }_{\mathrm{opt}}={\displaystyle \frac{Q_{\mathrm{rec}}}{I_{\mathrm{d}}{A}_{\mathrm{h}}{N}_{\mathrm{h}}}},

where A _h is the heliostat area (m²), I _d is the DNI received by the heliostat solar field (kWh/m²), and N _h is the total number of mirror in the heliostat field.

Central receiver subsystem

In the receiver, the concentrated solar energy is converted into heat energy. A fraction of the receiver thermal energy (Q _re) is transferred to the HTF, which is the molten salt (Q _re,abs). The remaining part of the thermal energy received by the receiver surface is lost to the environment (Q _re,totloss) by the convection heat loss, radiation heat loss, reflection heat loss, and conduction heat loss [20].

The efficiency of the central receiver (η _re) is defined as the ratio of the absorbed thermal energy by the HTF (Q _re,abs) to the thermal energy incident on the receiver absorber surface (Q _re) [39].

(4) {\eta }_{\mathrm{re}}={\displaystyle \frac{Q_{\mathrm{re,abs}}}{Q_{\mathrm{re}}}}.

The energy balance equation of the central receiver is given by

(5) Q_{\mathrm{re}}=Q_{\mathrm{re,abs}}+Q_{\mathrm{re,totloss}}.

The maximum HTF mass flow rate to the receiver is a very useful component for the calculation of the plant performance with a constant receiver efficiency. The relation between the maximum HTF mass flow rate and the receiver thermal efficiency is given as [40]

(6) \mathrm{Maximum\; flow\; rate\; to\; receiver}=\left(\mathrm{Maximum\; receiver\; operation\; fraction}\times \mathrm{Receiver\; thermal\; power}\left({\mathrm{MW}}_{\mathrm{t}}\right)\mathrm{}\times \mathrm{1}000000\right)÷\left(\mathrm{HTF\; Specific\; heat}\times 1000000\mathrm{}\times \left(\mathrm{HTF\; hot\; temperature}-\mathrm{HTF\; cold\; temperature}\right)\right).

Steam generator subsystem (SGS)

The steam generator subsystem links the central receiver unit and the steam turbine power unit, which is one of the most crucial components of the solar power plant. A number of heat exchangers are connected in series inside the SGS where the subcooled liquid is heated by the hot molten salt to superheated steam [20].

Power cycle subsystem

The Rankine cycle mainly consists of low and high-pressure turbine stages, a feed-water heater, tow pumps, and a condenser. In a simple Rankine cycle, a part of steam energy (Q _st,abs) is absorbed by the turbine and transformed into mechanical energy (W _net) which is then conveyed by rotating the shaft to drive an electrical generator. The energy balance equation of the power cycle subsystem is given as [20]

(7) Q_{\mathrm{st},\mathrm{abs}}=W_{\mathrm{net}}+Q_{\mathrm{ps},\mathrm{totloss}},

where Q _ps,totloss is the power cycle total loss.

The power cycle heat input and output power is a function of condenser pressure, HTF temperature and the HTF mass flow rate. The relation among the outlet HTF temperature, cycle heat absorption rate and the cycle efficiency are given as [41]

(8) T_{\mathrm{htf,out}}=T_{\mathrm{htf,in}}-{\displaystyle \frac{Q_{\mathrm{ab}}}{{\dot{m}}_{{}_{\mathrm{htf}}}{c}_{\mathrm{htf,avg}}}}\mathrm{,}

(9) {\eta }_{\mathrm{cycle}}\mathrm{=}{\displaystyle \frac{\dot{W}}{Q_{\mathrm{ab}}}}\mathrm{,}

where ƞ _cycle is the power cycle efficiency, T _htf,out is the outlet HTF temperature, T _htf,in is the inlet HTF temperature, {\dot{m}}_{{}_{\mathrm{htf}}} is the mass flow rate of the HTF, c _htf,avg is the average specific heat of heat transfer fluid, \dot{W} is the cycle power output, and Q _ab is the cycle heat absorption rate.

3.3.2 Capacity factor

Solar power plants are considerably dependent on intermittent solar radiation sources. The ratio of the actual energy generated at partial load to the energy that could potentially be generated if the plant is operated at full load is defined as the capacity factor [23].

(10) \mathrm{CF\; =}{\displaystyle \frac{E_{\mathrm{net}}}{C_{\mathrm{design}}\mathrm{\times 8760}}}\times \mathrm{100},

where CF is the capacity factor of the plant, E _net is the annual energy output in kWh/a, and C _design is the nameplate capacity of the plant in kW.

3.3.3 Solar multiple

The thermal power of the receiver has been defined by the solar multiple which is the ratio of the thermal power of the receiver produced by the heliostat solar field to the cycle thermal power [23].

(11) \mathrm{SM=}{\displaystyle \frac{q_{\mathrm{sf}}}{q_{\mathrm{pb}}}},

where q _sf is thermal power produced by the heliostat solar field (kW_th) and q _pb is the thermal power required by the power block under nominal conditions (kW_th).

3.3.4 Levelized cost of energy (LCOE)

The LCOE is a performance indicator that describes an annualized cost per energy produced over the course of a year [42,43].

(12) \mathrm{L}\mathrm{C}\mathrm{O}\mathrm{E}={\displaystyle \frac{\mathrm{}{\displaystyle \sum _{n=\mathrm{0}}^N\frac{C_n}{{(\mathrm{1}+d)}^n}}}{{\displaystyle \sum _{n=\mathrm{1}}^N\frac{E_{\mathrm{n}\mathrm{e}\mathrm{t}}}{{(\mathrm{1}+d)}^n}}}},

where E _net (kWh) is the electricity generated by the system in year n shown in the Energy row in the project cash flow, N is analysis period in years, C _n is the annual project costs in year n, and d is the nominal discount rate.

4 Results and discussion

4.1 Heliostat mirror sizing

The sizing of the heliostat mirror is one of the principal factors for the performance of the plant. Figure 4 characterizes the mirror size on plant performance. Figures 4(a) and 4(b) show that with the increase in single heliostat surface area, receiver efficiency and the field optical efficiency both decrease. The correlation between the heliostat surface area and the annual performance is analyzed in Figs. 4(c) and 4(d). Figure 4(c) shows that the annual solar-to-electric efficiency sharply increases at the beginning with the increase in heliostat surface area and thereafter there is a moderate decrease in the annual solar-to-electric efficiency due to unutilized solar energy in increased heliostat surface area. It has a maximum value when the heliostat surface area is 36 m² and the corresponding maximum annual solar-to-electric efficiency is 17.56%. Figure 4(d) depicts that the annual power generation from solar energy increases initially and then decreases with the increase in the heliostat surface area.

4.2 Tower height characterization

The height of the tower in the solar tower power plant is a deciding factor for the attenuation loss, required land area, field optical efficiency, receiver thermal power, energy output, and capacity factor of the plant. Characterizations of tower height with respect to these parameters are demonstrated in Fig. 5. Figure 5(a) shows that both the attenuation loss and total land field area increase with the increase in tower height while Fig. 5(b) illustrates the variation of field optical efficiency with the changes in tower height. It is observed that field optical efficiency enhances 4.41% with the increase in tower height from 80 m to 115 m (a 43.75% increase in height). Figure 5(c) gives the correlation between the tower height and the receiver thermal power which indicates that the receiver gets more thermal power from the heliostat field if the tower height increases. Figure 5(d) exhibits the variation of annual energy output and the plant capacity factor with regard to tower height. It is evident that energy production and capacity factor are augmented with the increase in tower height.

4.3 Solar multiple

The thermal power of the receiver can be defined by the solar multiple. The solar multiple is the ratio of the receiver thermal power to the cycle thermal power [23] which normalizes the size of the solar field with respect to the power block. Figure 6 explains the effect of solar multiple on the solar tower power plant. Figure 6(a) shows the impact of solar multiple on the CSP plant capacity factor at different values of the thermal energy storage (TES) capacity. It is apparently observed that as solar multiple increases, the capacity factor is found to increase, too. Figure 6(b) displays the electricity generation with respect to solar multiple. A larger solar multiple signifies a larger solar collector area. Surplus energy from an outsized solar field (i.e., larger solar multiple) can be sent to the thermal energy storage and afterward delivered to the power block. The annual solar electricity generation is obtained to be 221.37 kWh/m²/a for a thermal energy storage of 6 h and solar multiple of 2.4. Figures 6(c) and 6(d) present the solar-to-electrical conversion efficiency with solar multiple for different plant capacities with and without provision of TES respectively. The highest efficiency with a thermal storage of 6 h is found to be 17.45% at a solar multiple of 2.5 for a 10 MW power plant (Fig. 6(c)), while the maximum efficiency without thermal storage is chronicled as 15.82% at a solar multiple of 1.25 for a 10 MW power plant. It is evident that the plant capacity is proportional to the overall efficiency. The reason for this is that at a higher plant capacity the power block offers a higher efficiency.

4.4 Thermal energy storage performance

Thermal energy storage (TES) is one of the most important components in the CSP plant. The TES has been used to store the solar energy in the form of latent heat, sensible heat, and thermo-chemical reactions which can be utilized to run the power block for an extended periods of time. Figure 7(a) shows that the maximum value of the annual electricity generation per unit area is 221.91 kWh/(m²·a) at TES= 8 h. This figure helps to optimize the size of the TES, the design of the solar field, and the solar electricity generation. Figure 7(b) gives the relation between TES and plant capacity factor which shows that capacity factor improves with augmentation of TES. It is found that the capacity factor is 32.5% for a TES of 6 h (considering TES as a designed system) and the capacity factor is maximum (32.6%) at 8 h.

4.5 Receiver thermal property

Figure 8(a) shows the relation between the incident thermal power on the solar receiver and the receiver thermal efficiency. With the increase in incident thermal power on the receiver, the thermal efficiency of the receiver also increases. Figure 8(b) correlates the mass flow rate with the receiver thermal efficiency. It is observed that as the high mass flow rate increases, the receiver thermal efficiency is found to be higher.

4.6 Daily performance assessment

The daily estimated performance of the plant for two typical days (one cloudy day in July and one sunny day in March) are shown in Fig. 9.

High DNI month (March): In March, the sunny periods are quite prolonged. In the morning, the thermal energy stored in the storage is low. As time goes by, the DNI increases, and consequently the receiver also absorbs more energy.

Low DNI month (July): In July, the energy absorbed by the receiver is not as much as that in comparison to the DNI month of March. The energy discharge time of the thermal energy storage is higher in March compared to July.

4.7 Plant capacity analysis

Figure 10 illustrates the significance of the plant sizing on plant performance. Figure 10(a) shows the plant size versus the atmospheric attenuation loss at various solar heliostat field boundary values. Atmospheric attenuation loss is an optical loss that occurs in the heliostat solar field because of the scattering and distortion of the sunlight as the solar flux travels the distance between the heliostat and receiver. Attenuation loss increases as the distance between the receiver and the heliostat increases. The results show that with the augmentation of the plant size, the atmospheric attenuation loss also increases. The amount of attenuation loss is also dependent on the solar heliostat field boundary. The attenuation loss is higher for a higher land boundary condition for a given plant size. The plant optical efficiency is also dependent upon the plant capacity and the total field area. A large solar tower power plant requires a large heliostat solar field. However, as the heliostat solar field increases, the land area increases, too, which leads to a poor field optical efficiency [23]. Figure 10(b) shows that with the augmentation of the plant capacity the required field area of the plant increases and with the increase in the plant size the field optical efficiency decreases. Figure 10(c) portrays the relation between the land use coefficient and plant capacity. Land use coefficient is the ratio between the field optical efficiency and the total field area. The land use coefficient also varies with the change of plant size. Land use efficiency is the product of solar electric efficiency and the land use factor (ratio of the aperture area of the reflectors and the total land area required). The land use efficiency and the overall energy efficiency increases initially, whose growth rate decreases with the increase in the power plant capacities ranging from 4 to 14 MW which is shown in Fig. 10(d). The overall land use efficiency of the 10 MW power plant is determined to be 5.04%. The overall energy efficiency of the 10 MW power plant is found to be 17.56% which implies that 17.56% of the solar irradiation on the reflector aperture area of a heliostat field can be transformed into net electricity.

4.8 Impact of DNI on plant performance

The solar tower power plant performance crucially depends upon the incident solar radiation, which is basically dependent on the climatic conditions and the geographical position of the plant site [23]. Figure 11 shows the impact of DNI on incident heat flux on the receiver, net electricity output, and monthly average overall efficiency of the solar tower power plant.

Figure 11(a) is the scatter plot which determines the correlation between the resource beam normal irradiance and incident heat flux on the receiver. With a larger amount of incident beam normal irradiance on the heliostat solar field, the higher amount of solar radiation is concentrated from the solar field to the receiver surface. With a large amount of beam normal irradiance, the incident heat flux on the receiver also increases. DNI is working as a fuel in the CSP plant to generate electricity. The annual electricity output of a plant seems to be a decisive factor for the economic viability of an investment. The annual electricity output depends on the DNI of the plant site [27]. Figure 11(b) shows the DNI versus net electrical output and overall efficiency of the CSP plant over the year. The DNI values are found acceptable during the entire year for the study site but are observed especially high in March, April, October and November. Hence during these months, net electrical output from the plant increases significantly. As a result, the overall efficiencies are also found high in these months with higher DNI values.

4.9 Power cycle performance

Figure 12(a) shows the field incident thermal energy versus PC efficiency of the CSP plant over the year. The PC efficiency increases with the increasing field incident thermal energy. Figure 12(b) is the scatter plot which illustrates the correlation between the PC efficiency and gross power output. With the increase in PC efficiency, the gross power output also increases.

4.10 Energy flow pattern

The energy flow diagram is used to analyze the component-wise energy loss of the solar power plant. The energy flow diagram of the designed 10 MW solar tower power plant is shown in Fig. 13. It is observed that all the components are responsible for energy losses. The maximum energy losses for a solar tower 10 MW power plant occur in the heliostat solar field (40.55%) followed by power block (33.63%). The receiver heat loss accounts for 7.3% of the total losses and the remaining other losses (energy required for feed pump, mirror tracking and losses in pipe etc.) contributes to 0.81% of the total losses.

4.11 Plant economics

The main objective of the economic study of a power plant is to determine the inherent profitability of a project regardless of its financing. It helps the project planner to plan the project and to have a complete idea about the conceivable limitations to reduce its risks. There are different methods to measure the economic viability of an electric generation project but the levelized cost of energy (LCOE) is the most commonly used benchmark tool to evaluate the cost-effectiveness when comparing the technologies of electricity generation or considering grid parities for emerging technologies [44]. LCOE calculates the cost of electricity throughout the whole system over a lifetime.

Figure 14(a) shows the LCOE profile with respect to receiver radius profiles found for the five tower heights. The profile of the LCOE is quite clear and gives well-defined minimum value for the various options. The lowest LCOE is (19.11 c/kWh) obtained with receivers radius of 1.8 m and a tower height of 110 m. For the considered tower height of 115 m, the LCOE is found to be 19.52 c/kWh. Figure 14(b) indicates that for a thermal energy storage capacity of 6 h and for a solar multiple of 2.4, the value of LCOE is found to be the minimum (19.52 c/kWh). Figure 14(c) illustrates that the plant capacity has a significant impact on plant LCOE. At a higher plant capacity, the LCOE is found to be low but at a lower plant capacity, the LCOE is observed to be high due to the lower annual power generation. Figure 14(d) shows the sensitivity analysis of LCOE which explains the dependence of LCOE on various sensitivity parameters such as capacity factor, solar multiple, nominal discount rate, inflation rate, and heliostat field cost.

5 Performance comparison

The present paper has conducted a performance evaluation of a solar tower power plant in a low DNI zone which has not been reported anywhere before. The obtained results of the study are therefore compared with the testified results of the existent concentrated solar thermal system in order to realize the success of the proposed scheme. A comparison has been drawn in Table 2 between the solar thermal technologies in a high sun belt and the designed system in a low sun belt, in terms of various normalized parameters such as capacity factor, plant efficiency, land demand, water usage, gross to net conversion, plant solar-to-electricity conversion efficiency, and LCOE. The obtained results out of the designed system, subjected to low DNI are found not below par, but comparable to some extent with the performance results of such CSP plants at higher DNI values.

6 Conclusions

Solar power tower systems are considered as one of the most potential technologies for generating solar electricity. The present study tries to examine the solar thermal plant characterization in terms of heliostat field performance, thermal performance, and economic performance in a low DNI region. Different critical analyses such as heliostat mirror sizing on plant performance, tower height characterization, effect of solar multiple on electricity generation, thermal energy storage performance, receiver thermal property characterization, daily performance assessment of the plant, influence of DNI on plant performance, energy flow analysis, and plant economics have been evaluated. The analysis indicates that incorporation of thermal energy storage reduces the levelized cost of energy and augments the plant capacity. The capacity factor, plant efficiency, and the LCOE are found to be 32.50%, 17.56%, and 0.1952 $/kWh respectively. The analysis indicates that the solar tower power performance is highly dependent on the heliostat field efficiency, receiver efficiency, solar multiple, thermal energy storage, and most importantly, the DNI of the region. It is evident from the study that a higher DNI gives a higher plant efficiency. A higher field optical efficiency and a higher receiver efficiency bring about a higher plant performance in terms of power generation. Besides, solar multiple, capacity factor, and the TES are found to be strongly related. At a higher solar multiple and a higher storage capacity, the LCOE is found to be lower. It is also observed that the maximum amount of energy losses occur in the heliostat solar field (40.55%) followed by power block (33.63%). The analysis gives the essential data for the assessment of several features of the CSP technology which is helpful in designing of solar tower power plants in low DNI conditions. The obtained results indicate promising appreciable performance and potential for application of the CSP system at a low sun belt location. However, there are certain difficulties for adopting the CSP at a low sun belt location. It is evident that the higher solar multiple and the thermal energy storage is imperative to materialize the CSP technology in a lower DNI zone for realizing a higher capacity factor and a plant efficiency. Further, a higher solar multiple necessitates a little bit greater solar field and more heliostat mirrors to produce adequate electrical energy. The increase in solar field area with more numbers of collector mirrors and the suitable thermal energy storage capacity add to the investment cost as well as a slight augment in the LCOE of the plant.

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