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Investigating the environmental and socio‐economic impacts of grid‐tied photovoltaic and on‐shore wind systems in Bangladesh

2018; Institution of Engineering and Technology; Volume: 12; Issue: 9 Linguagem: Inglês

10.1049/iet-rpg.2017.0751

1752-1424

Md Nurunnabi, Naruttam Kumar Roy, M. A. Mahmud,

Photovoltaic Systems and Sustainability

IET Renewable Power GenerationVolume 12, Issue 9 p. 1082-1090 Case StudyFree Access Investigating the environmental and socio-economic impacts of grid-tied photovoltaic and on-shore wind systems in Bangladesh Md Nurunnabi, Md Nurunnabi Department of Electrical and Electronic Engineering, Khulna University of Engineering & Technology, Khulna, 9203 BangladeshSearch for more papers by this authorNaruttam Kumar Roy, Corresponding Author Naruttam Kumar Roy nkroy@eee.kuet.ac.bd orcid.org/0000-0002-6542-7684 Department of Electrical and Electronic Engineering, Khulna University of Engineering & Technology, Khulna, 9203 BangladeshSearch for more papers by this authorMd Apel Mahmud, Md Apel Mahmud School of Engineering, Deakin University, Waurn Ponds, VIC, 3220 AustraliaSearch for more papers by this author Md Nurunnabi, Md Nurunnabi Department of Electrical and Electronic Engineering, Khulna University of Engineering & Technology, Khulna, 9203 BangladeshSearch for more papers by this authorNaruttam Kumar Roy, Corresponding Author Naruttam Kumar Roy nkroy@eee.kuet.ac.bd orcid.org/0000-0002-6542-7684 Department of Electrical and Electronic Engineering, Khulna University of Engineering & Technology, Khulna, 9203 BangladeshSearch for more papers by this authorMd Apel Mahmud, Md Apel Mahmud School of Engineering, Deakin University, Waurn Ponds, VIC, 3220 AustraliaSearch for more papers by this author First published: 12 June 2018 https://doi.org/10.1049/iet-rpg.2017.0751Citations: 13AboutSectionsPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat Abstract Current power generation scenarios all over the world are not climate friendly as the generation systems are mainly dependent on fossil fuels that produce greenhouse gas (GHG). As renewable energies (especially solar and wind energies) have the sustainable characteristics, by replacing the conventional energy system with them, it is possible to significantly contribute to reducing the dependency on fossil fuels as well as GHG emissions. Though biomass is the primary renewable source in Bangladesh, this study is exploring new options in photovoltaic (PV) and on-shore wind in the 0.5–2 MW capacity range. This research presents environmental and socio-economic impacts of grid-connected hybrid (PV/wind) power systems by investigating the potentials of the solar and wind energy with considering various sensitivity variables for two different locations, namely Magnama and Dinajpur, in Bangladesh. The main goal of this research is to generate the lowest possible adverse socio-economic and environmental impacts ensuring a certain degree of monetary benefits. Three sizes of plants have been chosen for quantifying the variations in socio-economic and environmental impacts. It is found that the proposed model of the hybrid power system can maximise the benefits by reducing the adverse effects of conventional power plants. 1 Introduction Every sector of modern civilisation is dependent on energy which comes from various energy sources such as nuclear energy, renewable plants and fossil fuels (coal, oil and natural gas). The combustion of fossil fuels emits a huge amount of greenhouse gases (GHGs) such as carbon dioxide, sulphur dioxide, and nitrogen dioxide that harm the atmosphere and health of the population [1, 2]. Therefore, there is an acute need for a power generation system which is reliable and sustainable that overcomes various problems related to the existing power system. As renewable energy (RE) can play an important role in reducing global warming and they are clean and environmental friendly, the insertion of them instead of fossil fuels would be a great alternative solution for the present situation [3-5]. Recently, hybrid power systems using RE are becoming popular due to their potential benefits on the environment [2, 6]. The electricity demand of Bangladesh is increasing due to the advancement of economic activities in the country with sustained gross domestic product growth [7]. The maximum demand in FY 2016 was 11,405 MW which is 10.91% higher than the previous year [8]. With the increase in energy demand, per capita GHG emission rate is increasing day by day [9]. The per capita carbon dioxide (CO2) emissions from grid electricity in 2015 were 0.16 ton/annum. Though this value is lower than the world's average rate, it would go up in the near future due to the integration of a large amount of coal-based power generation system [9, 10]. According to the power development board of Bangladesh, power generation systems in this country are highly dependent on natural gas and in 2016, a 68.63% of the total net generation (national) came from natural gas; however, the present reserve of natural gas would be depleted by a decade [11]. Therefore, finding an alternative way of energy generation in Bangladesh is very urgently needed [12]. There is no other way for meeting the future power demand except to increase the utilisation of RE which is one of the important strategies adopted as part of fuel diversification programme [13]. Most of the developed countries are highly motivated to increase the contribution of RE systems to the national grid [3]. Currently, RE sources meet 15%–20% of the world's energy demand and it is increasing progressively [3, 6]. However, the development of RE is not significant in Bangladesh. The RE contributes only 3.7% of the total capacity where the hydroelectricity contributes 1.86% and other renewables contribute the rest [8]. An extensive research has been conducted worldwide in the area of RE but the techno-economic assessments of different RE sources in Bangladesh received much less attention. Asif et al. [14] describe the prominent features of Grameen Shakti programme that provides the micro-generation renewable systems to the rural population of Bangladesh over the last 14 years. By investigating the different RE projects, it is observed that with careful advanced planning RE sources can provide comprehensive socio-economic and environmental benefits to the rural community in Bangladesh. Some of the obstacles that need to be overwhelmed by the successful development of RE technology sector and improvement of rural livelihoods are also identified [15]. A recent study by Baki et al. [3] presented a thorough review of the current status and future potentials of RE sector in Bangladesh. Hossain et al. [12] investigated the business policy and problem for the solar energy system in Bangladesh. By investigating the solar energy potential in two different locations in Bangladesh namely Sirajganj and Jessore district, the analysis showed that the solar home systems for small business enterprise and household with small income generation are more viable compared with solar photovoltaic (PV) systems used for only household lighting [16]. A feasibility study has been performed for a stand-alone hybrid system in St. Martin Island, Bangladesh, and the cost of energy (COE) is found to be $0.345/kWh which is much higher than the present grid price of Bangladesh [17]. A PV/diesel hybrid system configuration has been conducted in the Northern part of Bangladesh and analysis showed that it is more economical than the only diesel system [18]. Bangladesh has a good potential for harnessing RE sources such as solar and wind [15]. Due to the short of literature in the sense of grid-connected RE system, there are lots of scopes to concentrate on this topic. For achieving the target value of renewable power generation (10 of the total generation) within 2020 [3, 8], it is highly essential to investigate the environmental issues of Bangladesh to bring the higher percentage of RE sources into the energy mix to build an eco-friendly environment for the future. Therefore, the specific objectives of this paper are: to investigate the RE (solar and wind) economics in Bangladesh, to analyse the feasibility of hybrid energy systems in a specific meteorological condition, to determine the environmental and socio-economic impacts of hybrid energy systems connected to the national grid of Bangladesh, and to determine how the access to electricity of the lower income group can be increased by RE systems. 2 RE resources Although the GHG emission is not a primary concern for a developing country like Bangladesh, the incorporation of RE is obvious because of rapidly reducing natural resources. Besides biomass Bangladesh has few RE potentials among which wind and solar are promising sources. 2.1 Wind energy resources Although the Meteorological Department of Bangladesh implemented the 20 monitoring stations for measuring wind resource data, it is essential to implement more stations in the coastal area to study the prospects of wind precisely. Most of the wind speed data are not taken at the desired level [7, 19]. The wind speed at desired height can be obtained by using the logarithmic law that is given as follows [20]: (1) where V2 represents the wind speed at height h2 (m/s), V1 is the known wind speed at height h1 (m/s), h2 is the desired level where wind speed is needed (m), Zo is roughness length in the current wind direction (m), and h1 is the anemometer height (m). In this paper, after collecting wind speed data [19], an area has been selected according to the availability of high wind energy potential which is Magnama located in the South-East part of Bangladesh. Fig. 1 shows the hourly average wind speed around the year at Magnama, Cox's Bazar. Fig. 1Open in figure viewerPowerPoint Wind speed in a year at Magnama (40 m height) 2.2 Solar energy resources Bangladesh having geographical location between 20.30° and 26.38° North latitude and 88.04° and 92.44° East longitude is an ideal location for solar energy harvesting [15]. From the radiation data, it is found that the daily solar radiation varies between 4 and 6.5 kWh/m2 [21, 22] over Bangladesh. This strong solar potential indicates that by implementing the solar power system, it is possible to electrify the maximum region of Bangladesh particularly in the northern part of this country. In this research, investigating and analysing the solar potential has been performed not only for power generation but also to reduce the GHG emission which is an urgent need. Fig. 2a shows the daily solar radiation for 14 locations in Bangladesh and it is observed that the highest solar radiation areas are Dinajpur and Rajshahi. Fig. 2b shows the average daily solar radiation and clearness index for the Dinajpur (25°37′N 88°38′E) and Magnama (21°87′N 91°87′E). Fig. 2Open in figure viewerPowerPoint Solar data(a) Solar radiation for 14 locationsof Bangladesh, (b) Monthly averagesolar radiation and clearness index for selected sites [22] 3 RE economics The cost parameters associated with the renewable power generation systems are described in this section. 3.1 Net present cost (NPC) An NPC means the present value of all components that are installed in the plant minus the present value of all the revenues that it earns over the lifespan [6, 20]. 3.2 Total annualised cost The total NPC in a year is called the total annualised cost. It expressed as [6, 20] (2) where CNPC, Total, i, CRF, and R plant--life represents the total NPC in the dollar, the annual real interest rate, capital recovery factor and the plant lifetime in year, respectively. 3.3 Capital recovery factor It is a ratio which is needed to calculate the present value of a series of equal yearly cash flows. It can be expressed as [6, 20] (3) where n is the number of years and i is the real interest rate in a year. 3.4 Annual real interest rate It is the discount rate which is used to transform between one-time costs and yearly costs. It is calculated as follows [6, 20]: (4) where i, i′ and F is the real interest, nominal interest and annual inflation rate, respectively. 3.5 Cost of energy It is defined as the mean value of cost per kWh of useful electrical energy produced by the plant. Total electrical loads are divided into AC primary load and DC primary load. It is calculated by the following equation [6, 20]: (5) where Cyr,total, ACload and DCload is the total annualised cost, AC primary load and DC primary load, respectively. 3.6 Discount rate and inflation rate The interest rate or discount rate is used to convert between one-time and annualised costs. The average value of last few years of interest rate in Bangladesh is 11.78% [23]. Expected inflation rate has been taken as 5.71 for economic analysis [23]. 3.7 System fixed capital cost The fixed capital cost involves housing the battery bank, charge controllers, generator, inverter and other relevant electrical instruments. It also includes the labor, engineering design and construction costs of distribution lines. An estimate of the fixed capital cost including 3 km long three-phase distribution lines has been estimated at $19,320/MW [18, 24]. 3.8 System fixed operation and maintenance (O&M) cost A system's fixed O&M cost firstly includes labor and insurance costs. Assuming the engineer and technician is full-time employed in the powerhouse, the annual fixed O&M cost has been taken as $15/kW [25]. 3.9 Project lifetime It is the number of years the system is operated which is needed to compute the annualised replacement and capital cost of each component, as well as the total NPC of the system. In this paper, the project lifetime has been taken as 25 years. 4 Components costs of the hybrid energy system The components cost of the hybrid energy system are given below. 4.1 Solar PV In order to use reliable economic inputs, after contacting several companies and analysing some technical reports [24-27] and their quotations and specifications, the capital cost for the solar system is estimated as $1340/kWp with 20 years warranty [26]. This cost also includes various equipment cost, installation cost, shipping cost and maintenance cost. The replacement cost of solar panel is estimated as 67% of the total capital cost and the O&M cost is estimated as $26/ kWp per year [24]. 4.2 Wind turbine The H21.0–100 kW wind turbine (WT) has been selected for the analysis due to its robust characteristics [28]. The capital cost of a typical onshore wind power system is associated with various factors such as the turbine cost, plant installation cost, planning cost and grid connection cost. The installation cost of a wind power project is dominated by the capital cost for the WTs (including towers and installation) and this can be as much as 64% of the total plant installed cost that is shown in Table 1 [29]. Table 1. Distribution of the total capital cost for a typical onshore wind power system [29] Section Contribution(%) wind turbine 64% foundation 16% grid connection 11% planning & miscellaneous 9% total 100% In this paper, the capital cost of a wind turbine is estimated as $161,125/100 kW [28], as a consequence, the total capital cost of a typical onshore wind power system is found approximately $251,758/100 kW. The replacement and O&M costs are estimated 75% and 2% of the total capital cost, respectively [30]. 4.3 Inverter In this research, the capital cost including shipment cost of the inverter is taken as $214/kW [26]. The replacement cost is 93% of total capital and O&M cost is estimated as 1.2% of the capital cost [30]. 4.4 Grid parameter In grid-connected design, a grid supplies power when there is not enough renewable power to meet the load demand and it consumes power when an excessive power is available. In this paper, the unit purchase price is estimated as $0.0975 per kWh [8]. Estimating the sellback price is a very argumental issue because no fixed sellback price is declared by the power division of Bangladesh [31]. A sensibility analysis has been performed by assuming various sellback prices and the nominal discount rates at fixed grid power price. 4.5 Land requirement for plant installation For the solar system, a 9.29 m2 per 100 kW footprint is needed for plant installation. Therefore, rooftops are the best suited for implementing 1, 2 even 3 MW plant. On the other hand, for a WT, a 46.45 m2 footprint area is needed for a 100 kW size [25-28]. According to the National Renewable Energy Laboratory, the area requirements for wind energy are about 3000–17,000 m2 per MW where the permanent infrastructure impacts amounted to 3000–4000 m2, and temporary impacts amounted to 2000–10,000 m2 [32]. In terms of land impact, wind plants sited on cropland require the largest total land. In this paper, 36,422 m2 areas for every MW of wind farm have been estimated. Most of the land used was devoted to roads, where only 10% of the total lands are needed for installing WTs, 6% for substations, and 2% for transmission infrastructures. Land requirements for the land base system are considered 24,281 m2/MW for crystalline and 28,328 m2/MW for thin film-based PV farms [33]. It should be mentioned that depending on various parameters like region and efficiency of solar panel, the actual land requirement may also vary. 5 Load estimation for the proposed region The load estimation is the preliminary essential part of plant installation. The estimation of the power demand was done after analysing the previously made case studies of rural electrification in developing countries [18, 30, 34, 35]. In this paper, the electric load demand is divided into the following three major categories such as household/domestic sector which includes lighting, TV, radio and baking appliances; commercial loads (shops); community loads which consist of school lighting, health clinic which includes vaccine refrigerator, communication radio, television, microscope, computer and printer and deferrable loads (water supply and irrigation systems, battery run auto-rickshaw). The total electric load estimated for the listed appliances above was summed up to get the required load to be supplied by the system [36]. 5.1 Electricity demand at Dinajpur The case study of this paper involves serving the load of an area of 300 households (average 5 people per household) located at Daptori Para, Dinajpur. The energy access of households was categorised into three different categories based on economic condition, i.e. high-class, medium-class and low-class household. For generating more accurate hourly load profile, a 10% hour to hour random variability and 10% day-to-day random variability has been considered. The total daily average electricity demand at Daptori Para is found as 2627 kWh and the load factor is found as 0.28 where the peak load is 395 kW. 5.2 Electricity demand at Magnama, cox's bazar In Magnama, more than 1200 families are living but only a very few of them are getting access to electricity [37]. In this paper, 100 families have been considered as a rich family having four light bulbs, three ceiling fans, one small TV, one refrigerator and one water pump for each family. Seven hundred families have been estimated as a solvent family having four lights, two fans and one TV set for each family. In the poor category, 400 families have been considered having two lights and one fan of each family. According to the load estimation, 50 shops, one community health centre, one school and 100 street lights are also considered for that region. By adding the 10% random variability, a peak load is observed as 645 kW, load factor 0.26, and daily average load 4029 kWh. 6 Methodology Flowchart of the optimisation methodology that is used in this research is shown in Fig. 3. Initially, the technical characteristics of PV panels, WTs, and converters beside with their capital and O&M costs are fed as an input parameter to HOMER [20]. Multiple sensitivity variables are set for sensitivity analysis. Various sizes of the component have been specified as a search space for selecting the best combination of WTs/PV/converters. Utilising the value of daily average solar radiation with clearness index, temperature data, wind speed, project economic and system constraints, project lifetime, grid parameters which contain grid power price and emission rate and the consumer power demand, and sensitivity variables, an optimum solution is determined. By calculating the optimal total system cost and device configuration, an optimal sizing procedure is performed for each combination of devices. Finally, the overall optimal system configuration and the corresponding optimisation results are found based on the lowest NPC. Fig. 3Open in figure viewerPowerPoint Flowchart of the optimisation methodology 6.1 Sensitivity variables A detailed scenario of a system model for the specific meteorological condition has been found by analysing sensitivity and optimising output. It also gives a marginal condition whether the hybrid systems are economically or environmentally feasible or not. This also needed in support decision making or the improvement of certain conditions from the proposed model. To observe the impacts of solar irradiation variability, wind resources, and some economic constraints and to make right decisions in developing hybrid system models, a sensitivity analysis has been performed. In this paper, the model has been simulated based on the sensitivity variables: wind speed or solar irradiation, grid electricity price, grid sellback price, nominal discount rate and system size. 6.2 Sensitivity results for the optimum configuration After considering all input parameters associated with the system, a sensitivity analysis has been performed using optimal system type for obtaining the optimum system configuration at desired locations. In these cases, sensitivity variables were grid power price ($/kWh), solar radiation (kWh/m2/day) and wind speed (m/s). Fig. 4 shows the sensitivity results for the specific locations. Fig. 4a shows that when the solar radiation is above the 4 kWh/m2/day, the PV/grid system is feasible at Dinajpur region. As the solar radiation at Dinajpur region lies between 4 and 6.5 kWh/m2/day, it is an ideal location for implementing the PV/grid system model. Fig. 4Open in figure viewerPowerPoint Sensitivity analysis results for variable grid power price(a) Dinajpur,(b) Magnama On the other hand, from Fig. 4b, it can be seen that with the increase in grid power price, different types of feasible system configurations were found for Magnama's local weather condition. At $0.097/kWh (country's levelised COE or LCOE point) [8], for instance, a PV/grid system is feasible when the wind speed is observed below 5.5 m/s and wind/grid for above the 5.5 m/s. With the increase in the grid power price, the feasible system configuration will be changed at the same sensitivity variable range of wind speed. For example, if the grid power price increases $0.2/kWh from the current LCOE then the PV/wind/grid system will be feasible between 4.8 and 6.6 m/s wind speed range and PV/grid system for beyond this range and wind/grid system for above this range. As the wind speed is observed between 6 and 7 m/s in Magnama region, the wind/grid system is the most feasible solution in this region. 7 Energy, socio-economic and environmental impact After finding the optimal system configuration for a specific location, an optimisation process has been conducted for evaluating the socio-economic impact considering a plant capacity in the range of 0.5–2 MW. 7.1 Energy impact Installing the proposed model in the suitable area will result in a significant amount of electrical energy. Table 2 shows the estimated annual renewable electricity generation in both regions. The first and second columns of this the table indicate the size of the plant and name of the region, respectively. The third column of Table 2 'Type of plant' shows which type of RE is estimated in that particular location. As Dinajpur has high solar potential, a grid-connected PV system would be best suited for economically and environmentally. On the other hand, Magnama has high wind energy. Due to the availability of high wind energy, a grid-connected wind farm is the best choice in that location. Fourth column 'generation (kWh/year)' reflects the total output energy that comes from the RE. It shows that by installing a 500 kW plant, it is possible to produce 810,820 kWh (annual) for Dinajpur region and 1,698,140 kWh (annual) for Magnama region. The next column of the table 'Energy purchased (kWh)' indicates the total amount of energy that is purchased from the grid when RE sources are not capable of producing enough power. When excess electricity is produced by this system, it will sell this to the grid as shown in the next column. Table 2. Power generation scenario Size of the plant Region Type of plant Generation, kWh/yr Energy purchased, kWh/yr Energy sold, kWh/yr 500 kW Dinajpur (PV + grid) 810,820 715,110 522,868 Magnama (wind + grid) 1,698,140 621,616 849,171 1 MW Dinajpur (PV + grid) 1,621,641 672,415 1,228,724 Magnama (wind + grid) 3,396,281 399,009 2,324,704 2 MW Dinajpur (PV + grid) 3,243,282 644,395 2,737,965 Magnama (wind + grid) 6,792,561 225,215 5,547,192 7.2 Economic impact Economic analysis for hybrid system model is dependent on various input variables such cost of installing and operating of the plant and economic constrains such as nominal discount rate, real discount rate, expected inflation rate, project lifetime which are described in Sections 3 and 4. A detail economic analysis has been evaluated after specifying the suitable input and sensitivity variables. 7.2.1 Sensitivity results A detail sensitivity analysis has been performed for the uncertainty of some input variable such as nominal discount rate and grid sellback price. By keeping the grid power price at a fixed rate (LCOE), the sensitivity analysis has been done by setting the certain range of sellback price ($/kWh) and nominal discount rate (%). HOMER simulates the results for every possible sensitivity cases which are shown in Fig. 5. From Fig. 5a, it can be seen that PV/grid system is feasible when grid sellback price is above $0.06/kWh for a certain condition. It also observed that, with the increase in the nominal discount rate, the feasible grid sellback price is increases, i.e., the grid sellback price is dependent on the nominal discount rate or vice versa. For instance, in Fig. 5a, the minimum feasible sellback price is found $0.105/kWh for 11.78% nominal discount rate at the feasible situation. Similarly, the minimum feasible sellback price is found $0.07/kWh at 11.78% discount rate point for Magnama which is shown in Fig. 5b. From this sensitivity analysis, it is possible to find out a suitable grid sellback price according to the nominal discount rate or vice versa at a certain environmental condition. Fig. 5Open in figure viewerPowerPoint Sensitivity analysis results for fixed grid power price ($0.097/kWh)(a) Dinajpur,(b) Magnama 7.2.2 Optimisation results The socio-economic analysis has been carried out with the aid of HOMER tools by considering all economic parameters as input. Optimisation results give the economic output for every possible system configuration according to the sensitivity variable. Fig. 6 shows the cost summary for two different locations which includes the initial capital, O&M cost, faulty equipment replacement cost and salvage value for 500 kW, 1, and 2 MW power plant, respectively. Fig. 6a shows the cost summary for Dinajpur and Fig. 6b for Magnama. It is observed that with replacing the plant size with double capacity, approximately twice capital and replacement cost is required for both regions. On the other hand, the O&M and salvage value is declined around fourfold and twofold, respectively. More importantly, in Magnama region, the initial investment and other cost values are required almost 66% higher than the Dinajpur region for the same capacity of the plant. Fig. 6Open in figure viewerPowerPoint Cash-flow summary(a) Dinajpur (PV/grid),(b) Magnama(wind/grid) Fig. 7a shows the variations in NPC and COE for Dinajpur (PV/grid) while Fig. 7b for Magnama (wind/grid) with varying the plant's size. It also shows a comparative analysis between only grid system and grid-tied hybrid energy systems. It can be visualised that, in case of COE, the similar decreasing pattern is observed for both regions; however, the different changing scenario for the NPC value has been seen. For Dinajpur region, the PV/grid system model (0.5 to 2 MW) requires comparatively lower NPC and COE value than the only grid system. On the other hand, in Magnama region, less NPC value is required for implementing up to 1 MW wind/grid model compared to the only grid system but for 2 MW hybrid system model higher NPC value is needed than the only grid system. From this figure, it can be concluded that all models in both regions have the significant economic benefit except 2 MW plant in Magnama. Though 2 MW plant in Magnama region is not economically feasible, it has massive social and environmental benefit which is described in the next section. Fig. 7Open in figure viewerPowerPoint Comparison of the NPC ($) and COE ($/kWh)(a) Dinajpur (PV/grid),(b) Magnama(wind/grid) 7.3 Social impact This section explores the social impact of RE (solar and wind) on the basis of following three parts.