Electrical power crisis solution by the developing renewable energy based power generation expansion

Bagdadee, Amam Hossain; Zhang, Li Article Electrical power crisis solution by the developing renewable energy based power generation expansion Energy Reports Provided in Cooperation with: Elsevier Suggested Citation: Bagdadee, Amam Hossain; Zhang, Li (2020) : Electrical power crisis solution by the developing renewable energy based power generation expansion, Energy Reports, ISSN 2352-4847, Elsevier, Amsterdam, Vol. 6, Iss. 2, pp. 480-490, https://doi.org/10.1016/j.egyr.2019.11.106 This Version is available at: https://hdl.handle.net/10419/243920 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by-nc-nd/4.0/ Available online at www.sciencedirect.com ScienceDirect Energy Reports 6 (2020) 480–490 www.elsevier.com/locate/egyr The 6th International Conference on Power and Energy Systems Engineering (CPESE 2019), 20–23 September 2019, Okinawa, Japan Electrical power crisis solution by the developing renewable energy based power generation expansion Amam Hossain Bagdadee, Li Zhang∗ College of Energy and Electrical Engineering, Hohai University, Nanjing 210098, China Received 7 October 2019; accepted 22 November 2019 Abstract This paper proposes a different hybrid system that considers the intelligible and complex to understand the problem of regulating the expansion of conventional power plants. The current reality is determined on a long-term power generation expansion plan for Bangladesh from 2016 to 2030. The discontent of the framework and weaknesses in the power systems are facing the main problem by the energy crisis. Thus, long-term renewable energy based power generation model and the use of inhabited coal are inspected in the extent of the costs of natural expansion and green impact. The results demonstrate that in 2030 the power generation needed to meet future demand is assessed at 160TWh. The proposed structure includes two steps. In the first step, the assessment of the importance of technology is carried out using a hybrid methodology and benefits from a system of excellent descriptions, starting points, and risk assessments in the second step that will make a multi-objective show to improve our generation’s expansion plans. Two objective capacities are considered in this model. That is, adding weight to the overall placement trend and reducing overall costs. The implementation of renewable power is a great decision to describe the lake of power in Bangladesh because it requires minimal effort and less danger. This activity is essential for developing sustainable power generation in Bangladesh. The numerical model is solved using the NSGA-II algorithm, and the effect analysis is carried out on the key parameters. The results show an expanded offer of constant renewable sources in power generation for ensuring sufficient power supply in Bangladesh. c 2019 Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer-review under responsibility of the scientific committee of the 6th International Conference on Power and Energy Systems Engineering (CPESE 2019). Keywords: Energy crisis; Renewable energy; Power generation expansion; Bangladesh 1. Introduction Energy generation expansion plans for power plants include the determination of alternative power generation innovations that will be added to the current framework, and when and where it should be developed to meet the energy demand for development during the perspective development period. Electricity, a type of energy to observe, plays a vital role in the current social order [1]. Power plants convert various renewable energy and ∗Corresponding author. E-mail addresses: [email protected] (A.H. Bagdadee), [email protected] (L. Zhang). https://doi.org/10.1016/j.egyr.2019.11.106 2352-4847/ c 2019 Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/ licenses/by-nc-nd/4.0/). Peer-review under responsibility of the scientific committee of the 6th International Conference on Power and Energy Systems Engineering (CPESE 2019). A.H. Bagdadee and L. Zhang / Energy Reports 6 (2020) 480–490 481 non-renewable energy assets, such as fossil fuels, a global energy, solar energy, and wind energy, into electricity as indicated by the 2018 Global Status report that around 77.9% of all electricity produced is supplied through fossil assets. Recently, the government has promoted the supply of renewable energy in its energy portfolio, due to difficulties such as fossil fuel constraints, ecosystem pollution, the importance of strengthening energy mixtures, and the possibility of getting more incentives from fossil assets [2]. The problem of spreading generation expansion was considered in all admirations, but a large number of experiments focused on finding the lowest cost expansion plan [3]. However, there are several conflicting goals, such as environmental impacts, reliability, imported fuels, and security in the regulation of generation expansion. Nowadays power is acting a great function wherever modern community lives and works in the industry, agribusiness, transportation, etc. The nation’s living stander and daily prosperities are directly depended on the electricity accessibility. The electricity consumption is growing steadily as technological innovation [4]. Sufficient and reliable electricity sources are essential things that need to be considered for sustainable and productive economic progress as well as reducing demands. In Bangladesh, 90 million of the 160 million people can access electricity, but high-quality power is still uncertain because of the energy crisis. In this industry need to meet the requirements lost in the future demand. As a result, the power generation industry requires generation expansion planning that can be adjusted to achieve harmony between free-market activities [5]. Generation expansion assesses speculation and operational choices for various technologies as a matter of longterm regulation. In principle, the focus of the generation expansion planning problem is on the economic approach. Bangladesh is considered unproductive against the effects of climate change [6]. There are need proper guidelines from the Bangladesh Government for reducing the impact of the environment, need to regulate the green generation expansion of power plants to meet demand with low cost. This paper shows a hybrid system to determine Bangladesh’s long-term power expansion plans from 2016 to 2030. These issues are considered from the perspective of a sustainable development approach. This study essential and obligatory factors in addition to the usual generation expansion crisis, and proposes a system of two steps to estimate the results of Bangladesh. The fundamental of this analysis is the primary stage plans to research critical and viable factors through a hybrid network analysis process for hazard investigation to investigate important and successful factors. At that time, the power plant was obtained by a multi-purpose validation model. This model is explained by non-predominant genetic calculations (NSGA-II). 2. Literature review Bangladesh has more than 160 million people, one of the most populous countries in the world. Agribusiness has been a fundamental source of income for the country’s people. However, Bangladesh’s gross domestic product (Gross Domestic Product) is 7.75% in 2018 [7]. Central Bank of Bangladesh estimates that economic progress will be more than 8.50% in 2019. Rapid urbanization, filled with relentless financial repairs, has created a massive demand for electricity. It is essential to anticipate the necessary components of poverty, increased monetary, rational structural movements, and security in all countries with poverty. The Bangladesh government must ensure that the electric power is functioning and are usually appropriately moved for public demand. The provisions of the electricity companies are facing the immorality effects of the energy crisis [8]. A stable power supply is essential to promote financial development. 2.1. Crises of the power sector Following a few paragraphs explain the interruptions and load shedding showing the intensity of power crisis: According to Table 1, six types of faults caused a blackout in transmission. In national grids are Partial Power failure due to trouble in a generation, partial power outage because of issues in the network by the S/S device, halfway power outage. The breakdown in the transmission line and partial power outage because of lightning in the transmission line/Electrical storm, incomplete power outage because of electricity in the Transmission Line/Rainstorm and Aggregate system discontent [9]. Among them, Partial Power failure due to trouble in a generation is the most dominant one. People of Bangladesh are suffering much due to normal load shedding, and it becomes a common term in the Power sector of Bangladesh. According to dictionary.com, load-shedding is the cutting off the electric current on specific lines when the demand grows more significant than the supply. In FY 2016–17 load shedding imposed on 482 A.H. Bagdadee and L. Zhang / Energy Reports 6 (2020) 480–490 Table 1. Interruption of national grid. Sl. no Type of fault Total number of fault Total duration (hours/minutes) 1Power failure due 95 06/44 trouble in generation 2Power failure due to 15 50/43 trouble in grid S/S Equipment 3Power failure due to 14 16/55 fault in transmission line 4due to the lightning 02 00/33 on transmission line/Thunder Storm 5Partial Grid failure 05 01/28 6Total Grid failure 00 00 351 days which was in the previous fiscal year 358 days which signifies how frequently load shedding occurs [10]. Table 2 shows that in November 2017 total demand was 12352 MW and complete load shedding by BPDB was 4212 MW. The highest load shed of 873 has done in Dhaka [11]. Table 2. Peak demand & load shed. Area Demand Load shed Area Demand Load shed (MW) (MW) (MW) (MW) Dhaka 3825 873 Mymen 745 283 Singh Chittago 1670 480 Sylhet 723 190 ng Khulna 1780 785 Barishal 499 214 Rajshah 1510 725 Rangpu 815 227 i r Comilla 815 435 Total =12352 4212 The following Fig. 1 shows the load shedding of the same day at a different time. It is clear from the graph that the majority of the load shedding has done between 18:30 and 21:00. However, the highest load shedding occurred at 19:3. Fig. 1. Load shed at a different hour. As a result of these persisting problems cause low access to electricity and poor reliability. Many of the rural areas and inhabitants are still out of reach of power. So they cannot contribute to the country’s GDP as much as they could. Another side effect is that people who have access to power are not getting it correctly. Extensive load A.H. Bagdadee and L. Zhang / Energy Reports 6 (2020) 480–490 483 shedding is done by the electricity company which makes the life of general people horrible. All types of industries failed to achieve their objective production which in turn lowered down their contribution to GDP. 2.2. Renewable energy potential Bangladesh invests in the supply of abundant renewable energy sources. Among renewable resources, solar, wind, biomass and hydropower can be used successfully in Bangladesh. 2.2.1. Solar energy Bangladesh is located somewhere in the range of 20.300 to 26.380 in the north and 88.040 to 92.440 in the east. This is the best area to use solar energy. Annual radiation amount is ranging from 1840 to 1575 kWh/m2 and 50%–100% higher than in Europe [12]. The expertise of solar power related to the framework is around 50,174 MW. In Bangladesh, the amount of solar radiation fluctuates from season to season. In this way, we might not get the same solar energy regularly. The most extreme radiation doses can be accessed from the spring of April to at least December and January. Fig. 2 shows the design of natural solar radiation for each month. Fig. 2. Monthly average solar radiation profile in Bangladesh [13]. 2.2.2. Wind energy The lack of robust wind speed information has hampered the assessment of wind energy property. There is in wind speed report announcing that it is reliable and used in Bangladesh wind energy assessments. Several coastal zone areas were investigated to assess wind energy potential. The most significant normal wind speed is around 5.3 ms−1in April length growth, and this is the lowest in Bangladesh, which is around 2.6 ms−1in December. The technical capacity of wind energy is rated at 4614 MW [14]. 2.2.3. Biomass In Bangladesh can control fertilizers used for biomass-controlled electricity generation, plant accumulation, dropping poultry, water hyacinth, and rice husk and so on. The annual rate of biomass that can be recovered in Bangladesh is around 1.26 million tons per year. There are around 50% of rice husk is used for energy applications, such as steam generators for local cooking and fertilizing rice. Thus, 50% of rice husk can be used for electricity generation. Only 57% of poultry manure is practical for small generations of controls. The technical potential of biomass energy is estimated at 566 MW [15]. 2.2.4. Hydro-power The landscape of the country is flat that required to limit exploitation of hydropower further due to the potential for substantial social and ecological impacts. The available limit for hydropower is 745 megawatts, of which around 200 megawatts are only slightly smaller than the typical estimated hydropower plant. The absolute installation limit for hydroelectric power plants in 2010 was 230 MW [16]. The expansion of 100 MW from the Karnafuli Hydroelectric Power plant will be included in 2016. 484 A.H. Bagdadee and L. Zhang / Energy Reports 6 (2020) 480–490 3. Methodology Different attributes and specific situations in the energy sector of all countries can cause a big difference in the expansion arrangement process. In this paper, concentrate on improving rational and sustainable power resources, and considering the problem of extension of indigenous generations by considering various important economic, ecological, social, political and security supply criteria. The Extended Energy Generation event used in this study is a situation-based energy status indicator made by the Stockholm Condition Foundation. The basic idea of expansion energy generation is a user-driven context based inspection. This situation includes various ways energy is given, changed, and created in a particular place or economy, under the scope of selective assumptions about society, economic progress, technology, and so on. The impact of environmental pollution factors is caused by each stage of fossil fuel processes such as the power plant, including electricity generation and costs of greenhouse gas emissions, distribution, and end-client training procedure. This stage proposes a multi-objective integer programming model to erase expansion plans and to determine the limits of the chosen innovation. 3.1. Objective function The proposed model combines two objective capabilities: intensification the trend of the proposed generation expansion plan and reducing current estimates of total costs. This model takes into relation various orders, such as power quality, meeting demand, stability, and upper and lower limit of selection factors. The representation of sets, parameters, and elements selected in numerical models such as: A. The proposed methodology, relationships between Eqs. (1) and (2), taking into description the gradient loads obtained from various techniques (Mj) from the main stage, are characterized to maximize the gradient of the expansion plan. As well, this objective potential is the whole of the proposed plan to determine the best combination of power generation techniques that exploit the general needs of each option determined by generation extension performances model Eq. (2). max Y1= S ∑ s=1 j ∑ j=1 MjNt j(1) Nt j=Zt jQj+Nt−1 j(2) B. The objective purpose of this model in Eq. (3) is to balance the power supply and demand activities and minimize the economic costs of all frameworks in the horizon setting including speculative costs, operation, and maintenance of costs, fuel costs, environmental costs. The existing calculation process is as follows Eqs. (3)–(7). Tcos t=(Tinv+Tmc +Tf c +Tevc) (3) Absolute investment Costs: The constant progress of power generation expansion innovations, the parameter η Eq. (4) is presented with conditions, which is the rate of progress of speculation. Tinv= 2030 ∑ 2016 8 ∑ i=1 Inv2015 ×(1 +ηi)(t−2015) × K/1+K (1 −(1 −K))t×(1 +K)−(t−2015) (4) Maintenance & operation costs to consider the complexity and various parts of maintenance costs, the parameter µ, that is, the level of progress of maintenance costs is shown in condition (5). Tmc = 2030 ∑ 2016 8 ∑ i=1 (O&M)2015 ×(1 +µi)(t−2015) ×Pg ×(1 +K)−(t−2015) (5) To calculate absolute fuel cost, the parameter ωis also presented in condition (6). The rate of progress in fuel costs Tmc = 2030 ∑ 2016 8 ∑ i=1 Fuel2015 ×(1 +ϖi)(t−2015) ×Pg ×(1 +K)−(t−2015) (6) A.H. Bagdadee and L. Zhang / Energy Reports 6 (2020) 480–490 485 Absolute environmental costs include two segments. The first part is the environmental costs of conventional plants (coal plants and combustible gas plants) and renewable energy-based power plants, and the last part is the environmental costs of nuclear power plants. Tenv= 2030 ∑ 2016 8 ∑ i=1 (co2(Emission))2015 ×(1 +σi)(t−2015) ×Pg ×(1 +K)−(t−2015) (7) 3.2. Model constraints Power and Energy balance power demand and Power Supply. In this paper, the power unit is TW-hour power includes a variety of constraints such as constant quality requirements. The most extreme and smallest recommend of renewable energy assets, and the upper and lower limits of all innovations are considered in the accompanying relationship. Following are the model requirements. In most cases, the retention limit can be resolved as a deterministic or probabilistic grant that electricity supply planning needs to meet the increasing power demand in the region; this study presents four explicit sub-instructions as shown in conditions (8)–(11). The parameter α of Eq. (10) is expressing the proportionality factor between the power obtained and the absolute power demand, which is evaluated from the power information. The parameter βof Eq. (11) is the power proportionality coefficient purchased an absolute peak load demand. In line with this, total limits can be accessed from all periods to protect the framework without affecting the quality and to ensure that the recognition limits are sufficiently accessible to meet the symbol of regular demands. Between the upper and lower bounds are visible as estimates 8 ∑ i=1 Eg+Ec≥ED(8) Eg≤6000 ×Tc×Pf(9) α×ED≥EC(10) β×PE D ≤EP(11) Energy security is commonly explained as “access to sufficient and consistent energy to meet demand”. Relying on technology that is isolated is significant supervision. As a result, restrictions on access do not exceed the upper limit patent for various technologies in all periods. This is confirmed by considering the distinct idea of renewable energy generation technology, the parameter “γ” symbolize of activity factors protected from the energy framework used in a condition (12). The Kparameter of conditional expression (13) is the load end coefficient, which is used to meet the load peak demand. γ× 8 ∑ i=1 Eg ≥ 6 ∑ i=5 Eg (12) 8 ∑ i=1 IC+EP≥(1 +K)×EL(13) Positive response decision variable, EG≥0,EC≥0,EP≥0 (14) 3.3. Optimizing the generation expansion by NSGA-II This is used in the NSGA-II algorithm to determine the proposed multi-purpose model and to determine the selection factor. This is a transformational calculation, prepared to find the principle set of placements on the surface of the Pareto model. It was developed as an able calculator to overcome the problem of multi-objective progress. In the NSGA-II algorithm analysis, the cost and location variables of all people in the population at new points such as large genetic calculations, four properties including positioning, instruction sets, extraordinary verify, the mass distance must be determined, and population estimates deployed must be discarded in a non-dominant placement approach. At all points, people who are not ordered by different people are in front of 1 Pareto. Various people 486 A.H. Bagdadee and L. Zhang / Energy Reports 6 (2020) 480–490 are dominated by people from the front one from the front two. The highest crowd distance has higher strength as with traditional genetic algorithm; hybrid managers and changes are used for NSGA-II calculations. NSGAII algorithms are elsewhere as with other met heuristic calculations, the sequel from the NSGA-II calculation is relatively sensitive against its parameter estimates. Therefore, the parameters must be comfortable. Here, the best property for calculation parameters is given in Table 3. After adjusting the NSGA parameters; the problem of generation expansion became clear. Recognition of the Pareto Front assessment of context investigation issues is illustrated in Fig. 3. Table 3. Strictures of NSGA-II algorithm. NSGA-II Parameter values populace 220 integer of iteration 800 intersect probability 0.50 Transformation probability 0.45 Fig. 3. The approximation of the case study problem. 4. Result and discussions All placements in the front of Pareto are compared to special situations for improvement, but there is no optimal placement. In this paper use the maximum and minimum utility methods to overcome the selection of the last settings in the settings. In this way, the selected settings are resolved, and the NSGA-II algorithm optimizes other objective capabilities (15) that occur concerning that. In connection (16),Yjis the utility of the objective capacitance Ri.Yi is equivalent to one when objective abilities have optimal respect. From connection (17) strengthens the primary utility of the objective element from the selected settings. Max =δ(15) δ=min(Y1,Y2) (16) Y1=1−(Rmax 1−R1 Rmax 1−Rmin 1)(17) Y2=(Rmax 2−R2 Rmax 2−Rmin 2)(18) Specified the previous explanation, different estimates of the solutions selected for objective capabilities are in Table 4. Areas, related costs, and requirements for the solutions are in Fig. 4. The total cost is on the x-axis, and the slope predilection of the plan is on the y-axis. However, that made planning as the optimal Pareto settings. Table 4. The Properties of the objective operation. Objective function RiRmax Rmin Yi Predilection 463470 520262.550 262523.943 0.7035 Absolute cost 5.56×1012 9.9×1012 3.86×1012 0.7025 A.H. Bagdadee and L. Zhang / Energy Reports 6 (2020) 480–490 487 Fig. 4. The Solution of the Pareto front. The installed capacity for the various types of power generation technology and the scope of the generation expansion planning horizon shows in Figs. 5 and 6. The overall install capacity of the power plant technology mentioned above will reach 160 TWh by 2030, and an annual growth rate of around 30,000 — 6.37%. As far as the growth rate of Fig. 6 is concerned, renewable energy technology (wind power and solar power plants), in any case, will reach the increasing capacities of Fig. 7 by using natural gas and coal power plants is the terminal power plant. In Bangladesh have the capacity of full oil product installations. The nuclear power plant is responsible for 9.38% of all installed installations. Optimal power development to anticipate Bangladesh from 2016 to 2030 comes from long-term demonstrations of renewable energy, including an optimal combination of power plants. Fig. 5. Install capacity. Fig. 6. Percentage of the each install technology. As shown in Fig. 5, while the supply of renewable energy is increasing, the provision of fossil-based technology will decrease over time. Considering large-scale criteria in traditional generation expansions seems to be a rational explanation behind obtaining these results. The results can create a pattern for the nation to achieve a sustainable and environmentally friendly electricity supply. Also, the use of new and clean technology to be used