Challenges and gaps for energy planning models in the developing-world context

Energy planning models (EPMs) support multi-criteria assessments of the impact of energy policies on the economy and environment. Most EPMs have originated in developed countries and are primarily aimed at reducing greenhouse gas emissions while enhancing energy security. In contrast, most, if not all, developing countries are predominantly concerned with increasing energy access. Here, we review thirty-four widely used EPMs to investigate their applicability to developing countries and find an absence of consideration of the objectives, challenges, and nuances of the developing context. Key deficiencies arise from the lack of deliberation of the low energy demand resulting from lack of access and availability of supply. Other inadequacies include the lack of consideration of socio-economic nuances such as the prevalence of corruption and resulting cost inflation, the methods for adequately addressing the shortcomings in data quality, availability and adequacy, and the effects of climate change. We argue for further research on characterisation and modelling of suppressed demand, climate change impacts, and socio-political feedback in developing countries, and the development of contextual EPMs

Corruption significantly increases the capital cost of power plants in developing contexts

Emerging economies with rapidly growing population and energy demand, own some of the most expensive power plants in the world. We hypothesized that corruption has a relationship with the capital cost of power plants in developing countries such as Bangladesh. For this study, we analyzed the capital cost of 61 operational and planned power plants in Bangladesh. Initial comparison study revealed that the mean capital cost of a power plant in Bangladesh is twice than that of the global average. Then, the statistical analysis revealed a significant correlation between corruption and the cost of power plants, indicating that higher corruption leads to greater capital cost. The high up-front cost can be a significant burden on the economy, at present and in the future, as most are financed through international loans with extended repayment terms. There is, therefore, an urgent need for the review of the procurement and due diligence process of establishing power plants, and for the implementation of a more transparent system to mitigate adverse effects of corruption on megaprojects

Maximizing daylight use potential in retail shopping environments in the context of Dhaka, Bangladesh

In the recent times with the increase in the population, the number of retail shopping environments has increased significantly in Dhaka city. But these shopping environments are developing into high consumption areas of electricity resulting from artificially light design approach. In this study, it was found that the energy consumption is rising because of the minimal or no use of daylight and natural ventilation. A field based case study was conducted to review the daylight inclusion in the design of retail shopping environments representing the historical periods of 1950-70, 1971-80, 1981-90, 1991-2000, 2001-2011. In this research in addition to field work, parametric study was done to identify the effect of design factors/parameters relating to daylight. The main focus was to develop a causal relation between the parameters of the shopping environments to maximize the use of daylight. The parameters which were considered in this study were- width, height and depth of the shops; the depth of the corridor between two rows of shops; the height and width of the light wells. All the parametric relations were derived to the width of the shop. Daylight level were measured and compared with the given level in the Bangladesh National Building Code (BNBC) code. It was found that shopping environments play an important role in energy consumption in urban areas and little or no utilization of daylight contribute to this energy demand. This is of particular significance in an environment where dwindling fossil sources of energy and an increasing energy demand created by positive economic growth pose a challenge for the building industry stake holders

Decarbonization cost of Bangladesh's energy sector: Influence of corruption

As a rapidly developing lower-middle income country, Bangladesh has been maintaining a steady growth of +5% in the gross domestic product (GDP) annually since 2004, eventually reaching 7.1% in 2016. The country is targeting to become uppermiddle- income and developed by 2021 and 2041 respectively, which translates to an annual GDP growth rate of 7.58% during this period. The bulk of this growth is expected to come from the manufacturing sector, the significant shift towards which started at the turn of this century. Energy intensity of manufacturing-based growth is higher, the evidence of which can be seen in the 3.17 times increase in national energy consumption between 2001 and 2014. Also, Bangladesh aims to achieve 100% electrification rate by 2021 against an annual population growth rate of 1.08%. With the increasing per capita income, there is now a growing middle class fuelling the growth in demand for convenient forms of energy. Considering the above drivers, the Bangladesh 2050 Pathways Model suggested 35 times higher energy demand than that of 2010 by 2050. The government and private sector have started a substantial amount of investments in the energy sector to meet the signi ficant future demand. Approximately US$104 billion would be invested in the power sector of Bangladesh for establishing 33 GW installed capacity by 2030, the majority of which would be financed by national and international loans. However, Bangladesh is one of the most corrupted country in the world which may influence the energy planning development. The current policies of Bangladesh power sector paved the future direction towards predominantly coal-based energy mix which would augment the greenhouse gas (GHG) emissions five times (117.5 MtCO2e) in 2030 than that of 2010. By increasing GHG emissions, the country would undermine the worldwide effort of keeping global temperature rise in 21st century below 2°C, as per the Paris agreement and COP21. V The objective of this research was to develop a framework to explore the cost of decarbonizing the Bangladesh's energy sector by 2050. For the study, six emissions scenarios business as usual (BAU), current policy (CPS), high-carbon (HCS), medium-carbon (MCS), low-carbon (LCS) and zero-carbon scenarios (ZCS), and three economic conditions high, average and low costwere considered. The combination of emissions and economic scenarios rendered 18 different emissionseconomic scenarios for the research. The results showed that Bangladesh would emit 343 MtCO2e by 2050 without any emissions reduction strategies under HCS. However, Bangladesh can reduce 23 of HCS by adopting decarbonization strategies such as energy mix change towards renewable and nuclear. On the optimistic side, the emissions can be reduced 73 by 2050 under ZCS than that of HCS. The study demonstrated that a zero carbon future is not yet feasible for Bangladesh by 2050 because the operational fossil fuel based plants would be operational. Therefore, the GHG emissions are going to rise even if Bangladesh adopts renewables and nuclear dominating energy mix. However, it will be possible to keep the GHG emissions approximately 2 tCO2e/capita threshold if the country adopts LCS. On the other hand, only MCS and LCS can meet the projected energy demand by 2050. The energy sector can meet the projected demand under ZCS only if the electricity consumption is reduced 26 2050. In terms total cost, the MCS was found to be 3.9 LCS by 2050. LCS would have a higher cost than that of MCS up to 2030, due to the high capital cost of renewable technologies. The total cost under LCS would start to be lower than of MCS after 2035 for the fossil fuel cost. Accumulated fuel cost would reach$250 billion in 2050 under HCS, which can be reduced 23% under ZCS. The cost of decarbonization would be 3.6, 3.4 and 3.2 times under average cost of MCS, LCS, and ZCS, than that of HCS. As the energy sector of Bangladesh is under rapid development, the accumulated capital would be comparatively high by 2050. However, fuel cost can be significantly reduced under LCS and ZCS which would also ensure lower emissions. The study suggested that energy mix change, technological maturity, corruption and demand reduction can influence the cost of decarbonization. However, the most significant influencer for the decarbonization of Bangladeshi energy sector would be the corruption. Results showed that if Bangladesh can minimize the effect of corruption on the energy sector, it can reduce the cost of decarbonization 45-77% by 2050 under MCS, LCS, and ZCS

Why is Bangladesh’s electricity generation heading towards a GHG emissions-intensive future?

Bangladesh—recently graduated to developing nation category from a least developed country with an emerging economy also is one of the severely affected countries by climate change—is heading towards a coal-intensive electricity generation mix contrary to global decarbonisation efforts. It is facing formidable challenges in achieving universal access to affordable, reliable, and sustainable electricity, decarbonising the energy mix by 2030 to achieve the objective of Sustainable Development Goal (SDG) 7, despite a 285% increase of installed capacity between 2008–09 and 2020–21 and aiming at achieving 40 GW and 60 GW by 2030 and 2041 with planned expansions, respectively. This study reviewed Bangladesh’s electricity sector developments—demand, generation, transmission, and distribution (T&D)—to identify progress in policies, drivers, and challenges behind the Greenhouse gas (GHG) emissions-intensive future direction. The rapid population and economic growth and shift towards industry-based economy drove the exponential growth in energy demand, eventually influencing the rapid generation capacity and T&D infrastructure development. However, Bangladesh has targeted transitioning from natural gas to coal dominating fuel mix due to the lower renewable potential, energy, and food security challenges, because of the anticipated substantial future electricity demand for becoming an Upper Middle and a High-income country by 2031 and 2041, respectively. We also recommended nuclear energy, (renewable) electricity import and floating solar plants to decarbonise the current trajectory

Forecasting methods in energy planning models

Energy planning models (EPMs) play an indispensable role in policy formulation and energy sector development. The forecasting of energy demand and supply is at the heart of an EPM. Different forecasting methods, from statistical to machine learning have been applied in the past. The selection of a forecasting method is mostly based on data availability and the objectives of the tool and planning exercise. We present a systematic and critical review of forecasting methods used in 483 EPMs. The methods were analyzed for forecasting accuracy; applicability for temporal and spatial predictions; and relevance to planning and policy objectives. Fifty different forecasting methods have been identified. Artificial neural network (ANN) is the most widely used method, which is applied in 40% of the reviewed EPMs. The other popular methods, in descending order, are: support vector machine (SVM), autoregressive integrated moving average (ARIMA), fuzzy logic (FL), linear regression (LR), genetic algorithm (GA), particle swarm optimization (PSO), grey prediction (GM) and autoregressive moving average (ARMA). In terms of accuracy, computational intelligence (CI) methods demonstrate better performance than that of the statistical ones, in particular for parameters with greater variability in the source data. However, hybrid methods yield better accuracy than that of the stand-alone ones. Statistical methods are useful for only short and medium range, while CI methods are preferable for all temporal forecasting ranges (short, medium and long). Based on objective, most EPMs focused on energy demand and load forecasting. In terms geographical coverage, the highest number of EPMs were developed on China. However, collectively, more models were established for the developed countries than the developing ones. Findings would benefit researchers and professionals in gaining an appreciation of the forecasting methods, and enable them to select appropriate method(s) to meet their needs

Modelling and Forecasting Energy Demand in Rural Households of Bangladesh

Bangladesh, the eighth largest populous country in the world, has a significant rural population (70%), which is contributing to the energy demand of the country. The major portion in energy demand of rural households is biomass energy. With the improvement in GDP the rural energy demand would switch to more electricity intensive demand pathway. This paper focuses on a bottom up approach towards modelling the aggregated energy demand of rural households of Bangladesh form the year 2010 to 2050. The combination of four level scenarios of four variables (population, GDP electrification index, public energy conservation index) would forecast lowest, highest and optimum energy demand pathways for rural households of Bangladesh. The study not only considers the electricity demand of the rural household, but also it would render the opportunity to concentrate at the detail user end energy demands (e.g. liquid fuel, biomass etc.)

Understanding Residential Occupant Cooling Behaviour through Electricity Consumption in Warm-Humid Climate

According to the India Energy Security Scenario 2047, the number of residential air conditioner (A/C) units may increase seven-fold by 2037 as compared to 2017. Also, the related energy consumption might increase four times in the next two decades, according to India’s National Cooling Action Plan. Therefore, the study of occupant cooling behaviour is essential to reduce and manage the significant electricity demand, helping to formulate and implement climate-specific cooling policies, and to adopt low-energy and low-cost technologies at mass-market scale. The study aims to analyse residential electricity consumption in order to investigate occupant behaviour, especially for thermal comfort by using space cooling and mechanical ventilation technologies. Among the five climate zones in India, this study focuses on the occupant behaviour in a warm-humid climate using Auroville as a case study, where climate analysis of the past 30 years demonstrated progression towards unprecedented warmer weather in the last five years. In this study, electricity consumption data from 18 households (flats) were monitored for seven months (November 2018–June 2019). The study also elaborated the limitations faced while monitoring and proposed a data filling methodology to create a complete daily profile for analysing occupant behaviour through electricity consumption. The results of the data-driven approach demonstrated the characteristics and complexities in occupant behaviour and insight on the operation of different technologies to attain thermal comfort in residential buildings in an increasingly warming climate

A CONTROLLED RELEASE MICROSPHERE FORMULATION OF AN ANTI-DIABETIC DRUG AND CHARACTERIZATION OF THE MICROSPHERE

Objective: Here the objective of this study was to prepare and characterize sustained release metformin loaded microsphere formulation which was prepared by W1/O/W2 emulsion solvent evaporation technique.Methods: Guar gum and sodium alginate were used as a matrix building material, whereas ethyl cellulose was applied as a coating polymer. Here various formulations were prepared by changing the drug and guar gum ratio, and the subsequent drug entrapment efficiency (DEE) and drug release were compared and evaluated.Results: Scanning Electron Microscopy (SEM) studies revealed spherical particles with a smooth appearance. Fourier-transform infrared spectroscopy (FTIR) showed there was no interaction between the ingredients in the final formulation. X-ray Diffraction (XRD) studies showed the emergence of polymorphic forms in the final formulation. The drug entrapment in the final drug loaded microsphere formulations was varied from 30-66.78%. The drug release studies showed the continuous release of the drug through twelve hours. The optimized formulation (f2) found to release 71.5% of drugs at the end of the 12th hour following zero order release kinetics.Conclusion: The increase in gum concentration in the W1 phase, which enhances viscosity in the W1 phase, resulting in an increase in the drug entrapment up to an optimum level and a decrease in the release rate. So, it can prolong the action. So by using this tool, we can say that metformin loaded microsphere formulation would be a suitable pharmaceutical formulation for the treatment of diabetic patients in modern drug therapy for its prolonged action. Â