Modeling and optimization of energy systems for nepal

Abstract

Worldwide, nearly more than half a billion people will still not have a reliable and affordable electricity till 2040 and nearly 1.8 billion may compel to rely on traditional fuel sources for day to day activities. Specially the case is even more critical in remote areas of developing countries. Remote areas of undeveloped and developing countries suffer from limited or no access to electricity. In Nepalese context, varieties of renewable energy sources are available for energy access; limited to lighting and cooking. In line with sustainable development goal no. 7, “Ensure access to affordable, reliable, sustainable and modern energy for all”, Nepal has also set its own targets and indicators”. Thus, this study aims to assess the level of energy access in rural context and further analyze the viability of replacement by reliable and sustainable energy sources. Providing electricity access in remote areas is one of the foremost challenges of any developing country. Alternative Energy Promotion Center (AEPC), a government institution under the Ministry of Energy, Water Resources and Irrigation (MoEWRI), is promoting renewable energy technologies in Nepal since 1996. AEPC looks after all the available renewable energy (RE) technology widely being implemented in Nepalese context like, solar energy technology, wind energy technology, biomass energy technology, biogas technology, biofuel technology, and mini/micro hydro technology. Availability of the mentioned technologies varies with different topography of Nepal. To full-fill the energy demand, which is the basis of development of Nepal, optimization and hybridization of such energy technologies is must. To address these energy problems, research on modeling and optimization of rural energy system is proposed for the overall development of developing countries like Nepal. Thus, the study aims to model and optimize the existing energy systems; solar energy and mini/micro hydro technologies backed up with battery and diesel generator (DG). The study has assessed the energy potential and existing energy supply for the community through the mentioned renewable energy technologies. The study has also analyzed the potentiality of replacement of the less reliable energy systems by the most reliable electricity source i.e., hydropower (grid extension).

The purpose of this study is to develop and propose a reliable and low-cost model for electrification. Thus, the research has modeled and assessed the feasibility of replacement of short-term energy sources/systems by long term sustainable energy sources and the overall impact of policy injections. The study is focused on energy trend of Nepal, energy planning methodologies, analysis of prevailing energy modeling and optimization techniques in context of developing and under developed countries.

The research gap is traced for the energy planning through the literature review of published papers and government reports. The research is conducted analyzing both primary and secondary data. Field level data collection of 17 village development committees (VDCs) of Gorkha district (research site) is carried out via questionnaire survey. Primary data is collected through various in-person meetings, focus group discussions, survey questionnaire and checklists. The electrification data is collected from Nepal Electricity Authority (NEA), District Development Committee (DDC), World Bank (WB) and community rural electrification entities (CREEs). Further, secondary data is collected from Alternative Energy Promotion Center (AEPC), Renewable Energy for Rural Livelihood (RERL), Central Bureau of Statistics (CBS) etc. Based on the available primary and secondary data the analysis is conducted in three methods; analytical method, techno-economic optimization by HOMER 2.68, and regression analysis. More than fifteen thousand (15,775) households, 24 educational institutions, 24 offices or health posts, and 24 industries exist in the research area with an average of electrical load growth of 10 % in first year and 5 % in the subsequent five years. Electricity load demand for the next five years calculated for 17 VDCs is 965 kW and is considered 1MW for the further analysis and calculation purposes. For the detail analysis, valid analytical method and Homer Pro 2.68 software is considered. The research has further analyzed the impact of Gross Domestic Product (GDP) on Electricity per Capita (EPC) through a regression analysis of an econometric model. Impact of policy injections is qualitatively assessed by analyzing the electricity generation, import, peak demand and the trend. Opting for an analytical method for modeling and analysis of electrification options based on life cycle cost (LCC) and economic distance limit (EDL), each energy system for varied load conditions is compared for a better option. The study presents an optimized choice between decentralized renewable energy systems and grid expansion.

A framework for energy system selection based on available resources is proposed. It compares the grid expansion option with potential isolated renewable energy systems to ensure energy access to the area under consideration. Additionally, off-grid configurations that rely on renewable energy sources are also considered for the necessity of backup supply to ensure continuous power to the research area. Techno- economic assessment of different off-grid and hybrid configurations proposed in this study and their feasibility checks are carefully examined. Commercial efficacy of the proposed hybrid energy systems by comparing the life cycle and energy cost and by performing different additional sensitivity is conducted. The major results show that grid expansion is feasible only for high load requirements. Off-grid technologies in hybrid mode are more feasible for low load requirements; depending on the availability of energy resources as well. The study shows that the energy cost for low load conditions is high and is low for high load conditions. This way the best alternative electrification option can be adopted. The study shows that; the reduced generation cost will support increasing the electrification penetration. The results from analytical study show that, EDL increases linearly with the increase in load and supply hours. Increased backup hours from battery or DG will ultimately increase the EDL which shows the dependency on DG is very expensive for electrification compared with other technologies. Further, EDL regularly increases on increasing the load and needed supply hours. LCC for grid expansion for 5 kW of the load was NRs 50.84 / kWh, whereas LCC for PV + DG for the same condition was NRs 11.41 / kWh. LCC for low load conditions is high, which is quite higher for grid expansion. The result shows that LCC decreases with the increased load to a certain level and stabilizes thereafter. LCC for electrification options appeared to increase in the order of PV+ DG, Grid expansion, MHP, PV (inc battery), MHP+DG, and DG. Further fluctuation of PV system cost shows that LCC varies between 12.6 to 16.2 Rs/kWh. The analysis of cost of generation, capital cost, discount rate and the losses in grid extension is found less sensitive compared with other energy systems. The analysis shows that, annual discount rate generated has positive impact on LCC and reduced the cost 14.1 to 13.0 Rs/kWh.

The techno-economic optimization result shows the highest penetration of hydropower is the most economic. The regression analysis shows a positive and significant relationship between GDP per capita and electricity per capita. This reveals that one- dollar increase in GDP increases 0.27 kWh consumption of electricity. The modeling indicates that higher the GDP per capita, higher would be the consumption of electricity. The study concludes that reduced generation cost supports increasing electrification penetration. Life cycle cost for grid expansion is the most economical in high load conditions whereas for the isolated and sparsely settled populations with low load conditions, photovoltaic (PV) backed up with diesel generator (DG) is the most economic among the energy systems under this study. Energy planning models (EPMs), approaches and optimization techniques play an important role in energy sectoral policy formulation. Above all, the research has traced a bi-linear polynomial equation with available data points of EDL, supply hours, and the demand load. The equation can further be utilized to identify the necessary EDL based on required supply hours and the load demand. Similarly, additional four bi-linear polynomial equation is fitted for the energy systems considered under the research. Thus proposed methodology for the development of such equations can be further replicated for other energy systems for research. The proposed bi-linear polynomial equations and the developed methodology to generate the equation can be utilized for long term energy planning. The long term energy planning through energy modeling and optimization techniques of energy technologies have a better impact to mitigate the issues of energy access. Energy demand forecasting and the subsequent planning is one of the most important aspect when dealing with long-term energy planning. For the technical researchers who want to continue similar research and energy planning, I would like to recommend extending the research scope to all the potential energy systems; not limiting to the energy systems and resources available in the research area. Further, the research site extended to the district level or national level will give more prominent, comparable and replicable results. Further, the policy makers, who plays a vital role in planning and policy making, I would recommend that the policies should be formulated in such a way that it promotes the electricity

generation to the optimum level. During energy planning, it is recommended that, even energy planning at local level, both analytical comparison of each energy technology in line with LCC and EDL should be mandatory. Further, adoption of the techno- economic optimization via various simulations of the potential energy systems for energy planning is essential.