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|Title: ||Distributed Bioenergy Systems For Expanding Rural Electricity Access In Tumkur District, India : A Feasibility Assessment Using GIS, Heuristics And Simulation Models|
|Authors: ||Deepak, P|
|Advisors: ||Ravindranath, N H|
|Keywords: ||Electricity - India|
Biomass Energy Systems
Rural Energy Planning
Rural Electrification - India
Rural Biomass Power Systems
Hybrid Renewable Energy Systems
Biomass Power Generation
Decentralized Energy Planning
|Submitted Date: ||2011|
|Series/Report no.: ||G24922|
|Abstract: ||Energy is an important input for various activities that provide impetus to economic,
human and social development of any country. Among all the energy carriers, electricity is the most important and sought after energy carrier for its quality, versatility and ability to perform various technology driven end-use activities. Therefore access to electricity is considered as the single most important indicator determining the energy poverty levels prevailing in a country. Demand for electricity has increased significantly, especially in the developing countries, in recent years due
to growth in population and intensification of economic activities. Therefore, providing quality and reliable electricity supply at low-cost has become one of the most pressing challenges facing the developing world.
Although sufficient efforts have gone into addressing this issue, little progress has
been made in finding a satisfactory solution in alleviating this problem. Currently,
electricity supply is mostly dependent on centralized large-scale power generation.
These centralized systems are strongly supply focused, fossil-fuel intensive, capital intensive, and rely on large-distance transmission and distribution systems. This results in electricity cost becoming unaffordable to the majority poor which comprises more than 70% of the total population in developing countries like India and the benefits of quality energy remaining with the rich, giving rise to inequitable distribution of energy. Continuous exploitation of fossil fuels has also contributed to local and global pollution. Therefore it is necessary to explore alternate means of providing energy access such that the energy carriers are clean, easy to use, environmentally benign and affordable to the majority of the rural poor. India is at a critical juncture of passing through the path of development. India is also in a unique position that its vast majority of rural population is energy poor which is disconnected from the electricity grid. In this context, the proposed research is an attempt towards developing a greater understanding on the issue of rural energy access and providing a possible solution for addressing this gap. This has been proposed to be achieved by adopting a decentralized energy planning approach and distributed energy systems mostly based on renewable energy sources. This is expected to reduce dependence on imported energy, promote self-reliance, provide economically viable energy services for rural applications and be environmentally
safe. The focus is limited to biomass energy route which has many advantages; it is a
geographically equitably distributed resource, geographical advantage of having
potential to setup energy systems at any location where vegetation is present and not
seasonal like other renewable energy technologies. A mathematical model-based
approach is developed to assess the feasibility of such a proposal. Models are
developed for performing biomass resource assessment, estimating end-use-wise
hourly demand for electricity, performing capacity and location planning and
assessing economic feasibility. This methodological framework was validated through a case study developed for the district of Tumkur in the state of Karnataka (a state in southern region of India).
The literature survey was conducted exhaustively covering the whole span of supplyside and demand-side management of electricity systems, and grid-connected and
stand-alone power generation systems, their technical, economic and environmental
feasibilities. Literature pertinent to GIS applications in biomass assessment, facility
location planning and scheduling models were also reviewed to discern how optimal
capacity, location and economic dispatch strategy was formulated. Through the
literature survey it was understood that there were very few attempts to integrate both demand-side management and supply-side management aspects in the rural energy
context. GIS based mathematical models were sparsely used in rural energy planning
and decision making. The current research is an attempt to bridge these gaps. The
focus in this study is on effectively utilizing the locally available biomass resource.
Assessment of Biomass Potential for Power Generation
As a first step, the supply option was studied at village level by overlaying LULC
(land use land cover) and village boundary GIS maps of Tumkur district. The result
was fortified by the NDVI results from remote sensing images of land use pattern in
Tumkur district. A detailed village-level assessment of wasteland potential was made
for the entire district. The result showed which shows that in Tumkur district, roughly
17.3% of total geographical land was under exploitable wasteland. Using secondary
data and literature, biomass potential indices were prepared for different wasteland
types to determine the total biomass potential for power generation. The results based on the GIS data the assessment shows that Tumkur has roughly 17.3% of exploitable
wasteland. A complete village-level annual power generation potential was assessed
considering both energy plantations from wasteland, existing degraded forests and
Assessment of end-use-wise hourly Demand for Electricity at Village Level
Household survey was conducted for 170 sample households randomly chosen from
15 villages, again randomly selected to represent different socio-economic categories. Using statistical tools like k-means clustering, one-way ANOVA and Tukey’s HSD test, first the households were classified into three economic categories to study the distribution of the households in each sample village. Later based on the number of households of each type in a village, the villages were further classified into five groups based on their socio-economic status. This was done to select the right representative per-household power demand for a village of any particular socioeconomic category. The representative per household power demand in each economic category along with secondary data helped in deriving the electricity daily
load profiles for all the villages. Representative demand profiles were generated for different seasons across different sectors namely domestic, agriculture and industry sectors at the end-use level comprising of activities like home lighting, appliances, irrigation pump sets operation and small industry operations.
Mathematical Modeling for Optimal Siting of Biomass Energy Systems Since the power has to be generated through biomass route, biomass may have to be transported over a large geographical area which requires efficient design of logistic systems. Apart from that, a major component of cost of biomass power is the cost of transportation of biomass from source to the power plant. Therefore it is important to determine the optimal siting of biomass energy systems to minimize the cost of transportation. Since these optimal locations are based on minimizing Euclidian distance, installing the power generation systems at these locations would also minimize total cost of local transmission and distribution. In order to locate the biomass energy system, K-medoid clustering algorithm was used to determine the optimal number of clusters of villages to minimize the Euclidean distance between the medoid of the cluster and the villages within the cluster, and minimize the total installed capacity to meet the cluster demand. The clustering algorithm was modified in such a way that the total capital cost of the power generation system installation was minimized. Since the total project cost not only depended on capital cost alone, but also on biomass transportation and power transmission costs, these costs were also included in the analysis. It was proposed to locate the energy systems at the medoids of the clusters.
Optimal Capacity Planning
Installing biomass power systems requires large investments. It is therefore necessary
to reduce the peak demand to bring down the installed capacity required. This was
achieved by developing heuristics to arrive at an optimal scheduling scheme of the
end-use activities that would minimize the peak demand. The heuristics procedure
was demonstrated on five representative villages, each from different economic
category. The optimal demand profile was used as input in HOMER micro-energy
system simulation software to perform a techno-economic analysis. The simulation
facilitated a thorough economic feasibility study of the system. This included a
complete analysis of the cash inflows and outflows, capital cost of the system,
operation and maintenance cost, cost of fuel and estimation of total GHG emissions.
There are many limitations in planning at village-scale. The results indicated that
capacity planning done at the village level was prone to over-estimation of installed
capacity of the system increasing the investment requirement, under utilization of the capacity and suffered from supply scarcity of biomass. This emphasized the need for looking at a bigger conglomerate of villages in other words cluster of villages. In the next step, the optimal capacity planning was performed for one of the clusters formed using the K-medoid clustering algorithm with the power generation system located at the medoid. For demonstrating the practical feasibility of extending the methodology to cluster level, a cluster with maximum number of villages was chosen from the optimal cluster set in the k-medoid algorithm output. The planning was conducted according to the socioconomic category of the villages in the cluster.
Economic implications of Stand-alone (SA) vs Grid-connected (GC) Mode of Operation
Other important question that was answered in this analysis was a comparison of GC
systems with SA systems. Since extension of grid to a village that is not electrified
involved drawing high voltage transmission lines from the nearest grid point,
installation of distribution transformers and low transmission lines within the village
for distribution. Since these involve high costs it was necessary to study whether or
not it is feasible to extend the grid or install a stand-alone system. This question was answered by the breakeven distance for which grid extension becomes more economical than a SA system. For each village breakeven distance varied with the total installed capacity and the operational costs. This helped to compare the GC systems vis-à-vis SA systems from the point of view of economic feasibility.
It is necessary that planning and strategies be rational and reasonable for effectively
assuaging the rural electrification imbroglio. The current study has highlighted the importance of integrating both demand-side-management and supply-sidemanagement
of energy systems in the context of planning for power generation and distribution in rural areas. The key findings in the current study are:
• The study showed the feasibility of biomass power systems in meeting the
rural electricity needs.
• Biomass assessment results showed that, if the power demand could be
brought down by replacing the existing appliances with efficient ones (ex.
compact fluorescent lamps and improved irrigation pump set valves), Tumkur
district has enough biomass potential to meet both the current as well as
increased future demands for electricity.
• The optimal number of clusters minimizing total capital cost of biomass
energy systems, transportation cost of biomass and distribution cost of power,
was 96 for Tumkur district. For Kunigal block, the optimal number of clusters
was 37 and 32 for supply and demand scenarios 1(BAU -Business As Usual)
and 2 (with 10% increase in cropland and 20% increase in demand).
• The optimal capacity planning emphasized the importance of clustering of
villages for minimizing the total installed capacity. The result also showed
that the breakeven distance was the determining factor about the choice of GC
vs SA systems.
The main contributions of this thesis are:
i. Hourly demand pattern was studied to estimate the aggregate demand for electricity at village level for different sectors across various seasons.
ii. Village-wise biomass resources potential for power generation was assessed
iii. Optimal locations for siting biomass energy systems were identified using
k-medoid clustering algorithm
iv. An optimal scheduling of end-use activities was planned using heuristics
method to minimize the installed capacity
v. Optimal location, scheduling plan of end-use activities and optimal
capacity were determined for individual villages as well as village clusters
vi. The economic implications of grid extension vis-à-vis stand-alone mode
of operation of the installed biomass energy systems were studied
The generalized, multipronged approach presented in this thesis to effectively
integrate both demand-side management and supply-side management in rural energy
planning can be implemented for any rural region irrespective of the location. The
results emphasized that for efficient demand-side and supply-side management, it is
important to plan for clusters of villages than at the individual village level. The
results reported in this thesis will help the policy and strategy makers, and
governments to achieve rural electrification to a satisfactory extent to ensure
continuous, uninterrupted and reliable power supply by determining the clustering
strategy, optimal cluster size, optimal scale and siting of decentralized biomass power generation systems.|
|Abstract file URL: ||http://etd.ncsi.iisc.ernet.in/abstracts/2668/G24922-Abs.pdf|
|Appears in Collections:||Centre for Sustainable Technologies (formerly known as ASTRA) (astra)|
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