Data Collection & Analysis for Area-Based Energy Planning

A Case Study in Phrao District, Northern Thailand

Introduction

Many households, industries and other enterprises in developing countries depend on wood and other biomass as an energy source. Estimates of woodfuel consumption vary from 30 to 80% of the total energy consumption for most countries. It has been shown that for all RWEDP countries woodfuel consumption is still growing (WEN, 1996). Therefore it can be assumed that the dependence on woodfuels will not change in the near future. However, with an increasing population the need for agricultural land is also increasing, which may conflict with the need for wood. It is necessary to assess if these trends are sustainable and if not, what interventions are required. Therefore it is important to incorporate wood energy in the formulation and implementation of energy policies, plans and projects.

Policy formulation and planning requires the assessment and forecasting of the demand and supply of all forms of energy to identify (future) problems and to allow for the evaluation of intervention options. For this purpose data on several factors that have an impact on an energy system are needed. However, in most developing countries these data are hardly available to energy planners. Data that are used for energy planning are often based on information about sales of conventional fuels, supplied by their respective producers, and estimates of demand and supply of traditional fuels. Data that are required for wood energy planning may exist, but these usually have to come from different sources, hence differences in objectives, definitions and scale may complicate comparison and integration.

The production, distribution and consumption of biomass fuels occur usually at local level, on a small scale and often outside the monetary economy. Due to the local nature of energy, the rural energy system is site-specific. As the environment, the level of income, the type of settlement and the existence and accessibility of resources vary among areas, the supply of biomass fuels and energy consumption patterns also vary. Likewise, within an area, patterns of energy demand and supply can vary by sub-area, town or village, depending on cultural, social, geographic, agro-ecological and climatic conditions. Apart from the influence of energy on the environment (e.g. in the form of CO2 emissions), environmental factors can influence the energy system in a certain area. The distribution of conventional fuels to an area and among consumers within the area depends on the infrastructure. The availability of biomass fuels depends on geographic factors such as the location of consumption and resources, the infrastructure, slope, land use and land ownership. Existing resources may be inaccessible to certain types or groups of consumers, due to landownership, distance or land use.

The development of energy planning since the early seventies has shown the need for an integrated analysis of the demand and supply of all energy forms (including traditional) in relation to a country's economy and environment, considering inter-sectoral relations and social impacts of energy trends and policies (APDC, 1985). More recently it has become apparent that rural energy, due to its site-specific nature, requires a decentralised approach, i.e. demand and supply assessment, forecasting and plan formulation and implementation for a distinct area, defined either by administrative boundaries or by factors such as agro-ecology, economy, social or cultural characteristics (FAO, 1990).

Unfortunately, at present energy planning in most RWEDP countries occurs mainly at national level, with an emphasis on conventional fuels. Energy planning at the local level is usually not conducted because it is assumed that data are not available and decentralised (energy) institutions do not exist or they lack the capabilities and responsibilities to formulate and implement decentralised energy plans. Little if any practical experience of area-based energy planning has been documented. Therefore the possibilities and limitations of area-based energy planning with respect to data collection and analysis are hardly known.

Objectives of the Study

In order to gain insight into the problems related to the availability, collection and analysis of data for energy planning at area-based level, a case study was conducted in Phrao District, Northern Thailand that followed and documented the planning process from the identification of data requirements to the impact analysis of future trends and intervention options. Energy planning is hardly performed at this level as yet and it is desirable to perform planning at area-based level. Therefore the possibilities and limitations of coming up with an energy plan using available data and analysis tools were studied, considering the effort and skill required for data collection and analysis. The study only used secondary data that are available from government agencies such as ministries, provincial and local administration offices and other organisations involved.

The present case study aims to serve only as an example of the required data collection and analysis steps, in order to assist government agencies involved in rural energy planning, since hardly documentation of this kind is available at present. It may not be feasible to conduct studies like this for all districts in Thailand or comparable areas in other countries. The present case study aims to be an example of data collection and analysis using secondary data that are already available at present for planning at area-based level, in order to identify problems related with these data. It was aimed to identify the minimum amount of data required to assess the present and future energy situation at area-based level.

In short the objectives of the case study are:

1. to identify possibilities and limitations in the formulation of energy plans at area-based level, based on data collection and analysis using secondary data;

2. to identify possibilities and limitations of the use of existing secondary data from government agencies and other organisations, in particular the integration of various scattered data;

3. to identify what can be done with a minimal amount of data to assess the present and future energy situation at area-based level;

4. to evaluate the applicability of existing planning tools such as LEAP and GIS for (area-based) energy planning.

The method of the case study is to apply the different steps of energy planning in an iterative way, i.e. in several stages of data collection and analysis. The initial stage will lead to the identification of data gaps, which will be followed by a another stage of data collection and analysis, and so forth. During the subsequent stages problems related to the requirements, availability, collection and processing of secondary data for area-based energy planning will be identified. The case study covers the assessment of the current energy demand and supply situation, the development of several forecasting scenarios, supply-demand balancing, the identification of intervention options, and the assessment of impacts of future trends and interventions in economic and environmental terms. Uncertainty assessment will be included in supply-demand balancing, because decisions to intervene in the energy system generally will be based on the ratio of wood demand and supply.

It should be stressed that the methods followed in this case study are not the only possible ones. Other options may be feasible depending on the area, data, available tools, institutional set-up, etc. The case study only intends to provide an insight into area-based planning through practical experience, and therefore it cannot be complete. A better understanding of limitations and opportunities in area-based planning requires more case studies conducted for other areas, using other approaches.

The study area was selected because information was already available from reports of ITC students who have done research in the area. These reports cover energy related topics, such as residential and industrial energy consumption and land use evaluation. This information will generally not be available for other areas. The case study tried to use information available from institutions in Thailand as much as possible and the ITC reports were used to identify which site-specific information is required for area-based energy planning in addition to existing information.

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