3. The decision support system approach

1. Flexibility and adaptability to accommodate changes in the environment and the decision-making process of the user.
2. Assist managers in their decision processes in semi- structured tasks-problems for which formal models are useful, but where the planner's judgement is also essential.
3. Support and enhance, rather than replace, managerial judgement.
4. Attempt to combine the use of models of analytical techniques with traditional data access and retrieval functions.
5. Specifically focus on features which make them easy to use by non-computer people in an interactive mode.
6. Organise data and models around decision(s) and are user- initiated and controlled.
7. Present information in a flexible way to support the widely differing requirements and cognitive styles of users. To this end, it should be possible to present data in different contexts and formats, and allow the user to change these contexts.
8. DSS software uses a hierarchical design approach. Rather than attempting to build highly specific software for each study application, the DSS is often designed as a model generator. That is, the model itself is built rather than the model building tools.

From these characteristics, it can be seen that DSS's focus is on providing flexible tools for policy analysis and not on providing models to give answers to structured problems. Indeed, the modelling tools are only one component to DSS, which may be described as comprising three-component subsystems:

1. The database management subsystem: This manages an integrated database to drive all the models. Its purpose is to extract and combine information from a variety of sources, display the data structure to the user in a logical way, and handle personal and unofficial data, so that the user can experiment with alternatives based on personal judgement.
2. The model management subsystem: The DSS offers the user a number of modelling tools. The capabilities of this subsystem include: creating of new models, cataloguing and editing of existing models, interrelating of models by links through the database and integrating small model 'building blocks' into larger model systems
3. The dialogue management subsystem: Some guidelines for the design of this subsystem (the user-system interface) include;
• the use of a consistent and familiar interface (for example, spreadsheet or word processing programs) throughout the system,
• help functions which are on-line, extensive and context sensitive,
• natural language messages, both in normal operation and error conditions,
• data entry forms ready-filled with sensible default values (profiles or templates),
• data entry validation,
• housekeeping functions (data back-ups, copying, deleting files, etc.).

The dialogue style is the main determinant of the usability of the DSS. This design is guided by various methodological considerations, such as

1. Scenario approach: Simulates alternative energy and economic futures under a range of different assumptions, such as, replacement of traditional stoves with improved stoves, switching over from incandescent bulbs to compact fluorescent bulbs, improvement in agricultural pumpsets' efficiency, improvement in industrial machinery's effi¬ ciency, agroforestry, etc.
2. Integrated energy environment planning: While emphasis¬ ing a disaggregated approach, design also stresses the importance of integrating the analyses within a compre¬ hensive planning framework. Integration of all types of
   
   energy sources [23], sectorwise energy demands, inter-mediate conversions of fuels, primary resources, and environmental and economic impacts across separate geographical areas takes place [24].
3. End use, needs driven approach: Resource requirements and supply side projections are carried out based on energy services required in different economic sectors. This approach places development objectives, such as, the provision of end use goods and services at the foundation of energy analysis. It achieves the goal of integrated energy planning by allowing the development plans of different sectors to guide the evaluation of energy strategies [25].
4. Flexibility and user friendliness: Is designed as a set of modules and is flexible, expandable and comprehensive. These provide an expandable data structure which can be adapted to the diverse energy systems with different requirements and developmental views of planners (Figs. 1.1 and 1.2).

The regional energy planning program, designed based on these concepts, consists of mainly four blocks of programs: energy scenarios, computation models, aggregation and the energy database. This is illustrated in Fig. 1.1.

The energy scenario module addresses the main components of an integrated energy analysis, namely, sectorwise demand analysis, energy conversion and resource assessment. There are three programs for building scenarios (demand, transformation and resource) and one for comparing and evaluating scenario costs and impacts. The planner uses the scenario building programs to develop current energy balances, projections of supply and demand trends, and scenarios representing the effects of energy policies, plans and actions. The aggregation program assembles area level (taluk, district, region, state, nation) energy projections into multi area results. The detailed structure is given in Fig. 1.2 and the individual components of the model are discussed below.