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Energy demand in rural areas is generally met by local energy resources. These areas are normally overlooked in the energy-planning process due mainly to the lack of data and proper analytical tools. In this paper, we apply a suitable multiobjective programming method for rural energy analysis. Multiobjective programming methods provide decision makers with an opportunity to negotiate and explore different energy options. As an illustration of the proposed method, we have analysed the energy situation of a rural area and examined the tradeoff between energy supply, investment for energy programs, and employment generation.

In Ontario, potential contributions of solar domestic hot-water (SDHW) heating to air-emission mitigation have been identified. The provincial utility Ontario Hydro does not include solar heating in its current demand-side management plans because of the capital cost barrier. We present results of life-cycle cost analyses for installing a typical solar system in single-family dwellings in Toronto. For high hot-water load, the generated societal benefits make solar domestic hot-water heating an economically viable option.

The residential sector accounts for most of energy-consumption in developing countries in the form of traditional energy. The use of commercial energy is nominal and confined mostly to urban areas where fuelwood is already monetized. A model, based on an end-use/process analysis approach, is developed on a spreadsheet, which is capable of simulating scenarios to address issues of increasing traditional energy-demand caused by population growth, sustainable supply capacity of the existing energy resources, potential for development of new and renewable energy resources, technology. This paper is divided into two parts: general energy issues and the modelling approach, and the application of this approach to Nepal in the context of fuelwood-supply sustainability.

The energy-use cost options for a service (cooking) with seven fuels and their different end-use devices under prevalent market conditions are examined with a model developed in Lotus version 3.1. This model has been used for a policy analysis of cooking-energy use in Nepal. The results, which are applicable to most of the developing and least-developed countries, indicate that readjustment of market price and improvement of end-use device efficiency could attract consumers for interfuel and intermode substitution, and renewable energy resources would then become a viable solution for meeting the cooking energy demand.

In Part I, we presented a pair of complementary variables and a set of component models that led to the development of a simulation model for industrial energy systems. Here, we present optimization and synthesis models based on the same variables and component models. The objective function in both cases is the minimum rate of exergy loss. Examples are given.

The energy systems in modern industrial plants are complex and of large scale. Engineers are increasingly turning to computer models for assistance in solving the sophisticated technical problems associated with these systems. The models developed to date have covered single energy sub-systems, such as the steam or electricity system. There is a need for plant-level overview models which can assist in the co-ordination of the energy sub-systems. An overview-level simulation model is presented in this paper. Systems theory and exergy are used extensively in this research. Exergy is used in the creation of a set of variables which can represent all energy forms, allowing combination of the sub-systems into a single unified model. Systems theory is used in the development of component models and formulations. The advantages of the new model include the ability to integrate the energy sub-systems into a single model, access to well-developed techniques for handling large and complex systems, a simultaneous rather than iterative solution, and ease of computerization.

An analysis of thermodynamic systems using the porcess graph model is presented in this paper. The process graph model is a linear-graph representation of systems undergoing thermodynamic processes. It provides a concise model of the interconnections and interaction interfaces of a thermodynamic system with respect to all types of flows. The analysis procedure accounts for all types of work, heat flow, and their interactions in a unified manner. The modelling and analysis procedures are illustrated by examples. The relation between the postulates of system theory and the laws of thermodynamics are stated as theorems. The first and second law analyses in thermodynamics are shown to be direct applications of network postulates from system theory. Appropriate system variables, namely, energy flow and exergy factors are introduced, which are shown to correspond to through and across variables, respectively.