Utility–service provision is a process in which products such as water, electricity, food, gas are transformed by appropriate devices into services satisfying human needs such as nutrition, thermal comfort, and wants such as e.g. entertainment. Utility products required for these processes are usually delivered to households via separate infrastructures, i.e. real-world networks such as electricity grids, water distribution systems or gas distribution networks. Additionally, they can be supplemented sourced locally from natural resources, e.g. electricity can be obtained from sun or wind. The main objectives of the research are to numerically evaluate feasibility of alternative approaches to utility–service provision problems and automatically generate suggestions of such alternative approaches, using knowledge base of present and future technologies and devices. These objectives are achieved via a simulation system implemented in C# and .NET 4.0 that is composed of the following blocks: an interface to define the utility–service provision problem (problem formulation), an interface to define candidate solutions (transformation graphs), a computational engine to analyse the feasibility of transformation graphs, a heuristic search algorithm to generate transformation graphs and a XML database.
The core of the proposed approach is a simulation system that carries out a feasibility study of transformation graphs. A transformation graph describes direct and indirect transformations of products into defined services or other products using various devices. The transformation graphs are represented in a form of standard directed graph where devices, product storages and services are nodes and edges represent product and service carriers. In the adapted approach each product has associated storage. The information about products, services and devices is used to create a visual representation of the content of the database - a Mastergraph. It is a directed hypergraph where services and product storages are nodes, while devices are edges spanning between. Since devices usually connect more than two nodes, a standard graph would not suffice to describe utility–service provision problem and therefore a hypergraph was chosen as a more appropriate representation of the system.
Two methods for defining transformation graphs are proposed. In the first one the candidate solutions are constructed manually. Additionally, an interface to calculate shortest paths between two products or a product and a service in Mastergraph was developed to simplify the manual process. In the second method, the transformation graphs are automatically generated using heuristic search approach developed for this model.
The functionalities of the proposed approach are presented through case studies. A benchmark case study based on the literature is analysed and compared with automatically generated solutions that vary in terms of energy and water delivered by the infrastructure as well as the total cost of supplying and removing products. These case studies showcase how the use of natural resources, recycling of some of the products that would normally be disposed, or simply the use of alternative devices have impact on the total cost and the amount of water and energy delivered by the infrastructure
