The task of developing effective public energy policy is becoming increasingly difficult. Economic liberalization favors competitive markets, private interests, and light regulation, while climate protection and sustainable land usage have created new public interests. Decentralized technologies have added to the analytical challenge and include weather-dependent energy sources, embedded generation and cogeneration, end-use efficiency, and status-aware demand. Smart grids and intelligent control look likely to radically alter system architectures over the coming decades. These new circumstances also offer opportunities for innovative public policy responses to motivate and guide the transition toward more sustainable and effective energy systems. This thesis presents a new energy systems framework that combines a range of technical and microeconomic processes at high resolution within the one simulation. A class library provides modelers with a coherent set of energy technologies, plant operations, dispatch methods, supply agreements, commodity types, and differentiated surroundings. These entities can then be used to populate a systems model that then evolves sequentially in fixed steps of between 5 min and 24 h and over one year typically. Structural change, including new capital works, is necessarily exogenous, but can be investigated via scenarios. Scenarios are run against some selected reference case and the resulting public interest performances are then reported by difference. Sets of scenarios can be interactively screened for Pareto dominance to assist with ranking and assessment. High-resolution models are data intensive but are indicated whenever fine-grained network effects and intertemporal dynamics are potentially present and need capturing and/or operator-level decisioning requires portrayal. The method itself draws on topics from graph theory, dynamical systems theory, multi-agent systems, engineering design, mixed-integer programming, project finance, and object-oriented software development. These ideas are encapsulated in the command-line application xeona, conceived and written as part of this project. Revision 9218 contains 58000 source lines of C++. The program was tested with a proof-of-concept model based on a simplification of the New Zealand national energy system. Although limited to 24 technical assets, 18 operators, 6 commitment domains, 5 commodities, and 6 environmental contexts, the nine scenarios deployed produced interesting and subtle results. A key motivation behind the development of xeona was the need to better understand end-user options and responsiveness in relation to the status of the system at large. The customer-side-of-the-meter is not well represented by mainstream policy analysis and high-resolution modeling applied to this area may well reveal untapped and worthwhile public interest opportunities.
Robert Ian Morrison (Thu,) studied this question.