(527c) Optimal Design and Operation of Integrated Multi-Vector Energy Networks

Integrated multi-vector energy networks are becoming more important because we have a much greater variety of primary resources of energy such as wind, solar, biomass etc. Whereas existing energy systems are dominated by fossil fuels as the primary resource, with electricity and natural gas as the energy vectors, increasing the penetration of renewable energy will change the energy mix and other energy vectors, such as hydrogen, methanol, syngas, ammonia etc. may also play important roles. There are many different pathways to satisfy energy service demands through different energy vectors: for example, hydrogen, biofuels or electricity are considered promising alternatives to petroleum for the transport sector.

The aim of this work is to determine the best design and operation of integrated energy network to obtain the most value from limited available resources while minimising its negative socio-economic and environmental impacts. This endeavour requires the use of mathematical models to provide an accurate representation of the potential technologies and transport infrastructures that may become part of the network, as well as optimisation techniques to determine the most promising designs among the many possible alternatives. This involves selecting the right combinations of conversion and storage technologies, where to locate them, what their capacities should be and how to interconnect them via transport infrastructures. Moreover, the mathematical models need to be sufficiently detailed to account for all of the operational issues at different time scales (e.g. hours, days, seasons, years) and interactions between the different energy vectors. In this conference, we will present a general mixed integer linear programming model that can simultaneously determine the design and operation of any integrated energy networks comprising technologies for conversion and storage and infrastructures for transport of resources (both material and energy). The model takes into account the spatial and temporal distribution of system properties and simultaneously determines the spatial structure, i.e. the location, number, capacity of the technologies and the structure of the transport infrastructures that connect them, as well as the hourly operation of the entire network. It is a dynamic model in order to properly account for the intermittency of renewables and dynamics of energy storage. The model includes detailed and coherent storage inventory balances, thus it is able to track the inventory level of each resource in storage at every hour over the entire planning horizon (e.g. out to 2050).

This presentation will describe the model and discuss a decomposition method that enables this very large, and otherwise intractable, optimisation model to be solved. We will also present case studies wherein the design and operation of an integrated electricity-hydrogen-syngas-natural gas network are determined in order to maximise the value (or minimise the cost or environmental impacts) of meeting the demands for heat, electricity and transport fuels in Great Britain.