Draft:Energy Hub

The Energy Hub is a analytical framework designed to find the optimal configuration and operation pattern of a Multi-energy system. An energy hub typically consists of four types of components: energy input, energy output, conversion technology and storage technology. Moreover, energy hubs can be connected via real or hypothetical energy pipeline (for example, electricity wires, hot water pipes or even transportation with cars) and form an energy hub network.

History

The energy hub was initially developed as a method in "a vision of future energy networks (VOFEN)" project in High Voltage Laboratory in ETH Zurich, as an interface between different energy infrastructure and demands. Originally, the following equation was presented to represent the energy balance constraint in the energy hub: $$E^{dem}=\left[\begin{array}{cc}C& -S\end{array}\right]\left[\begin{array}{c}{E}^{sup}\\ Q\end{array}\right]$$Where:

• $E_{[n\times 1]}^{dem}$ and $E_{[m\times 1]}^{sup}$ are column vectors representing demand and supply energy flows.
• $Q_{[(m+n)\times 1]}$ is a column vector that records energy flow from and to the storage technologies.
• $C_{[n\times m]}$ is the conversion coupling matrix, representing efficiencies of conversion technologies.
• $S_{[n\times (m+n)]}$ is the storage coupling matrix, representing the efficiency of storage technologies.

This framework was later expanded by Schulze et al. and Ahčin and Šikić, to include local energy production and demand response, respectively. The expanded energy hub formulation can be written as the equation below:$$E^{dem}+E^{exp}=\left[\begin{array}{ccc}C& -S& -D\end{array}\right]\left[\begin{array}{c}{E}^{sup}+E^{re}\\ Q\\ H\end{array}\right]$$Where:

• $E_{[n\times 1]}^{exp}$are the energy flows that are sold back to the supplier;
• $E_{[m\times 1]}^{re}$ are energy flows that are generated on-site;
• $H_{[k\times 1]}$ is the additional energy flows that are either requested or avoided by the demand response;
• $D_{[n\times k]}$ is the demand-response coupling matrix, representing the dynamics of the demand (in case of buildings, this matrix could represent the thermal mass of the building structure).