D5.3: Campus Microgrid Model Prototype

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The deliverable 5.3: Campus Microgrid Model Prototype was submitted by NTNU, ABB, POW & TE with contributions from NTNU and TK in April 2021. The executive summary of the deliverable is available below and the full deliverable at the end for download:

+CityxChange (Positive City Exchange) is a research and innovation smart city project, where cities experiment to integrate smart positive energy solutions. Through the use of digital services (e.g., smart automation), the quality of life for and together with the citizens shall be improved, more energy produced than consumed (e.g., Positive Energy Blocks), and experiences with cities across Europe exchanged to learn faster together. In this regard, Positive Energy Blocks are a cornerstone on integrating renewables, introducing smart coordination of energy assets (e.g., energy storage, solar PV and EVs) among buildings, and promote a consumer-centric energy transition in smart cities.

As part of the +CityxChange project, this report details the work carried out to optimise, automatize, smart control, and exploit the energy flexibility potentials of buildings within a microgrid. Through enabling smart operations and real-time control of the buildings’ energy management systems, the objective is to contribute to the realisation of local energy markets and Positive Energy Block (PEB). A well-functioning PEB will require smart automatization and ensure that on-site local energy production is efficiently used by activating flexibility assets or mechanisms (e.g., demand response, storage, load shedding or shifting, etc.) to balance renewable production (e.g., solar PV) or potentially react to signals (e.g., prices) of an ‘intra-PEB’ market between the participating buildings and the wider microgrid. This report, deliverable D5.3 of the +CityxChange project, details the work related to implementing smart flexibility in buildings in the context of a microgrid by applying it to a real-life case (NTNU campus microgrid). Increasing the energy flexibility in the microgrid brings more synergy between production and consumption, and therefore, contributes to move NTNU towards a PEB. The development of this demonstrator and related work activities were as follows:

1. Estimating flexibility potentials from two energy assets in buildings. We provide a framework along with its theoretical foundation on how to estimate the flexibility potentials and the benefits of smart control to: reduce energy demand, make energy supply-demand operations more efficient, and enable the possibility to react to external signals (e.g., electricity prices from a common energy market). Some of these frameworks will also be used to detect flexibility in D5.6 and D5.11.

2. Requirements and methods to enable smart control of assets. We were deploying this demonstrator in a real-life setting needed coordination among multiple software platforms. Here we combined new software (model created by NTNU in the programming language Python), the deployment of ABB OPTIMAX (Virtual Machine), and the buildings’ existing ICT management system.

3. Demonstrating smart control of energy assets into the NTNU campus microgrid. By developing an automated optimisation model connected to live data sources and regional energy market along with forecasting features (i.e. a rolling horizon approach for scheduling), we demonstrate the operations of two buildings in the NTNU campus, more specifically, smart control one heat panel in a ventilation system and one heat tank in a waterborne system.

4. Replicability and scalability to other energy assets, applications and services. Based on the campus’s Electrical Vehicles, an analysis of their flexibility value and smart charging potentials is outlined.

5. Based on the campus microgrid analysis, this report provides a predictive assessment of how the inter-PEB market can work in Trondheim between multiple PEBs. This presents various scenarios and results in the design of the common energy market.

6. As part of the solutions and demonstrator potentials done in this deliverable, a summary of methods to deploy this on follower cities or interested stakeholders is summarised (the optimisation models as software are made available as open source).

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