Abstract

Ambitious sustainable development goals lead cities to invest in renewable energy infrastructure as the primary energy source. With an increasing number of people moving to urban areas, providing reliable heating energy, especially in cold regions needs more investigation. A resilient and reliable energy system is able to provide the intended demand in day-to-day operation under a wide range of failure modes, as well as extreme situations. This research aims to provide a framework to investigate reliability indices, availability, and resilience of electric heating systems.
The availability and reliability indices such as Energy Not Served (ENS) and Loss Of Load Expectation (LOLE) are evaluated using sequential Monte Carlo (SMC) simulation. SMC is a probabilistic approach that is able to capture the random failures and behaviour of the systems over a defined sequence of time. To evaluate the energy system resilience under a major power outage, a method considering the resilience in terms of system robustness, ENS, and Average Energy Not Served (AENS) is proposed. During the power outage, resilience metrics are analyzed considering critical loads instead of business-as-usual demand. The critical load is the minimum demand that needs to be provided to customers and it is defined based on the ranking and assigning weights to user types.
The method is applied to a district to compare the performance of centralized and decentralized ground source heat pump systems. In terms of system resilience, the two energy systems have similar performance, however, results of the reliability simulation indicate that the centralized scenario is more reliable than the decentralized design in terms of the number of hours where energy is available to the area, and the amount of energy served to the consumers.