Opportunity to Reduce the Need for Peak Load
A district heating company identified an opportunity to reduce the use of costly peak load by introducing smart load control among customers in one of its district heating networks. By shifting customers’ heat demand over time, production peaks could be smoothed and the need for expensive peak production reduced.
To test this hypothesis, a structured and data-driven analysis was required. Sigholm was commissioned to carry out a study aimed at assessing what proportion of customers’ heat demand can realistically be controlled, under which conditions this is possible, and what economic impact smart load control can generate at system level.
Analysis of Customer Flexibility and System Constraints
The work was based on a detailed analysis of production and load data, combined with established knowledge of the thermal inertia of buildings. By analysing how long different types of properties can reduce their heat demand without significantly affecting comfort, a practical framework for the application of smart load control was developed.
To translate customer flexibility into actual system benefits, the district heating network was modelled as an accumulator, where curtailed load must be recovered at a later point in time. The model accounted for constraints in base production, efficiencies, and the need to balance the system over time. Several scenarios were analysed, ranging from theoretically optimal to more realistic assumptions regarding customer participation, controllability, and compensation levels.
Results and Insights
The study showed that smart load control in the specific case can help reduce the use of peak load, but that the overall economic potential in the system is limited. In many periods, the main constraint is not customer flexibility, but rather the production system’s ability to generate the deferred load at other times.
During certain weeks, there are good opportunities to shift a significant share of peak load, while during other periods the potential is very limited or non-existent.
The analysis also provided important qualitative insights. Implementing smart load control involves both technical and organisational complexity, including dependencies on customers’ internal systems, the need for coordination with production optimisation, and uncertainties related to long-term customer participation. These aspects need to be considered in strategic decisions regarding investments in flexibility solutions.
Decision Support for Continued Development
The assignment resulted in a clear decision-making basis that highlighted both the opportunities and limitations of smart load control in the district heating network in question. The study provided the district heating company with a data-driven foundation for comparing smart load control with alternative options, thereby enabling well-informed decisions on the next steps in the development of the production system.
