Abstract
The paper proposes a demand response scheme controlling many domestic electric water heaters (DEWHs) with a price function to consume electric power according to a target schedule. It discusses at length the design of an algorithm to calculate the price function from a target schedule. The price function is used by the control of each DEWH to automatically and optimally minimize its local heating costs. It is demonstrated that the resulting total power consumption approximates the target schedule. The algorithm was successfully validated by simulation with a realistic set of 50 DEWHs assuming perfect knowledge of parameters and water consumption. It is shown that the algorithm is also applicable to clusters of large numbers of DEWHs with statistical knowledge only. However, this leads to a slightly higher deviation from the target schedule.
Highlights
In electricity networks, suppliers have to inject the amount of electricity that is consumed by their customers at the same time
Evaluation for a single day The performance of the proposed algorithm is assessed with a realistic setup of domestic electric water heater (DEWH) for a fixed horizon of one day as well as with a receding horizon over 6 days
Scenario configuration The proposed algorithm requires a set of DEWHs with a sufficient diversity of τ -values in order to produce reasonable results
Summary
Suppliers have to inject the amount of electricity that is consumed by their customers at the same time. The supplier instructs power plants to produce this power, by sending each a so called target schedule containing the amount of power to be produced for each time interval (Konstantin 2013). The approach protects the customer’s privacy by design as no central entity has knowledge about the Lübkert et al Energy Informatics 2018, 1(Suppl 1): customer’s flexibility in power consumption. It requires that suppliers can fix prices leading to given consumption schedules
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