A Peak Demand Control Algorithm for Multiple Controllable Loads in Industrial Processes

Abstract

The peak demand or demand limit control is an important part of the actions that industries carry out to optimize their energy consumption and reduce the costs related to their electricity billing. Prioritized switching of multiple appliances is often needed in order to reduce demand and energy consumption during peak load periods. The present article describes a peak load limitation algorithm that estimates the optimal disconnection time for one or more electrical loads before the electric demand exceeds a preset limit. This algorithm uses parametric and variable load factors that vary dynamically depending on what loads are present at a given time. For its validation, a software-in-the-loop testbed was designed and developed, in which multiple electrical loads were simulated via LabVIEW software and connected to a PLC controller emulated through CODESYS software. In this environment, several test configurations were executed and evaluated to study the influence of variables such as the nominal power and the disconnection priority of loads in the algorithm output. The results showed that the control algorithm is effective for peak load limitation, the maximum demand value reached during simulations tests did not exceed the preset demand limit at any time interval. The performance of the algorithm could be improved when prioritizing the shutdown of loads with higher nominal power or when increasing the anticipation time used for the disconnection of the controllable loads.INDEX TERMS Demand response, demand side management, load levelling, peak shaving, smart grid.

Maximum Reserved Capacity of Aggregated Electric Water Heaters Virtual Battery for Peak Management

“…Utilities generally use available more costly spinning reserves to meet peak demands to ensure grid stability and customer comfort. This can increase the customer electricity price [1], contribute to harmful effects on the environment and result in poor generation efficiency [2]. A solution to reduce these costs is to control electric thermal loads through programs such as Demand Response (DR).…”

“…The number of TCLs are also expected to increase due to greater demands for heating, cooling, and population growth. The opportunity exists for such devices to contribute significant capacity for ancillary services such as peak shaving [1], [2], [11]- [14]. Their maximum capacity can be used as an emergency backup resource, deployable at the utility level for peak shaving and frequency restoration purposes.…”

“…We consider a continuous thermal model as an approximation to the simple model in (1) where each EWH has a continuous power input 𝑃 𝑘 (𝑡) ∈ {0, 𝑃 𝑟𝑎𝑡𝑒 𝑘 }. Therefore, the continuous thermal model in ON state (i.e., 𝑚 𝑘 (𝑡) = 1) can be written as [8], [10] 𝜃 ̇𝑘(𝑡) =…”