Abstract
An integrated model predictive control (MPC) strategy to control the power consumption and the effluent quality of a water resource recovery facility (WRRF) by utilizing the storage capacity from the sewer system was implemented and put into operation for a 7-day trial period. This price-based MPC reacted to electricity prices and forecasted pollutant loads 24 hours ahead. The large storage capacity available in the sewer system directly upstream from the plant was used to control the incoming loads and, indirectly, the power consumption of the WRRF during dry weather operations. The MPC balances electricity costs and treatment quality based on linear dynamical models and predictions of storage capacity and effluent concentrations. This article first shows the modelling results involved in the design of this MPC. Secondly, results from full-scale MPC operation of the WRRF are shown. The monetary savings of the MPC strategy for the specific plant were quantified around approximately 200 DKK per day when fully exploiting the allowed storage capacity. The developed MPC strategy provides a new option for linking WRRFs to smart grid electricity systems.
Highlights
The transition towards an increasing share of renewable energy sources is an essential step to reduce CO2 emissions and mitigate severe climate change
We propose an integrated model predictive control (MPC) strategy connecting water resource recovery facility (WRRF) and sewer systems and offering flexible energy consumption in a smart grid system
This paper illustrates the first application of model predictive control (MPC) in a price-based, Demand-Response set-up to control an integrated sewer-wastewater system during dry weather
Summary
The transition towards an increasing share of renewable energy sources is an essential step to reduce CO2 emissions and mitigate severe climate change. This transition requires the implementation of smart grids; that is, making electrical grids able to cope with highly fluctuating sources (such as wind and solar power) while being able to match supply and demand ( Jørgensen et al ). This can be obtained by either storing the electricity for later use or by modifying the consumption . This concept is referred to as Demand Response (Palensky & Dietrich ; O’Connell et al )
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