Stochastic Energy Management of Sustainable Wastewater Treatment Plants in Smart Distribution Systems
Creators: Ma, Siyao
Publisher: name: University of Alberta Library
Year: 2024

<p>Wastewater treatment plants (WWTPs), in their current state, appear to be significant energy-consuming entities, harboring enormous but neglected potential for energy production. When proper energy management is applied, they are critical for enhancing the efficiency, sustainability, and resilience of smart distribution systems (SDSs). However, various elements in SDSs with inherent randomness can significantly impact the energy management of WWTPs, including the power output of renewable energy sources (RES), the load demand for electricity, and electricity prices. In this thesis, the stochastic energy management of sustainable WWTPs in SDSs is investigated.<br>
Firstly, a multi-agent stochastic energy management scheme is investigated for SDSs with sustainable WWTPs in order to ensure system voltage quality while minimizing cost. Sustainable WWTPs incorporated in this work comprise various RES such as photovoltaics (PV), hydroelectric, cogeneration, and battery energy storage systems (BESSs). The distribution system operator (DSO) monitors and controls the SDS, which is integrated with BESSs. To achieve optimal operation of sustainable WWTPs while coordinating with DSO and BESSs, this energy management problem is formulated as an interactive partially observable Markov decision process (I-POMDP). The uncertainties associated with incoming wastewater flow, light intensity, and load demand are managed within the framework of the presented sustainable WWTP model. The coordination between the three interdependent entities, i.e., sustainable WWTP, DSO, and BESS, are modelled by I-POMDP featuring interaction and partial observation. An exact solution of the I-POMDP is derived to determine the optimal actions for the sustainable WWTP. Furthermore, to address the complexity arising from the curse of history and dimensionality, a pruning algorithm, based on on-peak and off-peak electricity price analysis, is further presented. The effectiveness of proposed energy management scheme is demonstrated by case studies based on the IEEE 33-Bus Test Feeder, the wastewater flow generated based on end-use model, as well as the historical data of light intensity and load demand.<br>
Additionally, the energy generated by WWTPs can be utilized not only for self-consumption but also for establishing sustainable communities with nearby energy consumers, RES, and energy storage systems within SDSs. A significant reason for establishing a sustainable community in proximity is the economic consideration of the thermal energy characteristics. As electrical energy, thermal energy, and wastewater production events often occur at different timescales, a multi-timescale Markov decision process (MMDP) is utilized to formulate the energy management problem of the sustainable community connected to the smart grid, which includes a sustainable WWTP. The objective is to minimize the total operating cost of the sustainable community while mitigating the impacts on the SDS, considering the randomness of electric loads, wastewater flow, and weather conditions. The proposed energy management scheme is also assessed using the IEEE 33-Bus Test Feeder and incorporates real data on weather conditions, along with wastewater flow information generated through the end-use model. </p>