Wastewater treatment plants are energy-intensive loads with operational flexibility, which has motivated interest in how these plants can support power grid operation through demand flexibility. Since electricity is often the largest single operating cost for wastewater treatment plants, leveraging demand flexibility could offer significant financial benefits. One approach to reduce and shift the wastewater treatment plant's demand is through the use of biogas, a by-product of anaerobic digestion within the wastewater treatment process. Biogas (composed primarily of methane and carbon dioxide) is a renewable fuel that can be used to produce electricity to offset the plant's demand from the grid. However, many wastewater treatment plants currently flare biogas. The goal of this paper is to determine the optimal use of an on-site biogas storage tank and generator to minimize the costs of a wastewater treatment plant participating in the frequency regulation market. To do this, we formulate the wastewater treatment plant optimization problem subject to biogas and frequency regulation constraints while managing biogas production uncertainty. We solve for the biogas generator schedule and frequency regulation capacity to minimize operational costs. In a case study using data from a California wastewater treatment plant, we demonstrate how our approach can exploit electricity rate structures to reduce electricity costs and effectively participate in the frequency regulation market.

Bibtex data:

@article{StuhlmacherIREP2025,
    author = {A. Stuhlmacher and A. Kody and M. Wu},
    title = {Optimizing Biogas Use in Wastewater Treatment Plants For  Demand Flexibility},
    journal = {Sustainable Energy, Grids and Networks  - Special Issue for the 2025 IREP Symposium on Bulk Power System Dynamics and Control},
    year = {2025},
    month = {June},
    address = {Sorrento, Italy}
}

Bibtex data:

@inproceedings{SakibPESGM2025,
    author = {A.N. Sakib and A. Stuhlmacher},
    title = {Leveraging Drinking Water Pumps as Flexible Loads Using Input Convex Neural Networks},
    booktitle = {Proceedings of the IEEE Power and Energy Society General Meeting (PES GM)},
    year = {2025},
    address = {Austin, Texas}
}

Bibtex data:

@article{StuhlmacherTPWRS2025,
    author = {A. Stuhlmacher and S. Guikema and J. L. Mathieu},
    title = {Assessing Power and Water Network Resilience When Water Pumps Provide Frequency Regulation},
    journal = {IEEE Transactions on Power Systems},
    year = {2025}
}

Bibtex data:

@inproceedings{StuhlmacherHICSS2025,
    author = {A. Stuhlmacher and J. L. Mathieu},
    title = {Demand Response Potential of Drinking Water Distribution Networks},
    booktitle = {Proceedings of the 58th Hawaii International Conference on System Sciences (HICSS)},
    year = {2025},
    address = {Waikoloa, Hawaii}
}

Bibtex data:

@inproceedings{StuhlmacherHICSS2024,
    author = {A. Stuhlmacher and J. L. Mathieu and P. Seiler},
    title = {Optimizing Dual-Axis Solar Panel Operation in an Agrivoltaic System and Implications for Power Systems},
    booktitle = {Proceedings of the 57th Hawaii International Conference on System Sciences (HICSS)},
    year = {2024},
    address = {Waikiki, Hawaii},
    month = {January}
}

The electrical grid has undergone significant transformations, which have had a profound impact on its distribution system development and expansion. These changes have been primarily driven by changing load profiles, distributed generation sources, and increasingly extreme weather events. Advancements in sensor and communication technologies have played a pivotal role in addressing and adapting to these changes. These changes have also led to an increased focus on reliability and resilience in planning, with priority placed on ensuring robust grid connectivity and flexibility.

Three decades ago, power distribution systems were primarily radial with unidirectional power flow. Today's electrical distribution systems have distributed energy resources, leading to bidirectional power flow. The utility's geographic information system network, advanced metering infrastructure, and other technologies are leveraged to allow feeders and distributed energy resources to be interconnected. This has facilitated the integration of the electric grid with networked microgrids, which has improved the overall resilience and efficiency of the distribution system.

While there have been notable improvements in grid planning, the power grid remains vulnerable to high-impact, low-frequency events caused by climate change, such as hurricanes and tornadoes. This monograph outlines potential solutions for addressing future electric grid issues, including transformer overloading due to electric vehicles, optimization challenges, advanced feeder reconfiguration, and contingency planning for extreme events. The proposed approaches focus on the implementation and operation of new technologies, such as renewable energy sources, batteries, flexible loads, and advanced sensors, that have the potential to transform distribution network planning and operation. From traditional methods to innovative networked microgrids within existing infrastructure and non-wire alternative strategies, this monograph provides a comprehensive overview of stateof- the-art strategies for future problems.

Bibtex data:

@article{StuhlmacherFnT2023,
    author = {A. Stuhlmacher and C. Ten and L. Dilworth and Y. Tang},
    title = {Operational Planning for Emerging Distribution Systems: A Unique Perspective on Grid Expansion},
    journal = {Foundations and Trends in Electric Energy Systems},
    volume = {7},
    number = {2},
    pages = {63--164},
    year = {2023}
}

Large amounts of renewable energy resources are being added to the electric power grid in a push to mitigate the effects of climate change. Due the intermittent and uncertain nature of these resources, more flexibility is needed to ensure safe operating conditions of the power grid. A growing body of research has shown that real-time control of flexible electric loads can provide flexibility to the power grid. For instance, drinking water distribution networks can be treated as flexible, controllable assets to the power grid by leveraging the power consumption of water supply pumps and storage capabilities of water tanks. Initial research has explored optimizing the operation of water distribution networks to support the power grid; however, the impact of uncertainty on network performance and value has not been considered.

In this dissertation, an integrated power-water optimization problem is developed subject to the water and power network constraints and multiple sources of uncertainty. The operation of water distribution networks is optimized to provide multiple local and system services-such as voltage and frequency regulation-to power networks. The integrated optimization of the water distribution network and power network is challenging because both networks have nonconvex models and experience uncertainty (e.g., water and power demands). Additionally, changes in network operation need to clearly provide value to both system operators as well as maintain or improve upon network resilience. The associated benefits and drawbacks of the integrated water-power optimization framework are investigated, with a particular focus on performance, conservativeness, and computational tractability. First, state and country-wide estimates of the power and energy capacity of water distribution networks as flexible loads are calculated using publicly available water distribution network utility information, indicating that water distribution networks can provide a sizable flexible resource. Second, stochastic and robust optimization frameworks are developed to optimally schedule and control the water distribution network to provide power system services while ensuring the safe operation of the power and water distribution networks given power and water demand uncertainties. Third, to address challenges surrounding problem complexity and scalability, this work develops proofs that the monotonicity properties apply to the water flow constraints under certain assumptions, uses approximation and relaxation techniques to reformulate the power-water problem as a convex program, and proposes an analytically reformulated probabilistic framework that manages uncertainty differently in the power and water network. Fourth, the flexibility of the water distribution network may be underutilized if any one power system service is considered. To prevent this, a formulation is developed where the water network provides multiple services simultaneously. This maximizes the overall benefit to the power grid and increases the value proposition to the water distribution network operator. And fifth, optimal pump operation strategies are evaluated to ensure that the power and water networks can respond and adapt to natural hazard events when the water distribution network is providing grid services.

Case studies demonstrate the capability of the water distribution network pumps to provide services to the power grid. By co-optimizing the power grid and the drinking water distribution network, improvement in costs, reliability, and resiliency can be realized across these two critical infrastructure systems. Additionally, leveraging the water distribution network to provide flexibility to the power grid can allow for greater quantities of renewable energy resources to be incorporated into the grid and reduce carbon emissions.

Bibtex data:

@inproceedings{Stuhlmacher2023,
    author = {A. Stuhlmacher},
    title = {Optimal Scheduling and Control of Uncertain Coupled Power-Water Distribution Networks},
    school = {University of Michigan},
    year = {2023},
    month = {May}
}

Drinking water distribution networks (WDNs) can be operated as flexible, controllable loads. In this paper, we consider using WDNs to provide local and grid level services simultaneously to the power grid. We formulate a robust water pumping problem to determine the amount of voltage support and frequency regulation that can be provided subject to network constraints while managing power demand uncertainty. We tractably reformulate the problem as a sequential optimization problem and solve for the scheduled water pumping operation, the frequency regulation capacity, and the optimal control policy parameters that update the pump operation based on the frequency regulation signal and power distribution network demand forecast error. We demonstrate our approach through detailed case studies. Additionally, we evaluate the performance of the reformulation and discuss the benefits and trade-offs of WDNs providing multiple services.

Bibtex data:

@article{StuhlmacherPSCC2022,
    author = {A. Stuhlmacher and J. L. Mathieu},
    title = {Flexible Drinking Water Pumping to Provide Multiple Grid Services},
    journal = {Electric Power Systems Research - Special Issue for the 2022 Power Systems Computation Conference (PSCC)},
    volume = {212},
    pages = {108491},
    year = {2022},
    month = {June},
    address = {Porto, Portugal}
}

Bibtex data:

@inproceedings{StuhlmacherIREP2022,
    author = {A. Stuhlmacher and J. L. Mathieu},
    title = {Uncertainty-Aware Methods for Leveraging Water Pumping Flexibility for Power Networks},
    booktitle = {Proceedings of the IREP Symposium on Bulk Power System Dynamics and Control},
    year = {2022},
    address = {Banff, Canada},
    month = {August}
}

Bibtex data:

@inproceedings{StuhlmacherCDC2023,
    author = {A. Stuhlmacher and L. A. Roald and J. L. Mathieu},
    title = {Tractable Robust Drinking Water Pumping to Provide Power Network Voltage Support},
    booktitle = {Proceedings of the Conference on Decision and Control (CDC)},
    pages = {4206--4213},
    year = {2021},
    month = {December}
}

Bibtex data:

@article{StuhlmacherIEEE2020,
    author = {A. Stuhlmacher and J. L. Mathieu},
    title = {Chance-Constrained Water Pumping to Manage Water and Power Demand Uncertainty in Distribution Networks},
    journal = {Proceedings of the IEEE},
    volume = {108},
    number = {9},
    pages = {1640--1655},
    year = {2020}
}

Bibtex data:

@article{StuhlmacherPSCC2020,
    author = {A. Stuhlmacher and J. L. Mathieu},
    title = {Water Distribution Networks as Flexible Loads: A Chance-Constrained Programming Approach},
    journal = {Electric Power Systems Research - Special Issue for the 2020 Power Systems Computation Conference (PSCC)},
    volume = {188},
    pages = {106570},
    year = {2020},
    month = {June}
}

Bibtex data:

@inproceedings{StuhlmacherNAPS2019,
    author = {A. Stuhlmacher and J. L. Mathieu},
    title = {Chance-Constrained Water Pumping Managing Power Distribution Network Constraints},
    booktitle = {Proceedings of the North American Power Symposium (NAPS)},
    year = {2019},
    address = {Wichita, KS},
    month = {October}
}