Energy Services for INtegrated FLexible Operation

Energy Services for INtegrated FLexible Operation of Wastewater Systems, IEDO
Mauter, Stanford
Contract Number | 10-01-2021 to 03-31-2023 Abstract OFFICE OF ENERGY EFFICIENCY & RENEWABLE ENERGY U.S. DEPARTMENT OF ENERGY Secondary wastewater treatment processes consume 0.7-0.8 kWh/m3, most of which is provided by the electricity grid. This translates to large electricity costs and air emissions externalities, which can both be reduced by exploiting energy flexibility resources within the wastewater treatment sector. These resources include backup energy storage (i.e., conventional batteries) as well as “virtual batteries” that shift electricity load by storing raw wastewater, primary effluent, or low-pressure compressed biogas. These underutilized energy flexibility resources are expected to support decarbonization and community benefits from the wastewater sector by halving the percentage of flared biogas, limiting local air emission damages from flaring, supporting the stability of the electricity grid, and mitigating the electricity price increases the industry is currently experiencing.
This project develops automated control tools for integrated (i.e., facility-scale) planning and operation of wastewater resource recovery facilities’ (WWRFs’) energy flexibility capacity. Its innovation lies in using statistical learning on IoT sensor data and wastewater process models to design cost-effective energy flexibility upgrades to wastewater treatment facilities. Next it uses site-specific, dynamic simulation and control to facilitate real-time operation of the facility for carbon reduction and energy bill savings. During Budget Period 1 (BP1) the recipient developed the simulation-based planning library for WWRFs and used the design tool, TEA, and LCA module to iteratively search for financially optimal energy flexibility upgrades at our partner facility in Northern California. The optimal flexibility upgrades would reduce electricity bills for our partner facility by 17% for a 3% annual return on investment and a payback period as low as 6 years. LCA shows optimal upgrades are associated with a reduction in lifecycle GHG emissions, primarily due to a 45% reduction in biogas flaring. Alignment with Office Mission Background Conclusions Challenges and Impact Challenges:
Wastewater consumes 0.7-0.8 kWh/m3; electricity bills are 25-40% of operating expenses
Tapping embedded energy flexibility processes to reduce costs must address operational complexity and robustness
Impact:
10-20% electricity bill savings due to load shifting and peak shaving
12% GHG emissions reduction due to reduced flaring and peak-hour electricity usage
Increased resilience to power interruptions or electricity generation equipment failure
High scalability due to tool’s modularity and potential to integrate with existing hardware Project Outline Innovation: Integrated energy flexibility control platform for wastewater resource recovery facilities
Project Lead: Stanford University
Project Partners: Silicon Valley Clean Water
Timeline: 10-01-2021 to 09-30-2024, progress 50%
Budget: Budget Period: 1, Cost Share: 20%




* Projected
End Project Goal:
Energy flexibility design optimization library that uses facility data and design characteristics to select optimal energy flexibility upgrades that 1. Achieve positive ROI and PBP < 8 years and 2. Have negative lifecycle GHG emissions impact
Real-time automated control library that selects optimal energy flexibility schedules, achieving better simulated financial performance than SVCW’s current battery operation
Demonstration of automated control library on live data stream from Silicon Valley Clean Water with actual performance similar to simulated performance Wastewater treatment is energy and emissions intensive, accounting for 1% of the U.S.’s electricity [1] and >2% of its GHG emissions [1]–[4]. But it is a substantial energy resource: state-of-the-art wastewater facilities reduce their energy and emissions footprint by recovering biogas from wastewater and combusting it on-site for combined heat and power.
This project focuses on another major energy resource the wastewater treatment sector offers: energy flexibility. Broadly, energy flexibility is a facility’s ability to change electricity use timing in response to prices or other incentives. Wastewater facilities possess multiple direct or indirect energy storage mechanisms (e.g., wastewater or biogas storage) they can use to lower costs and emissions. For example, flexibility allows more efficient use of carbon neutral biogas by allowing it to be stored when it isn’t needed (avoiding flaring); a battery allows a facility to use electricity during hours when the grid mix is cleaner/cheaper.
Wastewater facilities do not typically use their energy flexibility due to lack of suitable dynamic treatment system energy models and operator reluctance to repurpose key unit processes (e.g. storage tanks, pumps) for energy management [3], among other things. A few facilities use Li-Ion batteries to manage peak demand, but these are typically operated separately from treatment systems, with limited benefits. Generally, the sector lacks models for planning and operating energy resources that are already well-established for commercial and residential applications [5]–[6].
This project develops models for planning and operating energy flexibility resources in the wastewater sector. Data-driven, simulation-based design and optimization are used to ensure customizability to a wide range of facilities. In addition, models are “integrated”, that is, they encompass all a facility’s relevant processes, allows facilities to reap the benefits of facility-scale coordination (e.g. coordinating a Li-Ion battery and co-generator). Results Key Achievements Publications:
Bolorinos, J.; Meagan, M. M.; Rajagopal, R. Integrated Energy Management at Wastewater Facilities (under Review). Environ Sci Technol 2023
Conference presentations:
”Energy flexibility planning for wastewater treatment facilities”, American Environmental Engineering and Science Professors Conference, June 23-25 2022
Technical achievements:
Biogas and energy demand models have an out-of-sample cross-validated relative squared error <5%
Energy flexibility design tool search over 5 energy storage design parameters with 24 simulation replicates in <6 hours References Acknowledgements Future Work Develop facility-scale “model predictive control” method that forecasts future performance and optimizes all a facility’s relevant energy flexibility resources accordingly
Develop model predictive control simulation to estimate the benefits of real-time facility-scale energy flexibility operation
Run simulation on commercial partner’s (SVCW’s) sensor data
Create and run sensor “data stream” at SVCW that sends data to software and system in real-time
Test developed model predictive control method on data stream Technology Transfer Stanford has reached out to three other California wastewater utilities for feedback on energy flexibility tool and modeling approach
This DOE project was selected as a business case study for Stanford’s Graduate School of Business Summer 2022 Ignite program
A market study and commercialization plan was prepared by a team of students and postdocs led by Dr Jose Bolorinos, this project’s postdoctoral research assistant Energy flexibility is commercially viable for commercial partner’s case study facility
The nature and profitability of energy flexibility upgrades strongly depends on a facility’s existing treatment configuration and available sources of energy flexibility
Energy flexibility upgrades always result in a net GHG emissions reduction
Benefits for wastewater + biogas storage larger than battery due to battery’s high embodied (Scope 3) emissions
Optimal battery storage provides 6 (1) hours of additional autonomy in a planned (unplanned) power outage
Raw wastewater storage is more useful for preventing system shutdown
Use for energy bill management leaves adequate volume for wet weather events AMMTO & IEDO JOINT PEER REVIEW
May 16th-18th, 2023
Washington, D.C. This poster does not contain any proprietary, confidential, or otherwise restricted information Industrial decarbonization: Operational GHG emissions reductions averaging 12% of baseline
Revitalization of manufacturing: 17% average reduction in electricity costs, a large fraction of WRRF’s operating expenses
Community Health: 45% reduction in biogas flaring; flexibility supports electricity grid’s renewable transition [1] EPRI, “Electricity Use and Management in the Municipal Water Supply and Wastewater Industries,” pp. 1–194, 2013, Accessed: Mar. 23, 2023. [Online].
[2] EPA, “Inventory of U.S. GHG Emissions Sources and Sinks: 1990-2015,” Washington, DC, 2016.
[3] J. P. Alvarez-Gaitan, M. D. Short, S. Lundie, and R. Stuetz, “Towards a comprehensive greenhouse gas emissions inventory for biosolids,” Water Res, vol. 96, pp. 299–307, Jun. 2016, doi: 10.1016/J.WATRES.2016.03.059.
[4] L. Miller-Robbie et al., “Life cycle energy and greenhouse gas assessment of the co-production of biosolids and biochar for land application,” J Clean Prod, vol. 91, pp. 118–127, Mar. 2015, doi: 10.1016/J.JCLEPRO.2014.12.050.
[5] T. Lambert, HOMER® Energy Modeling Software Computer software. Vers. 00.” USDOE, 2000.
[6] “Storage Value Estimation Tool (Storage VET).” EPRI, 2016. TEA and design optimization
Digital twin simulation + “lazy-greedy” search used to find optimal energy flexibility upgrades for case study facility
Optimal upgrade: 3.2 MWh/ 0.88 MW battery
Performance (15-year lifetime):
NPV: $720k
ROI: 3%/year
PBP: 9 years
Benefit over system installed at SVCW: $150k Dynamic digital twin Lifecycle Assessment
LCA was performed on financially-optimal energy flexibility upgrades:
Scope 1, 2 emissions estimated from dynamic digital twin; Scope 3 emissions estimated from literature searches
Results:
All lifecycle impacts negative
Savings range from -1 (battery) to -6 (gas holder) g/m3 wastewater treated Resilience analysis
Power outages simulated for wastewater systems with 1.5 MW backup diesel generator and 24-hours fuel supply
Hours of “autonomy” computed for system with optimal (3.2 MWh/ 0.875 MW) battery and 24-h raw wastewater storage
Storage availability curves estimated for wastewater storage used for energy bill management Storage Availability Case study facility Silicon Valley Clean Water (SVCW)<br>