Strategic CIP Prioritization Utilizing Optimization Algorithms to Maximize Return on Investment

INTRODUCTION The City of Tulsa, OK engaged Tetra Tech and WCS Engineering to evaluate, optimize and prioritize sanitary sewer overflow remedial alternatives for the Northslope collection system. The Northslope sanitary sewer collection system and treatment facility provide service to the northern portion of Tulsa. This current system has over 950 miles of pipe, 18 lift stations, 4 storage facilities, and an 85 MGD treatment facility. OBJECTIVE This presentation will provide municipalities with an example framework to prioritize capital investments using a best in practice approach to apply intelligent algorithm optimization. The case study maximizes return on investment with respect to scheduling capital improvements to reduce the frequency and severity of sanitary sewer overflows as early as possible. There are many factors to consider when prioritizing collection system capital improvement projects. Selecting the implementation sequence that maximizes overflow volume reduction is one factor to consider; however, there may be value delivered to a greater number of customers if an investment is made that reduces several overflows in close proximity to houses rather than reducing a large, centralized overflow away from direct customer exposure. In this case study, these factors are considered when prioritizing capital projects to maximize return on investment. SIGNIFICANCE This presentation will provide the following benefits to the audience and industry: - Demonstrate how formal optimization software can be applied to prioritize large and complex capital programs including conveyance projects, storage facilities, inflow and infiltration remediation, and treatment plant upgrades. - Illustrate how approximately 82% of SSOs can be eliminated within the first 27% of capital expenditure in the case study example. - Provide a framework for other cities to optimize and prioritize SSO remedial measure plans. METHODOLOGY Optimization The Tulsa Optimization evaluated conveyance, storage, I/I remediation, and treatment alternatives to abate SSOs for different levels of service. To enable an exhaustive and objective evaluation of all feasible improvement alternatives, the optimization analysis was undertaken using Optimizer (product of Optimatics). The raw output from Optimizer was linked to customized post-processing tools to automatically generate ArcGIS maps and detailed solution summaries. Optimization runs were completed for a wide range of scenarios to demonstrate key trends and differences between strategies for different levels of service and with different combinations of alternatives. Additionally, a broad range of sensitivity analyses were completed to provide confidence in the recommended strategy. The variety of scenarios optimized provides valuable insights into potential treatment and collection system improvement strategies to mitigate system capacity deficiencies. The results from each scenario help to identify key trends and illustrate solution components that are consistent in each scenario and other solution components that are sensitive to key assumptions. The City can thereby make a more informed decision in determining a preferred solution based on the robust set of scenarios, anticipated costs and levels of service presented. Prioritization The objective of the prioritization was to determine the sequence of project implementation that would maximize return on investment with respect to scheduling capital improvements to reduce the frequency and severity of sanitary sewer overflows (SSOs) as early as possible. Multi-objective optimization analysis was applied using Optimizer WCS to evaluate thousands of implementation schedule alternatives to determine the Pareto front of capital projects that maximize return on investment. Return on investment was quantified based on reduction in the number and volume of modelled overflows. The following weightings were included in the prioritization: - Modelled overflows that were correlated with observed SSOs were defined as 'confirmed' and were weighted by a factor of five in the prioritization relative to unconfirmed modelled overflows. If an SSO was reported on more than one occasion, then any modelled overflows corelated to that location were weighted by a factor of ten. This had the effect of the prioritization targeting investment into projects that address confirmed SSOs earlier in the program than unconfirmed modelled overflows. - A non-worsening penalty was applied to avoid the prioritization shifting overflow issues downstream. Any instance where the overflow/freeboard violation becomes worse than the current value a weighting factor of ten was applied. This had the effect of the prioritization ensuring either the downstream system has sufficient capacity prior to an upstream conveyance improvement being implemented, or that conveyance upgrades were balanced with rehabilitation projects to avoid impacting the downstream system. RESULTS Optimization Optimization runs were completed for multiple scenarios to determine the cost savings as each improvement type was implemented. Sensitivity analysis was performed on certain scenarios to assess the impact of new storage facilities and potential investment by the City into a private I/I program. Improved utilization of existing storage facilities requires significant increases to the influent lift stations. Expensive lift station upgrades can be avoided by including new below-grade storage facilities that have gravity inflow and pumped dewatering to avoid large influent lift station sizes. The cost savings that may be achieved by including strategically located new storage facilities is on the order of $175 M (16%). I/I reduction presents a significant opportunity to reduce the overall cost of the master plan by eliminating or reducing the size of projects that are otherwise required. The cost savings associated with the selected public sector I/I rehabilitation program are on the order of $454 M (29%). Prioritization The prioritization results show the sequence of CIP project implementation based on highest return on investment with respect to modeled hydraulic performance. There may be other considerations outside the scope of the cost/hydraulic-based prioritization that influence the sequence of implementation; thus, the results from this analysis are intended to be used as a guide only. Consideration of road surfacing programs, combining relief sewer projects that are in proximity of each other, and allowing for detailed planning and design are factors that should be considered when refining the schedule of improvements. The prioritization results show projects that achieve a relatively high return on investment in Priority 1, 2, and 3 with an 82% improvement in weighted SSO reduction within the first 27% of the total capital expenditure. A 95% improvement in weighted SSO reduction is achieved within 43% of the total capital expenditure by Priority 4 projects. CONCLUSIONS The Tulsa optimization and subsequent prioritization analysis delivered the following outcomes for the City: - Supports the City's Planning efforts to identify the immediate CIP for the next five years due to budgetary constraints. - Minimizes capital and life-cycle costs required to achieve SSO compliance. - Prioritizes the investment schedule to maximize the reduction in overflows at each stage of capital investment. - Enables the City to tackle manageable pieces of the overall solution. - Provides a framework and strategy to assess improvement efforts on a continuous basis.