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were typically running between 2 a.m. and 8 a.m. on Sundays. Additional deviations from the base load were noted in other days, which corresponded to when transfer pumps were being used to transfer the effluent from the treatment ponds to the percolation ponds or when maintenance activities took place. Once the operation of the plant was understood, a baseline energy model was created that estimated a 24-hour profile of electric demand of the surface aerators, transfer pumps, headwork motors, and miscellaneous loads. The resultant loads were summed up and compared with the utility baseline. Post-Retrofit Energy Analysis Next came an estimate of the energy usage of the WWTP once the proposed retrofit took place. Savings came from two primary sources. First, since the fine bubble diffusers had much higher oxygen transfer efficiency than the surface aerators, the horsepower requirements for the blower motors were greatly reduced from those of the surface aerators. Second, since the VFD speed on the blower motors would be controlled to a dissolved oxygen set point in the treatment ponds, the power draw on the motors could be even further reduced from the peak for which they were designed. Savings were determined using two approaches. The first approach was to calculate the energy (kWh) savings. The hourly profile for the WWTP from the model was binned into the three time-of-use periods for each month. The difference between the baseline energy use and the post-retrofit model use was then calculated using the minimum method to determine the energy savings, ensuring savings are not overestimated for any of the data points. The energy savings for this project were estimated to be 2,593,087 kWh per year or 74.98 percent of the baseline. The second approach was to calculate the demand (kW) savings. Because demand is easily impacted by small variations in flow rates, it is difficult to accurately project the savings that will actually be seen on utility bills from the demand component. For this reason, a conservative approach was used to determine the expected demand savings. The demand savings for this project were estimated to range between 268 kW and 326 kW, depending on the month. This is equivalent to 41.75 percent of the baseline demand values. Post-Retrofit Utility Analysis The final step in the analysis was to determine the financial value of the energy and demand savings from this retrofit. The savings values calculated previously were run through the tariff simulation to determine the expected utility bill after the retrofit took place. The difference between the baseline cost and this calculated cost is the anticipated savings. The dollar savings for this project were estimated to be $240,129 per year or 65.4 percent of the baseline costs. A financial analysis for this project was done to show how quickly this retrofit would pay for itself in utility bill savings. The city wanted to have a project that would pay for itself within the life of the equipment being installed — an average of 15 to 20 years. The final project cost for this retrofit was $3.9 million, which gave a simple payback of 16.5 years. The procurement method used by the city to complete this work was an energy savings performance contract (ESPC). In an ESPC, the customer will typically take out a loan to pay for the project. They will contract with an energy services company (ESCO), who will be paid for the implementation of the work, and, in turn, will guarantee that the customer will see the savings that were estimated on their utility bills. If savings are not achieved as promised, the ESCO will be liable to write the customer a check for the difference. Riverbank chose this procurement methodology because they did not have the up-front funds to pay for the plant upgrade. Additionally, they wanted the fixed-price contract that comes with an ESPC and the guarantee of utility savings, so they could be sure to have the funds available to pay off the loan. Conclusion The project with the City of Riverbank and Schneider Electric has proved to be a successful partnership whereby the city received an upgraded WWTP, which resulted in a significantly reduced electric utility bill. In order to support the financial analysis and guarantee associated with this project, a detailed and innovative approach to estimating energy savings was developed. While not every WWTP will have the same magnitude of opportunity as this one, it is a great example of how a city can mitigate risk, upgrade its plant, become more efficient, and utilize utility savings to pay for it. It also shows how energy efficiency gains can be achieved without a reduction in the quality of operations. n 28 wateronline.com n Water Innovations GREENTECHNOLOGIES Ben Johnson is an energy engineering manager for Schneider Electric's Energy and Sustainability Services group. He's been with the company for 10 years and has worked as an energy analyst, project development manager, and energy team lead. He is a Professional Engineer, Certified Energy Manager, Project Management Professional, and LEED AP. He received his Bachelor of Science degree in mechanical engineering from Arizona State University and is currently working on his Master's of Science degree in engineering management at California State University, Long Beach. He can be reached at ben.johnson@schneider-electric.com. About The Author Surface aerator in operation