Preliminary Energy Audit methodology and key performance IWA 5 th - PowerPoint PPT Presentation

IWA 13 th Specialized Conference on Small Water and Wastewater Systems - Athens 2016 Resources-Oriented Sanitation - Athens 2016 Preliminary Energy Audit methodology and key performance IWA 5 th Specialized Conference on indicators (KPIs) in Small Wastewater Treatment Plants B. M. D’Antoni , S. Longo, E. Akkersdijk, L. Stefani, E. Parelli and F. Fatone Supported by the Horizon 2020 Framework Programme of the European Union

INTRODUCTION 1 % of the total electricity consumption per year of a Country. Cao et al., 2011 ENERGY AUDIT and ENERGY BENCHMARKING Parena et al., 2002 Key Performance Indicators (KPIs) Foladori et al., 2010 European Normative lag The main objective of Horizon2020 ENERWATER project is to develop, validate and disseminate an innovative standard methodology for continuously assessing, labelling and improving the overall energy performance of Wastewater Treatment Plants (WWTPs). Materials and Results and Introduction Goals Conclusions Methods discussions 1

GOALS Aims of the Preliminary Methodology  STAGE Treatment classification  Comprehensive key performance indicators (KPIs)  Energy Audit methodology and Energy TOOL  KPIs Energy Benchmarking  Wastewater Treatment Energy Index (WTEI)  Energy LABELLING Aim of this study  To Report the results of the smallest WWTP Materials and Results and Introduction Goals Conclusions Methods discussions 2

ENERWATER METHODOLOGY STAGE CLASSIFICATION In order to disaggregate the energy consumption data, taking into account the different processes and treatment schemes applied in municipal WWTPs, 7 stage were used. Materials and Results and Introduction Goals Conclusions Methods discussions 3

ENERWATER METHODOLOGY KEY PERFORMANCE INDICATORS (KPIs) There is a clear need to establish suitable KPIs within the WWTP that allow a comparable, realistic and universal form of reporting the energy data. STAGE CLASSIFICATION KPIs STAGE 1 kWh/m 3 STAGE 2 kWh/kg TSS removed kWh/kg COD removed , kWh/kgTP removed STAGE 3 kWh/kg TN removed , kWh/kgPEQ removed kWh/kg TSS removed, kWh/kgNH4 removed kWh/kg TN removed , kWh/kgTP removed STAGE 4 kWh/Log reduction STAGE 5 kWh/kg TS processed, kWh produced /kgVS removed STAGE 6 kWh/kgTP removed , kWh/kg TN removed STAGE 7 kWh/kg VOCs removed , kWh/kg VICs removed , kWh/kg VSCs removed , Materials and Results and Introduction Goals Conclusions Methods discussions 4

ENERWATER METHODOLOGY ENERWATER has initially considered the application of Italian Decree 102/2014 which has recently been adopted to audit large WWTPs in Italy. • General data of the WWTP LEVEL A • (Company, Country, Size, Etcc) • Identification of each Energy Carrier LEVEL B • Electricity, Diesel Fuel,Natural gas, Biogas • Identification of Functional Areas: LEVEL C • Main activities, General and Auxiliary Serv. • Identification of each process and equipment LEVEL D whithin the Functional Areas Materials and Results and Introduction Goals Conclusions Methods discussions 5

ENERWATER METHODOLOGY PRELIMINARY METHODOLOGY – INITIAL ASSUMPTIONS AND CONSIDERATIONS 1. The age and the wearing out of the equipment was not taken into account; 2. The nominal power of some devices was not available; 3. Blowers and/or Pumps with inverter can cause big deviation from the real consumption; 4. Some energy consumption data of Auxiliaries and General services was not available; 5. Possible overestimation of the use factor (Ratio between actual and nominal power). 6. All the energy carriers were converted in kWh. Materials and Results and Introduction Goals Conclusions Methods discussions 6

Case Studies and Audit Results ENERGY AUDIT PROCEDURE 2 – Influent and 1 ‐ WWTP Process 3 – Equipment Effluent scheme Inventory characteristics 6 – Calculation of 5 – Calculation of 4 – Application of Energy Performance KPIs in each stage the Energy Tool Index 8 – Identification 7 – Calculation of of Energy Label in W.T.E.I each Stage Materials and Results and Introduction Goals Conclusions Methods discussions 7

Case Studies and Audit Results 50 WWTPs • Italy  15 WWTPs • Spain  15 WWTPs • Germany  20 WWTPs Small or not Small, that is the question THIS STUDY  574 PE ESP_31 20  PE < 10,000  647 m 3 /d Materials and Results and Introduction Goals Conclusions Methods discussions 8

Case Studies and Audit Results EXAMPLE – WWTP ESP_31 1 ‐ WWTP Process scheme STAGE 4 STAGE 1 STAGE 3 2 – Influent and Effluent characteristics STAGE 5 CHARACTERISTICS Influent Effluent Unit 40.21 ± 24.50 5 ± 1.65 [mg/L] BOD 5 106.4 ± 38.43 25.17 ± 5.21 [mg/L] COD 11.43 ± 8.11 4.65 ± 2.07 [mg/L] TN 1.51 ± 0.82 1.21 ± 0.32 [mg/L] TP Materials and Results and Introduction Goals Conclusions Methods discussions 9

Case Studies and Audit Results EXAMPLE – WWTP ESP_31 3 – Equipment 4 – Application of the Energy Tool Inventory Equipment kWh/d % STAGE 1 9% Influent pumping 48.61 13.1% 20% Screening 0.78 0.2% Grit removal 16.76 4.5% 25% Storm water Tank 8.91 2.4% STAGE 3 STAGE 1 Recycling pump 19.57 5.3% STAGE 3 Excess sludge pump 1.18 0.3% STAGE 4 Mechanical aerator 73.71 19.9% Mixer Anaerobic 74.25 20.1% STAGE 5 STAGE 4 UV disinfection 94.24 25.5% STAGE 5 46% Thickener 6.92 1.9% Sludge press 25.13 6.8% TOOL CONSUMPTION CALCULATION [kWh/y] Real Energy Tool Calculation % ERROR ‐ 0.9 % 135,073 136,304 Electric Energy Materials and Results and Introduction Goals Conclusions Methods discussions 10

Case Studies and Audit Results Key Performance Indicators 5 – Calculation of KPIs in each stage ESP_31 STAGE KPI [kWh/m 3 ] 1 0.116 [kWh/KgCOD_rem] 1.17 [kWh/KgTN_rem] 1 15.9 ��� � 1 ��� �� � 100 20 3 � ��� ��� � ��� �� � [kWh/KgTP_rem] 21.73 [kWh/KgPEQ_rem] 0.149 [kWh/KgTS_proc] 5 1.51 Materials and Results and Introduction Goals Conclusions Methods discussions 11

ENERWATER METHODOLOGY 6 – Calculation of Calculation of Energy Performance Index from KPIs Energy Performance How to combine KPIs? How to add apples and oranges? Index ENERGY PERFORMANCE INDEX m 3  0.216 STAGE 1 ESP_31 ��� � �������� PEQ  0.639 STAGE 3 ��� � ��� ��� � �������� TS  0.949 STAGE 5 E % STAGE 1 14% BENCHMARK STAGE 3 70% STAGE 5 11% (EPI_whole) ESP_31 = 0.623 ���� ������ ∗ �% ������ � ��� ������ ∗ �% ������ � ��� ������ ∗ �% ������ � EPI Whole Plant � ��% ������ � �% ������ � �% ������ � Materials and Results and Introduction Goals Conclusions Methods discussions 12

Case Studies and Audit Results Waste Water Treatment Energy Index GUMBEL Distribution_STAGE 3 7 – Calculation of W.T.E.I 3 1.2 GUMBEL DISTRIBUTION The EPIs are RAW DATA 2.5 1 2 0.8 Probability density function PDF Distribution function Prob. density 1.5 0.6 1 0.4 Cumulative distribution function CDF 0.5 0.2 x  EPI 0 0 Regression of Derivative equation 0 0.2 0.4 0.6 0.8 1 1.2 � (Scale parameter) PDF CDF Numerical solution methods � (Location parameter) (maximum likelihood ‐ MLE) Materials and Results and Introduction Goals Conclusions Methods discussions 13

Case Studies and Audit Results Waste Water Treatment Energy Index 7 – Calculation of W.T.E.I HOW TO CALCULATE THE WTEI FROM THE CDF ?  prEN 15217:2005(E) Rr  Energy performance regulation  25 – Percentile of CDF Form the CDF Rs  Building Stock reference  50 – Percentile of CDF ENERGY LABELS A WTEI ≤ 0.5 ��� � 1� ���� � �� (if WTEI < 1) B 0.5 < WTEI ≤ 1 C 1 < WTEI ≤ 1.5 ��� � ��� 2� ���� � 1 � �� ��� (if Rr < CDF i < Rs) D 1.5 < WTEI ≤ 2 E 2 < WTEI ≤ 2.5 F 2.5 < WTEI ≤ 3 ��� � 3� ���� � 1 � �� (if eq.1 is > 1) G 3 < WTEI Materials and Results and Introduction Goals Conclusions Methods discussions 14

Case Studies and Audit Results 8 – Identification of Energy Label in each Stage ESP_31 STAGE WTEI STAGE 1 2.898 STAGE 3 3.457 STAGE 5 3.167 OVERALL 3.340 STAGE Theoretical Decrease 1 ‐ 44% 3 ‐ 50% 5 ‐ 47% Materials and Results and Introduction Goals Conclusions Methods discussions 15

ACTUAL OUTLOOK Power Analyser Tele ‐ controller User Interface Cable Materials and Results and Introduction Goals Conclusions Methods discussions 16

CONCLUSIONS The disaggregation of the KPIs within different treatment stages support to target the energy efficiency actions; The definition of WTEI and energy labels (classes A to G) can support the decisions of the water utilities to best target energy saving actions to less performing WWTPs. The comparison with the Benchmark shows that theoretically the energy consumption in ESP_31 could be reduced by 44% in Stage 1, 50% in Stage 3 and 47% in Stage 5 The real-time measurements are needed for the better reliability of the methodology and related tool; The real removal efficiency is measured by samples analyses before and after each treatment stage.

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