Abstract

Energy conservation is a concern in many industries, and consequently, facility operators are turning to various efficiency measures or alternative power sources to reduce electricity costs. With the expanding use of intermittent resources, energy storage systems (ESSs) and demand side management (DSM) options are also gaining interest to maximize potential energy savings. Here, we study the potential of ESSs versus DSM for water utilities through a case study of the National Energy Laboratory of the Hawaii Authority (NELHA). NELHA is a multizone water utility in which most of its electricity usage is dedicated to pumping water. In this study, the optimization of the overall electricity charges for NELHA, using both ESSs or DSM via pump load shifting and optimization of pump house output is investigated. An optimization algorithm is created to determine the optimal size of the batteries for installation considering the water demand and energy costs in each zone. An extended approach of considering the characteristics of individual pumps on each pump house in the optimization model is applied to provide insight into the proper optimization framework for dispatching pumps depending on the current zonal load, given pump efficiencies, and maximum flowrates from each pump. The outcome from mathematical models using general quadratic pump efficiency functions and a simplified linear version of pump efficiency is compared to determine the significance of this difference in modeling methodology in estimations and evaluations. Additionally, the effect of increasing solar power on electricity purchased is analyzed. This work will help to establish the role of ESS and DSM in energy savings for water utility industry as well as show what methods should be used for evaluation of the potential of ESS and DSM interventions.

References

1.
Energy Information Administration U
,
2020
, “
U.S. Energy Consumption by Source and Sector.
2.
de La Tour
,
A.
,
Glachant
,
M.
, and
Ménière
,
Y.
,
2013
, “
Predicting the Costs of Photovoltaic Solar Modules in 2020 Using Experience Curve Models
,”
Energy
,
62
, pp.
341
348
.
3.
Department of Energy
,
2021
, “
DOE Releases New Reports Highlighting Record Growth, Declining Costs of Wind Power
,” https://www.energy.gov/articles/doe-releases-new-reports-highlighting-record-growth-declining-costs-windpower, Accessed December 8, 2021.
4.
SEIA
,
2022
,
Solar Industry Research Data | SEIA
, https://www.seia.org/solar-industryresearch-data, Accessed January 2, 2022.
5.
U.S. Energy Information Administration (EIA)
,
2022
,
History of Wind Power – U.S. Energy Information Administration (EIA)
, https://www.eia.gov/energyexplained/wind/history-of-wind-power.php, Accessed January 2, 2022.
6.
Iliopoulos
,
T. G.
,
2021
, “
The Promotion of Renewable Energy Communities in the European Union
,”
Energy Services Fundamentals and Financing
, pp.
37
53
.
7.
Weiss
,
J.
,
Tsuchida
,
B.
,
Chang
,
J.
, and
Chupka
,
M.
,
2015
,
Integrating Renewable Energy into the Electricity Grid Case Studies Showing How System Operators are Maintaining Reliability
.
8.
Hawaii Clean Energy Initiative
,
2014
,
Clean Energy Vision – Hawai‘i State Energy Office (hawaii.gov)
, http://energy.hawaii.gov/testbeds-initiatives/hcei, Accessed March 29, 2021.
9.
Bini
,
M.
,
Capsoni
,
D.
,
Ferrari
,
S.
,
Quartarone
,
E.
, and
Mustarelli
,
P.
,
2015
, “
Rechargeable Lithium Batteries: Key Scientific and Technological Challenges
,”
Rechargeable Lithium Batteries From Fundamentals to Applications
,
Woodhead Publishing
,
Cambridge, UK
, pp.
1
17
.
10.
Das
,
C. K.
,
Bass
,
O.
,
Kothapalli
,
G.
,
Mahmoud
,
T. S.
, and
Habibi
,
D.
,
2018
, “
Overview of Energy Storage Systems in Distribution Networks: Placement, Sizing, Operation, and Power Quality
,”
Renewable Sustainable Energy Rev.
,
91
, pp.
1205
1230
.
11.
IRENA
,
2020
, “
Battery Storage Paves Way for a Renewable-Powered Future
,” /Newsroom/Articles/2020/Mar/Battery-Storage-Paves-Way-for-a-Renewable-Powered-Future.
12.
Byrne
,
R. H.
, and
Silva-Monroy
,
C. A.
,
2012
, “
Estimating the Maximum Potential Revenue for Grid Connected Electricity Storage: Arbitrage and Regulation
,” Sand2012-3863, p.
64
.
13.
Nguyen
,
T. A.
, and
Byrne
,
R. H.
,
2017
, “
Maximizing the Cost-Savings for Time-of-Use and Net-Metering Customers Using Behind-the-Meter Energy Storage Systems
,”
2017 North American Power Symposium (NAPS)
,
Morgantown, WV
,
Sept. 17–19
.
14.
Nguyen
,
T. A.
,
Byrne
,
R. H.
,
Concepcion
,
R. J.
, and
Gyuk
,
I.
,
2018
, “
Maximizing Revenue From Electrical Energy Storage in MISO Energy and Frequency Regulation Markets
,”
2017 IEEE Power & Energy Society General Meeting
,
Chicago, IL
,
July 16–20
, pp.
1
5
.
15.
Byrne
,
R. H.
,
Concepcion
,
R. J.
, and
Silva-Monroy
,
C. A.
,
2016
, “
Estimating Potential Revenue From Electrical Energy Storage in PJM
,”
2016 IEEE Power and Energy Society General Meeting (PESGM)
,
Boston, MA
,
July 17–21
.
16.
Eyer
,
J.
, and
Corey
,
G.
,
2010
,
Energy Storage for the Electricity Grid: Benefits and Market Potential Assessment Guide
.
17.
Uddin
,
M.
,
Romlie
,
M. F.
,
Abdullah
,
M. F.
,
Abd Halim
,
S.
,
Abu Bakar
,
A. H.
, and
Chia Kwang
,
T.
,
2018
, “
A Review on Peak Load Shaving Strategies
,”
Renewable Sustainable Energy Rev.
,
82
, pp.
3323
3332
.
18.
Loughran
,
David S.
, and
Kulick
,
Jonathan
,
2004
, “
Demand-Side Management and Energy Efficiency in the United States
,”
The Energy J.
,
25
(
1
), pp.
19
43
.
19.
Rivers
,
N.
,
Jaccard
,
M.
, and
JSTOR
,
2011
, “
Electric Utility Demand Side Management in Canada
,”
The Energy Journal
,
32
(
4
), pp.
93
116
.
20.
Sallam
,
A.
, and
Malik
,
O.
,
2018
, “
Demand-Side Management and Energy Efficiency
,”
Electric Distribution Systems
,
2nd ed., John Wiley and Sons Inc.
,
Hoboken, NJ
, pp.
429
463
.
21.
Logenthiran
,
T.
,
Srinivasan
,
D.
, and
Vanessa
,
K. W. M.
,
2014
, “
Demand Side Management of Smart Grid: Load Shifting and Incentives
,”
J. Renewable Sustainable Energy
,
6
(
3
), p.
033136
.
22.
Walker
,
A.
,
2006
, “
Exploring the Limits of Demand Side Management
.”
23.
Trovato
,
V.
, and
Kantharaj
,
B.
,
2020
, “
Energy Storage Behind-the-Meter With Renewable Generators: Techno-Economic Value of Optimal Imbalance Management
,”
Int. J. Electr. Power Energy Syst.
,
118
, p.
105813
.
24.
Prasatsap
,
U.
,
Kiravittaya
,
S.
, and
Polprasert
,
J.
,
2017
, “
Determination of Optimal Energy Storage System for Peak Shaving to Reduce Electricity Cost in a University
,”
2017 International Conference on Alternative Energy in Developing Countries and Emerging Economies
,
Bangkok, Thailand
,
May 25‐26
.
25.
Morsali
,
R.
,
Thirunavukkarasu
,
G. S.
,
Seyedmahmoudian
,
M.
,
Stojcevski
,
A.
, and
Kowalczyk
,
R.
,
2020
, “
A Relaxed Constrained Decentralised Demand Side Management System of a Community-Based Residential Microgrid With Realistic Appliance Models
,”
Appl. Energy
,
277
, p.
115626
.
26.
U.S. Energy Information Administration (EIA)
,
2019
,
Demand-Side Management Programs Save Energy and Reduce Peak Demand—Today in Energy
, https://www.eia.gov/todayinenergy/detail.php?id=38872, Accessed March 28, 2021.
27.
Conteh
,
A.
,
Lotfy
,
M. E.
,
Kipngetich
,
K. M.
,
Senjyu
,
T.
,
Mandal
,
P.
, and
Chakraborty
,
S.
,
2019
, “
An Economic Analysis of Demand Side Management Considering Interruptible Load and Renewable Energy Integration: A Case Study of Freetown Sierra Leone
,”
Sustainability
,
11
(
10
), pp.
1
19
.
28.
Sobhani
,
S. O.
,
Sheykhha
,
S.
,
Azimi
,
M. R.
, and
Madlener
,
R.
,
2019
, “
Two-Level Distributed Demand-Side Management Using the Smart Energy Hub Concept
,”
Energy Procedia
,
158
, pp.
3052
3063
.
29.
Manoharan
,
Y.
,
Headley
,
A.
,
Olson
,
K.
,
Sombardier
,
L.
, and
Schenkman
,
B.
,
2021
, “
Energy Storage Versus Demand Side Management for Peak-Demand Reduction at the Hawaii Ocean Science and Technology Park
,”
ASME 2021 15th International Conference on Energy Sustainability
,
Virtual Event
,
June 16–18
.
30.
Young
,
R.
,
2015
, “
A Survey of Energy Use in Water Companies
.”
31.
Headley
,
A.
,
Randolf
,
G.
,
Virji
,
M.
, and
Ewan
,
M.
,
2020
, “
Valuation and Cost Reduction of Behind-the-Meter Hydrogen Production in Hawaii
,”
MRS Energy Sustainability
,
7
, p.
26
.
32.
Hart
,
W. E.
,
Laird
,
C. D.
,
Watson
,
J.-P.
,
Woodruff
,
D. L.
,
Hackebeil
,
G. A.
,
Nicholson
,
B. L.
, and
Siirola John
,
D.
,
2017
,
Pyomo—Optimization Modeling in Python
, Vol.
67
,
Springer International Publishing
,
Cham
, pp.
122
126
.
33.
Gurobi Optimizer Reference Manual
,
2020
,
Gurobi Optimization, LLC
.
34.
Rose
,
D. M.
,
Schenkman
,
B.
, and
Borneo
,
D.
,
2013
, “
Test Report : Milspray Scorpion Energy Storage Device
.”
35.
Rose
,
D. M.
,
Schenkman
,
B.
, and
Borneo
,
D.
,
2013
, “
Test Report : Raytheon/KTech RK30 Energy Storage System
.”
36.
Headley
,
A. J.
,
Schenkman
,
B. L.
, and
Rosewater
,
D. M.
,
2020
, “
Discrete Logic Vs Optimized Dispatch for Energy Storage in a Microgrid
,”
2020 IEEE Power and Energy Society General Meeting (PESGM)
,
Virtual Event
,
Aug. 2–6
.
37.
Rose
,
D. M.
,
Schenkman
,
B.
, and
Borneo
,
D.
,
2013
, “
Sandia Report Test Report : GS Battery, EPC Power HES RESCU
.”
38.
Mongird
,
K.
,
Viswanathan
,
V.
,
Alam
,
J.
,
Vartanian
,
C.
,
Sprenkle
,
V.
, and
Baxter
,
R.
,
2020
, “
Grid Energy Storage Technology Cost and Performance Assessment 2020
.”
You do not currently have access to this content.