There is a growing interest in utilizing energy storage for various cost-saving measures for behind-the-meter (BTM) customers.&nbsp; Typical BTM applications of energy storage include energy arbitrage for time-of-use pricing customers and peak demand shaving for large scale customers that are subjected to large charges for their maximum monthly peak demand.&nbsp; Energy storage systems can do this by shifting electrical loads from high-cost to low-cost times of day or by reducing peak demands by discharging during high demand periods and charging during low demand periods.&nbsp; Particularly peak demand shaving can have a major impact on electricity charges for customers that are subjected to severe monthly $/kW pricing, making the upfront cost of an energy storage installation worthwhile.&nbsp;Demand side management can also provide similar functionality often with a significantly lower upfront cost.&nbsp; By shifting demand, either by automation or manually increasing and reducing energy usage, electrical loads can be smoothed to reduce peak demand charges similarly.&nbsp; However, often demand can only be varied within a small window, limiting the effectiveness of such a strategy, even with extensive automation to optimize the system.&nbsp; As such, there is a natural tradeoff between expense, ease of use, and effectiveness that must be addressed when seeking to understand the potential value of an energy storage project versus demand side management improvements.This tradeoff is highlighted at the Hawaii Ocean Science and Technology (HOST) park of the Natural Energy Laboratory of Hawaii Authority’s (NELHA) on The Island of Hawai’i.&nbsp; The main driver of energy consumption at the HOST park is pumping demand from the large surface water and deep-sea water wells installed at the park.&nbsp; The water pumped from these wells is used for a myriad of applications from providing suitable living environments for aquaculture projects to cooling for the buildings’ air-conditioning units.&nbsp; NELHA’s demand is broken into two major load centers that each house a large pump station to provide the bulk of the water needs in their respective areas.&nbsp; An extensive piping network has been installed over the years that allows to shift water demand from one area to the other.&nbsp; In theory, this network could be optimized to smooth the electrical demand in each area to reduce peak demand charges, but there are several associated complexities that make it very difficult to determine an optimal strategy.&nbsp;The areas use pumps with differences in performance, have different solar generation resources and potential, have different customers and demand profiles, and further are subjected to different energy and peak demand charges under by the local utility.&nbsp; Transmission upgrades are being considered to connect the areas and thereby share electrical loads between the areas in addition to seawater loads, but the cost to install underground electrical lines in the volcanic rock is prohibitive.&nbsp;Here we explore the potential benefits of utilizing energy storage in each area to act as virtual transmission to minimize the overall cost of operations to NELHA and avoid the installation of a costly underground transmission line.&nbsp; This case study is at the interface of BTM (peak demand shaving) and front-of-the-meter (demand side management and transmission deferral) concerns, and as such, provides an opportunity to investigate the application of energy storage for large scale customers.&nbsp; The scenario is modeled as a mixed-integer-linear-program in Python using Pyomo to optimize the dispatch of an energy storage system and the pump stations in each area to minimize the total energy costs for NELHA.&nbsp; The pump stations’ performance is modeled using piecewise linear representation to capture the effect of increasing load in one area to supply the other.&nbsp; Results with and without the inclusion of an energy storage system are compared to determine the relative value of automating the pump dispatch alone and the potential benefit of using energy storage systems in each area as well.&nbsp;

Energy Storage Versus Demand Side Management for Peak-Demand Reduction at the Hawaii Ocean Science and Technology Park

Paper Proceedings: https://asmedigitalcollection.asme.org/ES/ES2021/volume/84881

ASME 2021 Energy Sustainability (ES2021)

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