title: A Heuristic Approach to Operations and Control of BTM-DERS for Bill Management and Grid Services
Creators: name: Shaon, Md Arshad Rashid
Publisher: name: University of Nevada, Las Vegas
publisherIdentifier: https://ror.org/0406gha72
publisherIdentifierScheme: ROR
Year: 2024

description: Behind-The-Meter (BTM) distributed energy resources (DERs) have emerged as a critical and transformative force within the energy sector. These decentralized energy assets, which include solar  photovoltaic  (PV)  systems,  battery  energy  storage  systems  (BESS),  and  thermostatically controlled loads (TCLs), are increasingly essential for empowering customers by granting them greater  control  over  their  energy  production  and  consumption,  thereby  reducing  reliance  on centralized power sources. Additionally, they have the potential to play a pivotal role in enhancing grid resilience by providing grid services. This study investigates the management of customer electricity bills and grid services through the integration of various BTM-DERs, particularly solar photovoltaic  (PV)  systems,  BESS,  air  conditioning  systems  with  smart  thermostats,  and  grid-interactive water heaters, under variable electricity rate. A heuristic optimization approach that leverages the coordinated operation and control of these DERs to minimize customer electricity costs and improve grid services is proposed. Recognizing the potential barrier of high upfront costs for  residential  customers,  this  research  explores  Energy-Storage-as-a-Service  (ESaaS)  as  an alternative to individual BTM-BESSS ownership. Similar to community energy storage (CES), ESaaS provides virtual energy storage through a centralized system located in front of the meter, enabling  customers  to  lease  storage  capacity.  By  effectively  harnessing  photovoltaic  power generation,  optimizing  battery  charging  and  discharging  cycles,  and  strategically  scheduling thermostat  settings  for  controllable  loads,  this  approach  aims  to  achieve  a  balance  between maximizing cost savings for customers and enhancing overall grid efficiency and reliability. This work presents practical mathematical models for rooftop photovoltaic (PV) systems, battery storage, air conditioners, and electric water heaters. Day-ahead forecasting techniques were then employed to predict customer generation and consumption profiles, which are crucial for planning DER  control  strategies.  Local  weather  forecasts  from  the  National  Oceanic  and Atmospheric Administration  (NOAA)  and  customer  smart-meter  data  were  utilized  as  inputs  for  these predictions. The study addresses two key factors by formulating optimization functions subject to various constraints: Customer Bill Management (CBM) which aims to minimize the customer's electricity  bill  under  time-of-use  electricity  pricing  which  coincides  with  system  Peak  Load Management (PLM) as a grid service. To validate the effectiveness of the proposed approach, a case study is presented based on a local residential customer's smart-meter data and appliance power consumption. Customer’s annual electricity bill is evaluated under both flat rate and time-of-use pricing after leasing an ESaaS block are presented to support the efficacy of the proposed approach.