Solar+ Optimizer: A Model Predictive Control Optimization Platform for Grid Responsive Building Microgrids

Anand Krishnan Prakash,Richard Brown,Kun Zhang,Peter Alstone,Pranav Gupta,Gabe Fierro,Marco Pritoni,David Blum,Marc Marshall,James Zoellick

doi:10.3390/en13123093

Abstract

With the falling costs of solar arrays and battery storage and reduced reliability of the grid due to natural disasters, small-scale local generation and storage resources are beginning to proliferate. However, very few software options exist for integrated control of building loads, batteries and other distributed energy resources. The available software solutions on the market can force customers to adopt one particular ecosystem of products, thus limiting consumer choice, and are often incapable of operating independently of the grid during blackouts. In this paper, we present the “Solar+ Optimizer” (SPO), a control platform that provides demand flexibility, resiliency and reduced utility bills, built using open-source software. SPO employs Model Predictive Control (MPC) to produce real time optimal control strategies for the building loads and the distributed energy resources on site. SPO is designed to be vendor-agnostic, protocol-independent and resilient to loss of wide-area network connectivity. The software was evaluated in a real convenience store in northern California with on-site solar generation, battery storage and control of HVAC and commercial refrigeration loads. Preliminary tests showed price responsiveness of the building and cost savings of more than 10% in energy costs alone.

Highlights

The United States electrical grids face a range of new challenges to safe and reliable operation: aging infrastructure, increased penetration of less predictable renewable generators to mitigate climate change and the increasing occurrence of extreme weather events all place stress on the grid [1].To address these issues, more decentralized grid architectures have been proposed [2] based on distributed energy resources (DERs) and microgrids [3,4,5]
The performance of the software platform called “Solar+ Optimizer” (SPO) solution in a real commercial building is evaluated. It begins with the description of the site where SPO has been deployed, the hardware and software details, followed by the specifications of the optimization engine and concludes with the results of how SPO controls the building’s loads and its distributed energy resources in response to different grid signals
The SPO has been deployed in a convenience store/gas station in Blue Lake, California, United

Summary

Introduction

The United States electrical grids face a range of new challenges to safe and reliable operation: aging infrastructure, increased penetration of less predictable renewable generators to mitigate climate change and the increasing occurrence of extreme weather events all place stress on the grid [1]. To address these issues, more decentralized grid architectures have been proposed [2] based on distributed energy resources (DERs) and microgrids [3,4,5]. Microgrid software typically focuses on site protection and battery control and does not coordinate with control of building systems, especially

Methods

Results

Discussion

Conclusion