Electric motors in commercial and industrial applications account for almost a third of total electric grid load in the United States. With these applications representing such a significant level of energy use, increasing efficiency in these applications can help substantially increase resilience and lower total energy costs. This report examines stationary high-efficiency electric motor technologies and their supply chains.

It was last estimated that in 2020, data centers comprised approximately 2% of total US electricity consumption, with an estimated annual growth rate of 4%. As our country increasingly relies on information technology (IT), our data centers (DCs) will need to increase their energy efficiency (EE) to stabilize their energy consumption. The task of studying EE in DCs is complicated by the interconnected nature of humans and mission-critical technical systems. Moreover, the literature tends to focus on technology solutions such as improvements to IT equipment, cooling infrastructure, and software, without addressing organizational and psychological drivers. Our research demystifies the complex interactions between humans and DCs, by asking What non-technical barriers impede EE investment decision-making and/or implementing energy management strategies? To begin to answer this question, we perform a literature review of 86 resources, ranging from peer-reviewed journal publications to handbooks. We also consider related fields such as organizational behavioral management and energy intensive buildings. We develop a public Zotero library, perform content coding, and complete a rudimentary network analysis. Our findings from the literature review suggest that (1) technological solutions are abundant in the literature but fall short of providing practical guidance on the pitfalls of implementation, (2) making energy efficiency a priority at the executive level of organizations will be largely ineffective if the IT and facilities staff are not directly incentivized to increase EE, and (3) there is minimal current understanding of how the individual psychologies of IT and facilities staff affect EE implementation in DCs. In the next phase of our research, we plan to interview data center operators/experts to ground-truth our literature findings and collaboratively design decarbonization policy solutions that target organizational structure, empower individual staff, and foster a supportive external market.

Utilizing policies and programs which incentivize energy efficiency or on-site renewables is difficult. The challenges and costs associated with researching these policies, interacting with their providers, and ensuring regulatory compliance can be collectively referred to as administrative burden. To better understand the impact of administrative burden on energy efficiency policies, we investigated the administrative burden associated with energy sales arrangements (ESA). ESAs are a contracting vehicle related to energy savings performance contracts where an energy services company designs and constructs a renewable energy system at a federal site, transferring ownership of those generating assets to the site after a 20-year term. We conducted a series of in-depth interviews with a variety of relevant ESA stakeholders, including federal project managers, subject matter experts, and energy service companies. We then augmented these interviews with a review of the relevant literature. This research indicated that the current level of administrative burden decreases the adoption of renewable energy through ESAs by the federal government by raising upfront costs, depressing project attempts due to complexity, and introducing delays and challenges in successfully implemented projects. This chilling effect is especially pronounced in new policy vehicles and with inexperienced implementers. Findings from the specific case of ESAs can be generalized to other types of energy policy including efficiency programs. Policy makers decrease the efficacy of initiatives through increased administrative burden, and these effects will be most pronounced in programs with novel design or targeted at unfamiliar audiences.

It was last estimated in 2016 that data centers (DCs) comprise approximately 2% of total US electricity consumption. However, this estimate is currently being updated to account for the massive increase in computing needs due to streaming, cryptocurrency, and artificial intelligence (AI). To prevent energy consumption that tracks with increasing computing needs, it is imperative we identify energy efficiency strategies and investments beyond the low-hanging fruit solutions. In a two-phased research approach, we ask: What non-technical barriers still impede energy efficiency (EE) practices and investments in the data center sector, and what can be done to overcome these barriers? In particular, we are focused on social and organizational barriers to EE. In Phase I, we performed a literature review and found that technical solutions are abundant in the literature, but fail to address the top-down cultural shifts that need to take place in order to adapt new energy efficiency strategies. In Phase II, reported here, we interviewed 16 data center operators/experts to ground-truth our literature findings. Our interview protocols focus on three aspects of DC decision-making: procurement practices, metrics and monitoring, and perceived barriers to energy efficiency. We find that vendors are the key drivers of procurement decisions, advanced efficiency metrics are facility-specific, and there is convergence in the design of advanced facilities due to the heat density of parallelized infrastructure. Our ultimate goals for our research are to design DC decarbonization policies that target organizational structure, empower individual staff, and foster a supportive external market.