How an energy planning tool changed decision-making at MSU


How an energy planning tool changed decision-making at MSU

MSU image by Dextera Photography via Compfight cc.

What if you had to identify solutions and implement changes that would result in a 45 percent greenhouse gas (GHG) emissions reduction for your organization by 2020?

What if your goals also included achieving a 20 percent increase in your renewable energy sources by 2020? As a leader aware of your limited financial resources, how would you guide your organization to success?

Generically, these would be difficult questions. But with the specific constraints of 10,000 employees, 580 buildings, 5,200 acres of land, a 100 megawatt power plant that is primarily coal-fired, 48,000 students who use the campus daily, 16,000 permanent residents and sub-optimal annual weather conditions (77 sunny days, average wind of 9 miles per hour and 49 inches of snow), the "what ifs" of this type can seem impossible to address.

At Michigan State University (MSU), the complexity of these constraints provided an opportunity for the institution to look for a tool that would help everyone understand the impact of a decision against a set of key performance indicators, or metrics, that are most important to the university (see next page). Like businesses, colleges and universities have many stakeholders, all of whom have different points of view and opinions about paths towards environmental progress.

MSU was searching for such a tool that could provide everyone the quick ability to see the trade-offs of each environmental scenario, thereby identifying the missed opportunities and efficiencies to be gained.

Developing an integrated energy and planning model, with the help of Confluenc Inc., has impacted university decision-making processes relating to resource allocation and strategic planning. Confluenc provides institutional energy planning distinguished by processes and analytical tools that facilitate complex decision-making.

As universities work to identify the path to their varied sustainability goals, it is clear that there is no silver bullet. Nor is there a right or wrong way to arrive at the destination. In fact, there are an overwhelming number of scenarios by which to travel.

What is important to any university is that all stakeholders have a good understanding of the impact of potential scenarios on the various key performance indicators of the university, which generally fall into the three categories of fiscal, operational and environmental performance. Knowing how a decision will affect these various key performance indicators before the decision is made is critical.

Comparing scenarios and impacts

In the example below, we compared various scenarios. There is the business as usual (BAU), along with example scenarios focused on conservation (blue), expanding electrical grid purchases (red) and fuel switching from coal to natural gas (orange).

The effects of each are seen in the following cost of utility service graph, as an example, and for all other key performance indicators as the dashboard is expanded to other views.  

Key performance metrics

Cost of utility service graph

Click to enlarge graph.

MSU's model allows the development of "what if?" scenarios using data that already exists within the institution and compares these scenarios to various reference cases, including a business-as-usual (BAU) condition. The ability to begin this modeling with existing data sets -- and augmenting only where the value of additional information is clear -- distinguishes this methodology from any others used in the past.

Users can develop and then compare multiple scenarios against a set of fiscal criteria such as debt capacity, capital expenditures (annual and cumulative), utility costs and tuition impact; against operational criteria such as building efficiency, plant efficiency and power capacity; and against environmental criteria such as greenhouse gas emissions, renewable energy utilized, water conservation or other institutional environmental goals. Institutions likely will have unique key performance indicators they want to measure, which can be easily incorporated into the platform and decision environment.

For example, would you be better off with a scenario where you would move off coal to burning only natural gas as a fuel? Would you be better off with a scenario where you implement an aggressive energy conservation program in buildings? Would you be better off with a mix of different types of supply for energy plus adding new renewable energy? The scenarios and combinations are vast and varied.  

The two graphs below show scenarios similar to the questions asked here and how those scenarios perform relative to the BAU reference case (gray line) and MSU's energy transition plant targets for greenhouse gas (GHG) emissions reductions and percent renewable energy. Literally hundreds of scenarios have been developed and compared in this way.

GHG emissions

Click to enlarge graph.

Renewable energy

Click to enlarge graph.


Dashboard decision-making     

The intangible benefits of the technology for MSU emerged during meetings with decision makers and constituents by showcasing and comparing multiple opportunities and scenarios against each other.

Rapid response and visualization of ideas and proposals are easily viewed in the dashboard, which then allows for in-depth discussion by individuals with different perspectives (students; facilities; academics).

When multiple performance indicators are viewed simultaneously by a diverse group of stakeholders, the tradeoffs associated with different scenarios become clear and understood and group insight is established.  

In the dashboard illustrated here, four different indicators are visualized simultaneously: required capital (upper left); cost of utility service (upper right); GHG emissions and transition plan targets (lower left); and percent renewable energy with transition plan targets (lower right).

The drop downs in the ribbon at the top of the dashboard can be used to change the content of any window helping conversations amongst a diverse group quickly visualize information relevant to the discussion at any moment.

Energy tool dashboard

Click to enlarge graph.

In my opinion, this is the most powerful but subtle educational and consensus-building tool I have seen and it has changed the way we make decisions. It has also affected who takes part in the decision-making, which is more inclusive than ever.

It has done something that is very hard to do in higher education: It has changed our decision environment.

MSU image by Dextera Photography via Compfight cc.