Content area
Full Text
Abstract
Distributed energy resources (DERs) have the potential to lower energy costs and increase energy resilience. However, they complicate the current energy system and can negatively affect a utility 's cost and reliability. Existing frameworks for modeling DER integration are complicated and lack clear insights. One approach to simplify the DER integration problem would be to use a decomposition technique. Decomposition techniques simplify models, make them easier to solve and provide clear and useful insights. Decomposing DER integration into a model with disjoint utility and community problems creates a clear, efficient, and decipherable model. In this study, I use a decomposition framework to investigate the benefits of DERs and their effects on utilities. My results show that DERs lower the overall cost of electricity, lower utility demand which forces utilities to raise prices, and that communities overcome intermittency by using the utility as backup power.
Keywords
Distributed, Energy Systems, Optimization, Decomposition
1.Introduction
Distributed energy resources (DERs) complicate and provide benefits to our current energy system. DERs can produce electricity at various levels of the energy system, making them difficult to manage. Because DERs can be implemented closer to the demand, they are more flexible, responsive, and resilient. Determining if DERs can be cost effective and then integrating them into the energy system is paramount.
One group of algorithms that could help solve these types of problems are decomposition techniques. Decomposition techniques break large complicated problems into smaller parts that are easier to decipher and solve. They operate under the premise that some problems are so large or complex that they can be solved in pieces faster than they could be solved together. This idea is useful when new complicating paradigms are added to an existing system making the new system much harder to manage.
An energy system model, that incorporates DERs, can decompose into utility and community models. The utility model must invest in enough generation capacity to meet demand and the community models must report their hourly demand to the utility. The utility model needs the demand data from the communities to optimize its investments and provide a price and the community models need the price to decide how much of their own generation capacity they want to invest in. However, if the...
