Climate change is one of the most pivotal issues for the world in which we live today.
The power grid transformation to become, smarter sustainable and carbon-free,
has been a primary emphasis in recent times. This includes the integration of Distributed
Energy Sources (DERs). In this work, innovative and novel techniques are
presented to facilitate and expedite the engineering, planning, and deployment of
high penetration levels of renewable and distributed energy resources to aggressively
attack climate change and move the industry to a new paradigm. Towards this end,
both traditional and non-traditional techniques and methodologies are leveraged to
enhance distribution planning methods such that more electric distribution feeders
can be analyzed more dynamically. Tried and true iterative mathematical techniques
and convergence algorithms are used to adhere to the Laws of Physics for the flow of
electricity.
Findings in the area of Control Theory and System Identification are used to develop
dynamic and predictive models of the electric distribution system that analyze
the impact of interconnecting high levels of renewable generation. These predictive
models are represented by parametric models or transfer functions developed from the
Laplace Transform technique, leveraging proven powerful tools of time-domain and
frequency domain analysis to evaluate system stability. Critical to this work is both
the validation of realized models wherein these models can accurately predict system
response at varying load levels, renewable energy penetration levels, all-around necessary
sensitivities. Such a dynamic model development process can be used and
applied to any electric distribution feeder to better optimize penetration levels and
provide the planning engineer with smart models to optimize system planning.