15 research outputs found
Efficient Dynamic Compressor Optimization in Natural Gas Transmission Systems
The growing reliance of electric power systems on gas-fired generation to
balance intermittent sources of renewable energy has increased the variation
and volume of flows through natural gas transmission pipelines. Adapting
pipeline operations to maintain efficiency and security under these new
conditions requires optimization methods that account for transients and that
can quickly compute solutions in reaction to generator re-dispatch. This paper
presents an efficient scheme to minimize compression costs under dynamic
conditions where deliveries to customers are described by time-dependent mass
flow. The optimization scheme relies on a compact representation of gas flow
physics, a trapezoidal discretization in time and space, and a two-stage
approach to minimize energy costs and maximize smoothness. The resulting
large-scale nonlinear programs are solved using a modern interior-point method.
The proposed optimization scheme is validated against an integration of dynamic
equations with adaptive time-stepping, as well as a recently proposed
state-of-the-art optimal control method. The comparison shows that the
solutions are feasible for the continuous problem and also practical from an
operational standpoint. The results also indicate that our scheme provides at
least an order of magnitude reduction in computation time relative to the
state-of-the-art and scales to large gas transmission networks with more than
6000 kilometers of total pipeline
Optimizing Service Restoration in Distribution Systems with Uncertain Repair Time and Demand
This paper proposes a novel method to co-optimize distribution system
operation and repair crew routing for outage restoration after extreme weather
events. A two-stage stochastic mixed integer linear program is developed. The
first stage is to dispatch the repair crews to the damaged components. The
second stage is distribution system restoration using distributed generators,
and reconfiguration. We consider demand uncertainty in terms of a truncated
normal forecast error distribution, and model the uncertainty of the repair
time using a lognormal distribution. A new decomposition approach, combined
with the Progressive Hedging algorithm, is developed for solving large-scale
outage management problems in an effective and timely manner. The proposed
method is validated on modified IEEE 34- and 8500-bus distribution test
systems.Comment: Under review in IEEE Transactions on Power System
Using historical utility outage data to compute overall transmission grid resilience
Given increasing risk from climate-induced natural hazards, there is growing interest in the development of methods that can quantitatively measure resilience in power systems. This work quantifies resilience in electric power transmission networks in a new and comprehensive way that can represent the multiple processes of resilience. A novel aspect of this approach is the use of empirical data to develop the probability distributions that drive the model. This paper demonstrates the approach by measuring the impact of one potential improvement to a power system. Specifically, we measure the impact of additional distributed generation on power system resilience