Regularized MIP Model for Optimal Power Flow with Energy Storage Systems and its Applications
arxiv(2024)
摘要
Incorporating energy storage systems (ESS) into power systems has been
studied in many recent works, where binary variables are often introduced to
model the complementary nature of battery charging and discharging. A
conventional approach for these ESS optimization problems is to relax binary
variables and convert the problem into a linear program. However, such linear
programming relaxation models can yield unrealistic fractional solutions, such
as simultaneous charging and discharging. In this paper, we develop a
regularized Mixed-Integer Programming (MIP) model for the ESS optimal power
flow (OPF) problem. We prove that under mild conditions, the proposed
regularized model admits a zero integrality gap with its linear programming
relaxation; hence, it can be solved efficiently. By studying the properties of
the regularized MIP model, we show that its optimal solution is also
near-optimal to the original ESS OPF problem, thereby providing a valid and
tight upper bound for the ESS OPF problem. The use of the regularized MIP model
allows us to solve two intractable problems: a two-stage stochastic ESS OPF
problem and a trilevel network contingency problem.
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