Abstract
The traditional security-constrained optimal power flow (SCOPF) model under the classical N-1 criterion is implemented in the power industry to ensure the secure operation of a power system. However, with increasing uncertainties from renewable energy sources (RES) and loads, the existing SCOPF model has difficulty meeting the practical requirements of the industry. This paper proposed a novel chance-constrained preventive SCOPF model that considers the uncertainty of power injections, including RES and load, and contingency probability. The chance constraint is used to constrain the overall line flow within the limits with high probabilistic guarantees and to significantly reduce the constraint scales. The cumulant and Johnson systems were combined to accurately approximate the cumulative distribution functions, which is important in solving chance-constrained optimization problems. The simulation results show that the model proposed in this paper can achieve better performance than traditional SCOPF.
Highlights
The growth in renewable energy sources (RES) and charging loads in recent years, such as wind power, photovoltaics and electric vehicle, has brought considerable economic benefits; the uncertainty of power injections has increased, which leads to increased operational risks [1,2,3], especially for highly-loaded power systems
This paper proposes a novel chance-constrained preventive security-constrained optimal power flow (SCOPF) model (CC-PSCOPF) that is an improvement on the traditional preventive SCOPF (PSCOPF) model
Using PSCOPF, pre-contingency controls are the only measures allowed to ensure that the system always operates in a state where any single component outage does not lead to constraint violations
Summary
The growth in renewable energy sources (RES) and charging loads in recent years, such as wind power, photovoltaics and electric vehicle, has brought considerable economic benefits; the uncertainty of power injections has increased, which leads to increased operational risks [1,2,3], especially for highly-loaded power systems. Optimal power flow (OPF) is the fundamental dispatch and planning tool that is used to minimize operational costs while ensuring the security of the normal state, and security-constrained optimal power flow (SCOPF) [4,5,6,7] is an extended form of OPF that considers the classical N-1 criterion. With the emergence of uncertainties in the power system, several drawbacks of traditional SCOPF have become apparent and these need to be addressed. 2. Traditional SCOPF disregards the probability of a contingency occurring; in other words, it considers the occurrence probability to be 1 for every contingency in a contingency set [4]. This means that for a large power system where a large number of contingencies are considered, the calculation burden is high, and directly solving a SCOPF problem in a short time is quite challenging
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