Chance-Constrained Optimal Distribution Network Partitioning to Enhance Power Grid Resilience

Abstract

This paper proposes a method for identifying potential self-adequate sub-networks in the existing power distribution grid. These sub-networks can be equipped with control and protection schemes to form microgrids capable of sustaining local loads during power systems contingencies, thereby mitigating disasters. Towards identifying the best microgrid candidates, this work formulates a chance-constrained optimal distribution network partitioning (ODNP) problem addressing uncertainties in load and distributed energy resources; and presents a solution methodology using the sample average approximation (SAA) technique. Practical constraints like ensuring network radiality and availability of grid-forming generators are considered. Quality of the obtained solution is evaluated by comparison with-a) an upper bound on the probability that the identified microgrids are supply-deficient, and b) a lower bound on the objective value for the true optimization problem. Performance of the ODNP formulation is illustrated through case-studies on a modified IEEE 37-bus feeder. It is shown that the network flexibility is well utilized; the partitioning changes with risk budget; and that the SAA method is able to yield good quality solutions with modest computation cost.

Microgrid Protection Challenges and Mitigation Approaches–A Comprehensive Review

“…Islanding detection helps the smooth and safe transition of the grid-connected operational mode of the microgrid to the islanding mode [91]. Islanding is a state in which the microgrid is detached from the utility grid when any fault occurs on the utility grid side or LOM condition occurs [92].…”

Applications of Probabilistic Forecasting in Smart Grids: A Review

“…Minimizing the costs of buying power from thermal units + Minimizing the costs of buying spinning reserves from generators as well as demand-response resources [125] Renewable generations Chance-constrained programming Microgrid management by minimizing the operation costs of its units + Minimizing the costs of buying power from the upstream grid + Maximizing the revenue obtained from selling electricity to the upstream grid [126] Operational modes of the microgrids Chance-constrained stochastic conic programming Solving multi-site microgrids' investment problem and microgrid dual-mode network operations by minimizing microgrid operation and maintenance costs, microgrid electricity transaction costs, its network loss costs, and microgrid load curtailment costs [128] Renewable generation and loads…”

A Microgrid Formation-Based Restoration Model for Resilient Distribution Systems Using Distributed Energy Resources and Demand Response Programs

“…The model considers exact power flow equations tackled by a mixed-integer linear programming (MILP). In Biswas et al (2021), a chance-constrained optimal distribution network partitioning was proposed for identifying the best candidates for microgrid formation after HR event.…”

“…With the high penetration of DGs, MG formation is an effective operational strategy to restore critical loads as major faults occur in distribution systems. Optimal methods based on heuristic search (Bajpai et al, 2016;Sedzro et al, 2018;Xu et al, 2016;Zadsar et al, 2017) and mathematical programming (Alizadeh et al, 2020;Biswas et al, 2021;Gilani et al, 2020;Momen et al, 2020Momen et al, , 2021Sedzro et al, 2017;Zhu et al, 2020) were used for MG formation problem in the resilient distribution systems. In (Bajpai et al, 2016), a methodology based on the graph-theoretic method and Choquet integral was introduced for MG formation to quantify the distribution system resilience during extreme contingencies.…”