TY - JOUR
T1 - Risk-Based Hosting Capacity Analysis in Distribution Systems
AU - Madavan, Avinash N.
AU - Dahlin, Nathan
AU - Bose, Subhonmesh
AU - Tong, Lang
N1 - This work was supported by NSF CAREER under Grant 2048065. The work of Lang Tong was supported by NSF under Grant 1932501.
PY - 2024/1/1
Y1 - 2024/1/1
N2 - Solar hosting capacity analysis (HCA) assesses the ability of a distribution network to host distributed solar generation without seriously violating distribution network constraints. In this paper, we consider risk-sensitive HCA that limits the risk of network constraint violations with a collection of scenarios of solar irradiance and nodal power demands, where risk is modeled via the conditional value at risk (CVaR) measure. First, we consider the question of maximizing aggregate installed solar capacities, subject to risk constraints and solve it as a second-order cone program (SOCP) with a standard conic relaxation of the feasible set of the power flow equations. Second, we design an incremental algorithm to decide whether a configuration of solar installations has acceptable risk of constraint violations, modeled via CVaR. The algorithm circumvents explicit risk computation by incrementally constructing inner and outer polyhedral approximations of the set of acceptable solar installation configurations from prior such tests conducted. Our numerical examples study the impact of risk parameters, the number of scenarios and the scalability of our framework.
AB - Solar hosting capacity analysis (HCA) assesses the ability of a distribution network to host distributed solar generation without seriously violating distribution network constraints. In this paper, we consider risk-sensitive HCA that limits the risk of network constraint violations with a collection of scenarios of solar irradiance and nodal power demands, where risk is modeled via the conditional value at risk (CVaR) measure. First, we consider the question of maximizing aggregate installed solar capacities, subject to risk constraints and solve it as a second-order cone program (SOCP) with a standard conic relaxation of the feasible set of the power flow equations. Second, we design an incremental algorithm to decide whether a configuration of solar installations has acceptable risk of constraint violations, modeled via CVaR. The algorithm circumvents explicit risk computation by incrementally constructing inner and outer polyhedral approximations of the set of acceptable solar installation configurations from prior such tests conducted. Our numerical examples study the impact of risk parameters, the number of scenarios and the scalability of our framework.
KW - Hosting capacity analysis
KW - conditional value at risk
KW - distributed solar
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U2 - 10.1109/TPWRS.2023.3238846
DO - 10.1109/TPWRS.2023.3238846
M3 - Article
AN - SCOPUS:85148446431
SN - 0885-8950
VL - 39
SP - 355
EP - 365
JO - IEEE Transactions on Power Systems
JF - IEEE Transactions on Power Systems
IS - 1
ER -