Probabilistic Security-Constrained Preventive Control under Forecast Uncertainties Including Volt/Var Constraints

Emanuele Ciapessoni, Diego Cirio, Francesco Conte, Andrea Pitto (), Stefano Massucco and Matteo Saviozzi
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Emanuele Ciapessoni: Ricerca sul Sistema Energetico-RSE S.p.A., 20134 Milano, Italy
Diego Cirio: Ricerca sul Sistema Energetico-RSE S.p.A., 20134 Milano, Italy
Francesco Conte: Faculty of Engineering, Campus Bio-Medico University of Rome, 00128 Roma, Italy
Andrea Pitto: Ricerca sul Sistema Energetico-RSE S.p.A., 20134 Milano, Italy
Stefano Massucco: Polytechnic School, University of Genova, 16145 Genova, Italy
Matteo Saviozzi: Polytechnic School, University of Genova, 16145 Genova, Italy

Energies, 2023, vol. 16, issue 4, 1-26

Abstract: The continuous increase in generation from renewable energy sources, marked by correlated forecast uncertainties, requires specific methodologies to support power system operators in security management. This paper proposes a probabilistic preventive control to ensure N-1 security in presence of correlated uncertainties of renewable sources and loads. By adopting a decoupled linear formulation of the AC load flow equations, the preventive control is decomposed into two subsequent linear programming problems, the former concerning the active power and the latter the voltage/reactive power-related issues. In particular, in the active control problem, the algorithm combines Third Order Polynomial Normal Transformation, Point Estimate Method, and Cornish–Fisher expansion to model the forecast uncertainties and characterize the chance constraints in the problem. The goal is to find the optimal phase shifting transformer tap setting, conventional generation redispatching, and renewable curtailment at the minimum cost to assure the probabilistic fulfillment of N and N-1 security constraints on branch active power flows. The second stage solves another linear programming problem, which aims to minimize the adjustments to generators’ set-point voltages to avoid violations at node voltages and branch-rated limits due to reactive power flows while meeting generator reactive power constraints. Simulations performed on an IEEE test system demonstrate the effectiveness of the proposed security control method in limiting the probability of violating security limits in N and N-1 state, including voltage/reactive power constraints, in presence of correlated uncertainties.

Keywords: probability; stochastic optimization; renewable energy sources; security; uncertainty (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
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