Probabilistic optimal power flow in islanded microgrids with load, wind and solar uncertainties including intermittent generation spatial correlation

J. Jithendranath, Debapriya Das and Josep M. Guerrero

Energy, 2021, vol. 222, issue C

Abstract: Increased investiture towards Distribution Generation (DG) in recent past had prompted for transmutation of existing networks to form microgrids that can operate autonomously or in conjunction with main-grid. In particular, the augmenting zeal for renewable DGs is thriving at recent times; but non-dispatchability and uncertain nature pose specific challenges, which is the primary concern in this work. This paper employs Point Estimate Method (PEM) for handling uncertainties to solve the probabilistic-optimal power flow problem (POPF) with multiple objectives formulated in an islanded microgrid with droop coordinated DGs including uncertainties involved in load, wind and solar PV with suitable probability distributions. The devised POPF problem is proposed to solve for optimal droop parameters by multi-objective ant-lion optimization algorithm; tested and verified on modified 33-bus system. Furthermore, in actuality, spatial correlations among renewables play vital role in devising operational schedule for energy management strategies. This paper deals with PEM compounded with Nataf Transformation for POPF to handle spatial correlations in renewable generations. The dominance of wind correlation over solar PV correlations in POPF problem is highlighted. The robustness of proposed approach is verified with benchmark Monte Carlo Simulation (MCS) to affirm about its accuracy for suitable replacement of proposed approach to MCS.

Keywords: Distribution generation (DG); Photovoltaic (PV); Islanded microgrid (IMG); Probabilistic optimal power flow (P-OPF); Point estimate method (PEM); Nataf transformation (NT); Multi-objective ant lion optimization (MALO); Monte Carlo simulations (MCS) (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (14)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:222:y:2021:i:c:s0360544221000967

DOI: 10.1016/j.energy.2021.119847

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