Risk-Aware Scheduling for Maximizing Renewable Energy Utilization in a Cascade Hydro–PV Complementary System

With the increasing integration of variable renewables, cascade hydro–photovoltaic (PV) systems face growing challenges in scheduling under PV output uncertainty. This paper proposes a risk-aware bi-level scheduling model based on the Information Gap Decision Theory (IGDT) to maximize renewable ener...

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Main Authors: Yan Liu, Xian Zhang, Ziming Ma, Wenshi Ren, Yangming Xiao, Xiao Xu, Youbo Liu, Junyong Liu
Format: Article
Language:English
Published: MDPI AG 2025-06-01
Series:Energies
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Online Access:https://www.mdpi.com/1996-1073/18/12/3109
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author Yan Liu
Xian Zhang
Ziming Ma
Wenshi Ren
Yangming Xiao
Xiao Xu
Youbo Liu
Junyong Liu
author_facet Yan Liu
Xian Zhang
Ziming Ma
Wenshi Ren
Yangming Xiao
Xiao Xu
Youbo Liu
Junyong Liu
author_sort Yan Liu
collection DOAJ
description With the increasing integration of variable renewables, cascade hydro–photovoltaic (PV) systems face growing challenges in scheduling under PV output uncertainty. This paper proposes a risk-aware bi-level scheduling model based on the Information Gap Decision Theory (IGDT) to maximize renewable energy utilization while accommodating different risk preferences. The upper level optimizes the uncertainty horizon based on the decision-maker’s risk attitude (risk-neutral, opportunity-seeking, or risk-averse), while the lower level ensures operational feasibility under corresponding deviations in the PV and hydropower schedule. The bi-level model is reformulated into a single-level mixed-integer linear programming (MILP) problem. A case study based on four hydropower plants and two photovoltaic (PV) clusters in Southwest China demonstrates the effectiveness of the model. Numerical results show that the opportunity-seeking strategy (OS) achieves the highest total generation (68,530.9 MWh) and PV utilization (102.2%), while the risk-averse strategy (RA) improves scheduling robustness, reduces the number of transmission violations from 38 (risk-neutral strategy) to 33, and increases the system reserve margin to 20.1%. Compared to the conditional value-at-risk (CVaR) model, the RA has comparable robustness. The proposed model provides a flexible and practical tool for risk-informed scheduling in multi-energy complementary systems.
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series Energies
spelling doaj-art-d0f6bd9fb55447d2a4884d3c8707c1c32025-08-20T03:27:28ZengMDPI AGEnergies1996-10732025-06-011812310910.3390/en18123109Risk-Aware Scheduling for Maximizing Renewable Energy Utilization in a Cascade Hydro–PV Complementary SystemYan Liu0Xian Zhang1Ziming Ma2Wenshi Ren3Yangming Xiao4Xiao Xu5Youbo Liu6Junyong Liu7School of Electrical Engineering, Sichuan University, Chengdu 610065, ChinaBeijing Power Exchange Center, Beijing 100032, ChinaBeijing Power Exchange Center, Beijing 100032, ChinaState Grid Sichuan Economic Research Institute, Chengdu 610041, ChinaState Grid Sichuan Economic Research Institute, Chengdu 610041, ChinaSchool of Electrical Engineering, Sichuan University, Chengdu 610065, ChinaSchool of Electrical Engineering, Sichuan University, Chengdu 610065, ChinaSchool of Electrical Engineering, Sichuan University, Chengdu 610065, ChinaWith the increasing integration of variable renewables, cascade hydro–photovoltaic (PV) systems face growing challenges in scheduling under PV output uncertainty. This paper proposes a risk-aware bi-level scheduling model based on the Information Gap Decision Theory (IGDT) to maximize renewable energy utilization while accommodating different risk preferences. The upper level optimizes the uncertainty horizon based on the decision-maker’s risk attitude (risk-neutral, opportunity-seeking, or risk-averse), while the lower level ensures operational feasibility under corresponding deviations in the PV and hydropower schedule. The bi-level model is reformulated into a single-level mixed-integer linear programming (MILP) problem. A case study based on four hydropower plants and two photovoltaic (PV) clusters in Southwest China demonstrates the effectiveness of the model. Numerical results show that the opportunity-seeking strategy (OS) achieves the highest total generation (68,530.9 MWh) and PV utilization (102.2%), while the risk-averse strategy (RA) improves scheduling robustness, reduces the number of transmission violations from 38 (risk-neutral strategy) to 33, and increases the system reserve margin to 20.1%. Compared to the conditional value-at-risk (CVaR) model, the RA has comparable robustness. The proposed model provides a flexible and practical tool for risk-informed scheduling in multi-energy complementary systems.https://www.mdpi.com/1996-1073/18/12/3109cascade hydro–photovoltaic hybrid systemrisk-aware schedulinginformation gap decision theoryrenewable energy utilizationforecast uncertainty management
spellingShingle Yan Liu
Xian Zhang
Ziming Ma
Wenshi Ren
Yangming Xiao
Xiao Xu
Youbo Liu
Junyong Liu
Risk-Aware Scheduling for Maximizing Renewable Energy Utilization in a Cascade Hydro–PV Complementary System
Energies
cascade hydro–photovoltaic hybrid system
risk-aware scheduling
information gap decision theory
renewable energy utilization
forecast uncertainty management
title Risk-Aware Scheduling for Maximizing Renewable Energy Utilization in a Cascade Hydro–PV Complementary System
title_full Risk-Aware Scheduling for Maximizing Renewable Energy Utilization in a Cascade Hydro–PV Complementary System
title_fullStr Risk-Aware Scheduling for Maximizing Renewable Energy Utilization in a Cascade Hydro–PV Complementary System
title_full_unstemmed Risk-Aware Scheduling for Maximizing Renewable Energy Utilization in a Cascade Hydro–PV Complementary System
title_short Risk-Aware Scheduling for Maximizing Renewable Energy Utilization in a Cascade Hydro–PV Complementary System
title_sort risk aware scheduling for maximizing renewable energy utilization in a cascade hydro pv complementary system
topic cascade hydro–photovoltaic hybrid system
risk-aware scheduling
information gap decision theory
renewable energy utilization
forecast uncertainty management
url https://www.mdpi.com/1996-1073/18/12/3109
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