Uncertainty-Aware Incentive-Based Three-Level Flexibility Coordination for Distribution Networks

Omar Alrumayh; Abdulaziz Almutairi

doi:10.3390/electronics15071503

journal article Open Access Apr 03, 2026

Uncertainty-Aware Incentive-Based Three-Level Flexibility Coordination for Distribution Networks

Omar Alrumayh

Abdulaziz Almutairi

Electronics Vol. 15 No. 7 pp. 1503 · MDPI AG

View at Publisher Save 10.3390/electronics15071503

Abstract

The rapid growth of distributed energy resources (DERs) is transforming distribution networks and increasing the need for coordinated flexibility management to maintain secure and economically efficient operation. In this work, we examine how uncertainty in load demand and photovoltaic (PV) generation affects incentive-based flexibility coordination within a hierarchical three-level framework. The proposed architecture integrates household energy management systems (HEMSs), an aggregator responsible for incentive allocation, and a distribution system operator (DSO) model based on AC optimal power flow. To account for demand and PV variability, a Γ-budget-robust optimization approach is adopted. Also, an incentive–penalty mechanism is introduced to allocate compensation according to each prosumer’s actual flexibility contribution while promoting economic fairness. The entire framework is implemented in PYOMO and tested on the IEEE 33-bus distribution system. A comparative evaluation between deterministic and uncertainty-aware cases is conducted to quantify the cost of robustness and to analyze its influence on flexibility participation, incentive distribution, household net cost, and voltage regulation performance. The results indicate that uncertainty can lead to deviations from initially scheduled flexibility commitments, thereby triggering penalty signals during re-optimization and strengthening contractual compliance. Although the robust formulation results in a moderate increase in operational cost, it substantially improves voltage compliance and overall system reliability. Overall, the findings highlight the importance of explicitly incorporating uncertainty in multi-level flexibility coordination to ensure both technical consistency and practical enforceability in modern distribution networks.

Topics

No keywords indexed for this article. Browse by subject →

References

41

[1]

McKenna "Residential Load Modeling of Price-Based Demand Response for Network Impact Studies" IEEE Trans. Smart Grid (2016) 10.1109/tsg.2015.2437451

[2]

Olsen "Optimal penetration of home energy management systems in distribution networks considering transformer aging" IEEE Trans. Smart Grid (2016) 10.1109/tsg.2016.2630714

[3]

Multi-Level Energy Management Systems Toward a Smarter Grid: A Review

Sadam Hussain, Claude Ziad El-Bayeh, Chunyan Lai et al.

IEEE Access 2021 10.1109/access.2021.3078082

[4]

Sun, K., Sarker, M.R., and Ortega-Vazquez, M.A. (2015, January 26–30). Statistical characterization of electric vehicle charging in different locations of the grid. Proceedings of the IEEE Power and Energy Society General Meeting, Denver, CO, USA. 10.1109/pesgm.2015.7285794

[5]

Liu "Two-stage optimal scheduling of electric vehicle charging based on transactive control" IEEE Trans. Smart Grid (2018) 10.1109/tsg.2018.2815593

[6]

Liu "Transactive real-time electric vehicle charging management for commercial buildings with PV on-site generation" IEEE Trans. Smart Grid (2018) 10.1109/tsg.2018.2871171

[7]

Logenthiran "Demand side management in smart grid using heuristic optimization" IEEE Trans. Smart Grid (2012) 10.1109/tsg.2012.2195686

[8]

Guo "Decentralized coordination of energy utilization for residential households in the smart grid" IEEE Trans. Smart Grid (2013) 10.1109/tsg.2013.2268581

[9]

Parsibenehkohal "A multi-stage framework for coordinated scheduling of networked microgrids in active distribution systems with hydrogen refueling and charging stations" Int. J. Hydrogen Energy (2024) 10.1016/j.ijhydene.2024.05.364

[10]

Hussain, S., Menon, R.P., Amara, F., Lai, C., and Eicker, U. (2024, January 15–18). Optimization of Energy Systems using MILP and RC Modeling: A Real Case Study in Canada. Proceedings of the 2024 IEEE International Systems Conference (SysCon), Montreal, QC, Canada. 10.1109/syscon61195.2024.10553577

[11]

Yu "Assessing the performance of uncertainty-aware transactive controls for building thermal energy storage systems" Appl. Energy (2021) 10.1016/j.apenergy.2020.116103

[12]

Yoon "Optimal retail pricing for demand response of HVAC systems in commercial buildings considering distribution network voltages" IEEE Trans. Smart Grid (2018) 10.1109/tsg.2018.2883701

[13]

Ma "Two-stage optimization model for day-ahead scheduling of electricity-heat microgrids with solid electric thermal storage considering heat flexibility" J. Energy Storage (2024) 10.1016/j.est.2024.112329

[14]

Lezama "Flexibility management model of home appliances to support DSO requests in smart grids" Sustain. Cities Soc. (2020) 10.1016/j.scs.2020.102048

[15]

Oikonomou "Optimal coordination of water distribution energy flexibility with power systems operation" IEEE Trans. Smart Grid (2018) 10.1109/tsg.2018.2824308

[16]

Hao "Optimal coordination of building loads and energy storage for power grid and end user services" IEEE Trans. Smart Grid (2017) 10.1109/tsg.2017.2655083

[17]

Yao "Residential demand side management under high penetration of rooftop photovoltaic units" IEEE Trans. Smart Grid (2015) 10.1109/tsg.2015.2472523

[18]

Huang "Real-time congestion management in distribution networks by flexible demand swap" IEEE Trans. Smart Grid (2017) 10.1109/tsg.2017.2655085

[19]

Gottwalt "Modeling and valuation of residential demand flexibility for renewable energy integration" IEEE Trans. Smart Grid (2016) 10.1109/tsg.2016.2529424

[20]

Rastegar "Developing a two-level framework for residential energy management" IEEE Trans. Smart Grid (2018)

[21]

Alrumayh "Flexibility of Residential Loads for Demand Response Provisions in Smart Grid" IEEE Trans. Smart Grid (2019) 10.1109/tsg.2019.2901191

[22]

Sarker "Optimal coordination and scheduling of demand response via monetary incentives" IEEE Trans. Smart Grid (2014) 10.1109/tsg.2014.2375067

[23]

Hussain "Novel incentive-based multi-level framework for flexibility provision in smart grids" IEEE Trans. Smart Grid (2023) 10.1109/tsg.2023.3302520

[24]

Wong "Autonomous demand-side management based on game-theoretic energy consumption scheduling for the future smart grid" IEEE Trans. Smart Grid (2010) 10.1109/tsg.2010.2089069

[25]

Alharbi "Incentive design for flexibility provisions from residential energy hubs in smart grid" IEEE Trans. Smart Grid (2021) 10.1109/tsg.2021.3049291

[26]

Hu "A framework of residential demand aggregation with financial incentives" IEEE Trans. Smart Grid (2016) 10.1109/tsg.2016.2631083

[27]

Papaioannou "MAS-DR: An ML-Based Aggregation and Segmentation Framework for Residential Consumption Users to Assist Demand Response Programs" Energy Build. (2022)

[28]

Michalakopoulos "A machine learning-based framework for clustering residential electricity load profiles to enhance demand response programs" Appl. Energy (2024) 10.1016/j.apenergy.2024.122943

[29]

Aussel "A trilevel model for best response in energy demand-side management" Eur. J. Oper. Res. (2020) 10.1016/j.ejor.2019.03.005

[30]

Li "Coordination between smart distribution networks and multi-microgrids considering demand side management: A trilevel framework" Omega (2021) 10.1016/j.omega.2020.102326

[31]

Wang "Distributed coordinative transaction of a community integrated energy system based on a tri-level game model" Appl. Energy (2021) 10.1016/j.apenergy.2021.116972

[32]

Hussain "Multi-stage optimization for energy management and trading for smart homes considering operational constraints of a distribution network" Energy Build. (2023) 10.1016/j.enbuild.2023.113722

[33]

Hussain "New coordination framework for smart home peer-to-peer trading to reduce impact on distribution transformer" Energy (2023) 10.1016/j.energy.2023.129297

[34]

Mak "Optimization framework for coordinated operation of home energy management system and Volt-VAR optimization in unbalanced active distribution networks considering uncertainties" Appl. Energy (2020) 10.1016/j.apenergy.2020.115495

[35]

Hussain "Integrating Device-Level Flexibility in Home Energy Management Systems for Prosumers" IEEE Access (2025) 10.1109/access.2025.3606499

[36]

Network reconfiguration in distribution systems for loss reduction and load balancing

M.E. Baran, F.F. Wu

IEEE Transactions on Power Delivery 1989 10.1109/61.25627

[37]

Gazafroudi "Hierarchical approach for coordinating energy and flexibility trading in local energy markets" Appl. Energy (2021) 10.1016/j.apenergy.2021.117575

[38]

Soares "Demand response implementation in smart households" Energy Build. (2017) 10.1016/j.enbuild.2017.03.020

[39]

Paterakis "Optimal household appliances scheduling under day-ahead pricing and load-shaping demand response strategies" IEEE Trans. Ind. Inform. (2015) 10.1109/tii.2015.2438534

[40]

Hart "Pyomo: Modeling and solving mathematical programs in Python" Math. Program. Comput. (2011) 10.1007/s12532-011-0026-8

[41]

Wu "Stochastic control of smart home energy management with plug-in electric vehicle battery energy storage and photovoltaic array" J. Power Sources (2016) 10.1016/j.jpowsour.2016.09.157

Metrics

0

Citations

41

References

Details

Published: Apr 03, 2026
Vol/Issue: 15(7)
Pages: 1503
License: View

Authors

O

Omar Alrumayh

Department of Electrical Engineering, College of Engineering, Qassim University, Buraydah 52571, Saudi Arabia

A

Abdulaziz Almutairi

Department of Electrical Engineering, College of Engineering, Majmaah University, Almajmaah 11952, Saudi Arabia

Funding

Qassim University Award: QU-APC-2026

Majmaah University Award: R-2026-134

Cite This Article

Omar Alrumayh, Abdulaziz Almutairi (2026). Uncertainty-Aware Incentive-Based Three-Level Flexibility Coordination for Distribution Networks. Electronics, 15(7), 1503. https://doi.org/10.3390/electronics15071503

Uncertainty-Aware Incentive-Based Three-Level Flexibility Coordination for Distribution Networks

You May Also Like