[Paper Review] Network-Constrained Transactive Control for Multi- Microgrids-based Distribution Networks with SOPs

Xiaodong Yang, Zehao Song+6 more|arXiv (Cornell University)|Nov 6, 2020

Microgrid Control and Optimization32 references4 citations

TL;DR

This paper proposes a network-constrained transactive control (NTC) framework for multi-microgrid distribution networks that jointly optimizes economic efficiency and system security by integrating a transactive energy market with soft open point (SOP)-based power flow regulation. The method uses a dynamic two-timescale model and reformulates bilevel games into single-level mixed-integer second-order cone programs via KKT conditions and relaxation, significantly improving computational efficiency while effectively mitigating uncertainties and enhancing voltage profile and cost savings under varying prediction errors.

ABSTRACT

Different from most transactive control studies only focusing on economic aspect, this paper develops a novel network-constrained transactive control (NTC) framework that can address both economic and secure issues for a multi-microgrids-based distribution network considering uncertainties. In particular, we innovatively integrate a transactive energy market with the novel power-electronics device (i.e., soft open point) based AC power flow regulation technique to improve economic benefits for individual microgrids and meanwhile ensure the security of the entire distribution network. In this framework, a dynamic two-timescale NTC model consisting of slow-timescale pre-scheduling and real-time scheduling stages is formulated to work against multiple system uncertainties. Moreover, the original bilevel game problems are transformed into single-level mixed-integer second-order cone programming problems through KKT conditions, duality, linearization and relaxation techniques to avoid iterations of transitional methods, so as to improve computational efficiency. Finally, numerical simulations on a modified 33-bus test system with 3 MGs verify the effectiveness of the proposed framework.

Motivation & Objective

• To address the gap in existing transactive control studies that focus only on economic efficiency while neglecting network constraints and system security.
• To develop a holistic framework that coordinates distribution network operators (DNOs) and microgrids (MGs) through price signals while ensuring voltage and line flow security.
• To integrate soft open points (SOPs) as a control mechanism for active power flow regulation in distribution networks with high renewable penetration.
• To formulate a two-timescale transactive control model that handles uncertainties in renewable generation and load demand.
• To improve computational efficiency by transforming complex bilevel games into single-level mixed-integer second-order cone programs using KKT conditions and relaxation techniques.

Proposed method

• Develops a dynamic two-timescale NTC model with slow-timescale pre-scheduling and real-time scheduling to manage system uncertainties.
• Integrates a transactive energy market with SOP-based active power flow control to balance economic and technical objectives.
• Applies KKT conditions, duality theory, and relaxation techniques to convert bilevel optimization problems into single-level mixed-integer second-order cone programs (MISOCP).
• Uses SOPs as flexible, controllable power electronics devices to reshape power flows and maintain voltage stability under uncertain conditions.
• Employs a modified IEEE 33-bus test system with three microgrids to simulate real-world distribution network dynamics and validate the framework.
• Implements a robust optimization approach to handle prediction errors in renewable generation and load, ensuring system resilience.

Experimental results

Research questions

• RQ1 How can transactive control be extended to simultaneously address economic and security constraints in multi-microgrid distribution networks?
• RQ2 What is the impact of integrating SOP-based power flow regulation on voltage profile and system losses in a network-constrained environment?
• RQ3 How does the proposed two-timescale NTC model perform under varying levels of prediction uncertainty in renewable generation and load?
• RQ4 To what extent does the proposed reformulation of bilevel games into single-level MISOCP improve computational efficiency compared to iterative methods?
• RQ5 How does the inclusion of a transactive energy market with SOP control compare to non-market or economy-only control strategies in terms of cost, losses, and voltage violations?

Key findings

• The proposed NTC method reduces voltage deviation by 64.33% and line losses by 152.49% compared to a case without SOPs, demonstrating the critical role of SOPs in enhancing system security.
• Compared to an economy-only transactive control (Case I), the proposed method reduces voltage violations and improves voltage profile despite a slight trade-off in economic cost.
• The two-timescale NTC model effectively mitigates adverse effects of prediction errors, with performance degradation remaining bounded even under high uncertainty levels (e.g., 0.25/0.2/0.15).
• The reformulation of bilevel games into single-level MISOCP via KKT and relaxation techniques avoids iterative solving, significantly improving computational efficiency.
• Case IV (proposed NTC) achieves the lowest overall operational cost and best voltage regulation among all compared cases, including unscheduled and single-layer models.
• The integration of transactive energy pricing with SOP control leads to better distribution of benefits between DNO and MGs compared to fixed-price or drooping market mechanisms.