Exposing Barriers to Flexibility Aggregation in Unbalanced Distribution Networks

Abstract

The increasing integration of distributed energy resources (DER) offers new opportunities for distribution system operators (DSO) to improve network operation through flexibility services. To utilise flexible resources, various DER flexibility aggregation methods have been proposed, such as the concept of aggregated P-Q flexibility areas. Yet, many existing studies assume perfect coordination among DER and rely on single-phase power flow analysis, thus overlooking barriers to flexibility aggregation in real unbalanced systems. To quantify the impact of these barriers, this paper proposes a three-phase optimal power flow (OPF) framework for P-Q flexibility assessment, implemented as an open-source Julia tool 3FlexAnalyser.jl. The framework explicitly accounts for voltage unbalance and imperfect coordination among DER in low voltage (LV) distribution networks. Simulations on an illustrative 5-bus system and a real 221-bus LV network in the UK reveal that over 30% of the theoretical aggregated flexibility potential can be lost due to phase unbalance and lack of coordination across phases. These findings highlight the need for improved flexibility aggregation tools applicable to real unbalanced distribution networks.

Figures (10)

• Figure 1: Literature review mapping. Columns represent the two research directions most relevant to this work. Representative studies are located according to their contributions to these directions and are arranged chronologically, with more recent publications displayed at the bottom. Each study is visualised by a circle with the corresponding reference number.
• Figure 2: Conceptual step-by-step illustration of the interval-based OPF algorithm for constructing an aggregated P-Q flexibility area: (a) the initial operating point with no flexibility is calculated; (b) the bounds of the area are obtained by calculating Q minimum and maximum, points 1 and 2, and P minimum and maximum, points 3 and 4; (c) these limits are discretised into intervals – 10 Q intervals in this example; (d) the first Q interval is considered by constraining the Q component of the aggregated flexibility, the corresponding P limits (boundary points 5 and 6) are calculated; (e) after evaluating all intervals, the final area is estimated as the hull of all boundary points. The algorithm is executed separately for each phase. The P and Q axes in this figure are schematic and do not correspond to specific numerical values. In real calculations for distribution networks, these axes can be expressed in kW and kVAr or in per-unit values.
• Figure 3: Flowchart of the proposed framework. Flexibility services from DER are estimated for each phase using the concept of P-Q flexibility areas. Then, the impact of phase unbalance and DER coordination is quantified by introducing corresponding constraints, resulting in reduced flexibility areas.
• Figure 4: Case study: illustrative 5-bus system with four loads and one flexible unit. Each load can consume different power across the phases, thus creating phase unbalance. The flexible unit is assumed to produce a balanced output (to simulate a three-phase flexible device) or an unbalanced output (to simulate three independent flexibility providers connected to different phases).
• Figure 5: Analysis of the load unbalance impact on flexibility services provided by the three-phase balanced flexible unit in the 5-bus system. The services are characterised by the aggregated network flexibility area in the P-Q space at the primary substation. The cross markers correspond to the initial operating point (with no flexibility provision), while the coordinates represent the total network’s power consumption.