Market-Efficient and Robust Integration of DER in Unbalanced Distribution Systems

Abstract

Uptake of distributed energy resources (DER) is accelerating across the globe. There is growing need for coordination frameworks to ensure high volumes of DER can participate effectively in existing market structures at the transmission-scale, while also satisfying technical constraints at the distribution-scale. Dynamic operating envelopes (DOE) have emerged as the leading approach in Australia for enabling effective integration of DER into power systems.

Calculating dynamic operating envelopes in a manner that enables effective DER participation while providing robust guarantees of network-feasible outcomes is a complex computational task. Sources of complexity include non-linear and non-convex formulations of power flow and network operational constraints, the uncertainty of DER dispatch within envelopes due to their flexibility, and the balancing of various objectives (including efficient system operation, maximising assigned flexible capacity and ensuring fair outcomes) arising from the multitude of actors whose interests may not align. As the technical readiness level of dynamic operating envelope frameworks approach wide-spread deployment in industry, there are several aspects to their design which warrant further consideration by the research community. In this thesis we delve into three aspects.

We first develop an operating envelope optimisation framework that maximises the market efficiency of expected wholesale market outcomes, as opposed to existing methods that maximise total import and export capacity or metrics of fairness. Our proposed formulation incorporates projections of wholesale market prices in energy and reserve markets, constituting a novel form of TSO-DSO coordination in envelope calculation. Our objective function maximises expectations of producer and consumer surplus as defined in microeconomics, effectively prioritising the expected value-generating potential of DER, across a range of potential market price outcomes. As a result, our framework navigates a trade-off between allocating capacity to efficient bidders and maximising total allocated capacity as a function of evolving TSO needs. We employ a stochastic programming formulation to handle price uncertainty, demonstrating robust performance even during periods of significant price volatility.

Our second contribution addresses feasibility considerations in unbalanced three-phase networks by proposing a completion of voltage constraints. We develop a linearised proxy for voltage unbalance factor by applying first-order Taylor series expansion to the Line Voltage Unbalance Rate (LVUR) with linearised phase angle recovery. This approach enables efficient large-scale calculations despite introducing conservatism due to the LVUR approximation and the need to ensure constraint satisfaction under improbable dispatch scenarios.

Our final contribution mitigates the conservatism of robust DOE approaches through aggregator coordination. Rather than calculating independent operating envelopes, we develop an approach to partition high-dimensional representations of unused network capacity amongst aggregators using robust polytopic projection. This framework provides aggregators with scalar functions to calculate DER-level envelopes as a function of feeder-scale dispatch outcomes. Results show this approach can significantly increase the aggregate flexible allocations of import and export capacity compared to an alternative robust DOE approach in literature. This is achieved by steering aggregators away from dispatch outcomes that would cause significant levels of voltage unbalance in the network, thereby mitigating the risk of constraint violations caused or exacerbated by phase couplings through mutual impedance.

The methods developed in this thesis provide new avenues for distribution system operators to enhance the effectiveness of DER integration, including into wholesale markets, while ensuring safe operation of distribution networks. Show more