Julio H. Braslavsky’s research while affiliated with Division of Energy, The Commonwealth Scientific and Industrial Research Organisation and other places

Demand response is a concept that has been around since the very first electric power systems. However, we have seen an explosion of research on demand response and demand-side technologies in the past 30 years, coinciding with the shift towards liberalized/deregulated electricity markets and efforts to decarbonize the power sector. Now we are also seeing a shift towards more distributed/decentralized electric systems; we have entered the era of "distributed energy resources," which require new grid management, operational, and control strategies. Given this paradigm shift, we argue that the concept of demand response needs to be revisited, and more carefully/consistently defined to enable us to better utilize this massive resource for economic, technical, environmental, and societal aims. In this paper, we survey existing demand response definitions, highlight their shortcomings, propose a new definition, and describe how this new definition enables us to more effectively harness the value of demand response in modern power systems. We conclude with a demand response research agenda informed by a discussion of demand response barriers and enablers.

Dynamic operating envelopes (DOEs), as a key enabler to facilitate distributed energy resource (DER) integration, have attracted increasing attention in the past years. However, uncertainties, which may come from load forecasting errors or inaccurate network parameters, have been rarely discussed in DOE calculation, leading to compromised quality of the hosting capacity allocation strategy. This letter studies how to calculate DOEs that are immune to such uncertainties based on a linearised unbalanced three-phase optimal power flow (UTOPF) model. With uncertain parameters constrained by norm balls, formulations for calculating robust DOEs (RDOEs) are presented along with discussions on their tractability. Two cases, including a 2-bus illustrative network and a representative Australian network, are tested to demonstrate the effectiveness and efficiency of the proposed approach.

Dynamic operating envelopes (DOEs) have been introduced to integrate distributed energy resources (DER) in distribution networks via real-time management of network capacity limits. Recent research demonstrates that uncertainties in DOE calculations should be carefully considered to ensure network integrity while minimising curtailment of consumer DERs. This letter proposes a novel approach to calculating DOEs that is robust against uncertainties in the utilisation of allocated capacity limits and demonstrates that the reported solution can attain close to global optimality performance compared with existing approaches.

The rapid expansion of consumer distributed energy resources (DERs) such as solar photo-voltaic generation in low-voltage distribution grids in Australia presents new challenges to network operation, such as voltage imbalances and over-voltage issues. To manage large numbers of DERs Distributed Network Service Providers (DNSPs) are adopting dynamic operating envelopes (DOEs), which specify a time-varying permissible capacity range for DER operation within the network operational constraints. However, the computation of these DOEs is complex and existing algorithms for calculating DOEs require high levels of network visibility that can be expensive to acquire at the large-scales of typical distribution grids. To overcome these difficulties, this paper investigates in comparative numerical simulation studies a power flow based decentralised algorithm that adapts the additive increase multiplicative decrease (AIMD) congestion control algorithm used in transmission control protocols to calculate DOEs distinctly for each partition of the network. The proposed algorithm presents several appealing features, including guaranteed voltage violation avoidance, fast calculation of localised DOEs, practical scalability for large networks, and increased total power export to the network.

The increasing levels of distributed photovoltaic (PV) generation in Australia have introduced new challenges in the operation of power systems, especially in Low Voltage (LV) distribution networks. One of these challenges is caused by Minimum Operational Demand (MOD). As operational demand decreases at times of high PV generation, maintaining system operation within its technical limits becomes more difficult and may require removing some controllable generation from the network, with the consequent reduction of system resilience. To maintain MOD, network operators can resort to emergency shedding of generation on the distribution network by (i) switching off controllable PV inverters using a demand response functionality mandatory for new inverters, and by (ii) forcing disconnection of legacy inverters by triggering their overvoltage protections through a temporary increase of voltage setpoints at zone substation transformers. However, while the emergency generation shedding (EGS) capability has been proven effective in supporting the power grid to ride through a critically low demand period, the steep increase in voltage setpoint results in observable power swings which could lead to stability risks. This work conducts a simulation study on a typical Australian LV network model to investigate voltage and power oscillations triggered by EGS and sensitivities to various parameters and scenarios through dynamical nonlinear power flow equations numerically simulated using Matlab MATPOWER. The main focus of the study is on legacy inverters prevalent in many Australian networks, but a comparison with inverters using voltage support functions is also included to assess the effectivity of EGS more broadly.

Dynamic operating envelopes (DOEs) have been introduced to enable the integration of distributed energy resources (DER) in electricity distribution networks via real-time management of network capacity limits. Recent research demonstrates that uncertainties in the calculation of DOEs should be carefully considered to ensure network integrity while minimising curtailment of consumer DERs. This letter proposes a novel approach to calculating DOEs that is robust against uncertainties in the utilisation of allocated capacity limits and demonstrates that the reported solution can attain close to global optimality performance as compared with existing approaches.