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The number of residential consumers with solar PV and batteries, aka prosumers, has been increasing in recent years. Incentives now exist for prosumers to operate their batteries in more profitable ways than self-consumption mode. However, this can increase prosumer exports or imports, resulting in power flows that can lead to voltage and thermal limit violations in distribution networks. This work proposes a framework for Distribution Network Operators (DNOs) to ensure the integrity of MV-LV networks by using dynamic operating limits for prosumers. Periodically, individual prosumers send their intended operation (net exports/imports) as determined by their local control to the DNO who then assesses network integrity using smart meter data and a power flow engine. If a potential violation is detected, their maximum operating limits are determined based on a three-phase optimal power flow that incorporates network constraints and fairness aspects. A real Australian MV feeder with realistically modelled LV networks and 4,500+ households is studied, where prosumers’ local controls operate based on energy prices. Time-series results demonstrate that the proposed framework can help DNOs ensure network integrity and fairness across prosumers. Furthermore, it unlocks larger profitability for prosumers compared with the use the 5kW fixed export limit adopted in Australia.

In the context of active distribution networks, AC Optimal Power Flow (OPF) has shown great potential to calculate setpoints for controllable devices. Although considerable literature exists, temporal aspects that may affect the actual execution of these setpoints are rarely investigated. Due to the diverse operating characteristics of controllable devices (i.e., delays, ramp rates and deadbands), when these setpoints are executed by multiple devices without adequate considerations, the resulting outcome can differ drastically from what is expected; leading to violations of network constraints and excessive control actions. Therefore, this work proposes a series of necessary adaptations within the controllers of existing devices as well as in the OPF formulation to cater for the diversity in operating characteristics, ensuring that calculated setpoints are adequately implemented by controllable devices. This involves the direct control of conventional devices and enforcing a new ramping behavior for inverter-interfaced devices. Furthermore, a linear, mixed-integer formulation is proposed to handle discrete devices and improve scalability in large networks. Co-simulation results (using a U.K. test network with the objective of maximizing renewable energy production and considering 1s time-step) demonstrate that, by catering for the operating characteristics of controllable devices, the expected outcome from OPF-based setpoints can be achieved.

Active power curtailment of residential PV systems is an effective way to mitigate technical issues in distribution networks. However, existing curtailment schemes can treat households unfairly; e.g., Volt-Watt schemes increasingly being adopted worldwide inherently penalize PV systems at remote locations in radial feeders. Nonetheless, whether fairness is improved or not by alternative curtailment schemes depends on how the impacts on households are considered. In this context, household-centric metrics that quantify PV harvesting, energy export and financial benefit are used along with the Jain's fairness index to assess fairness from different perspectives. To explore the trade-offs brought by schemes that consider fairness differently, four linearized, three-phase Optimal Power Flow (OPF)-based schemes are proposed to determine, periodically, short-term curtailment settings. Using a real Australian 22kV feeder and realistically modelled LV networks with 4,500+ households, a detailed comparison is carried out considering also a Volt-Watt scheme. Results demonstrate tha tall the schemes that consider fairness are effective in removing locational penalizations. However, in terms of fairness, their performance across the adopted metrics reveals noticeable trade-offs. This highlights the need for decision-makers to determine the metric from which fairness can be based upon in a way that aligns with their respective policies.

Made available in DSpace on 2018-12-11T17:33:13Z (GMT). No. of bitstreams: 0 Previous issue date: 2018-09-01 Smart grid schemes in which multiple network elements and participants are managed for the benefit of the distribution network (e.g., energy loss reduction, restoration, etc.) require sophisticated algorithms to control them in the most suitable manner while catering for network constraints. Such a complex decision making process can be solved by tailoring the ac optimal power flow (OPF) problem to the corresponding smart grid scheme. Non-linear programming ac OPF formulations, however, can suffer from scalability and robustness issues which in turn might limit their adoption. Here, a novel quadratic programming formulation is proposed and compared against the non-linear, quadratically constrained, and linearized approaches. Two cases are carried out to assess their performance: 1) management of distributed generation units to maximize renewable energy harvesting (continuous control variables) and 2) control of capacitors to minimize energy losses (discrete control variables). The results demonstrate that the proposed quadratic approach significantly outperforms the more conventional formulations in both computational efficiency and robustness. This makes it a suitable alternative to be at the heart of the decision making of complex, real-time schemes to be adopted by future smart distribution networks. Universidade Estadual Paulista UNESP Department of Electrical and Electronic Engineering University of Melbourne School of Electrical and Electronic Engineering University of Manchester Faculdade de Engenharia de Ilha Solteira Universidade Estadual Paulista UNESP Universidade Estadual Paulista UNESP Faculdade de Engenharia de Ilha Solteira Universidade Estadual Paulista UNESP