PI-based controller for low-power distributed inverters to maximise reactive current injection while avoiding over voltage during voltage sags

This paper is a postprint of a paper submitted to and accepted for publication in IET Power Electronics and is subject to Institution of Engineering and Technology Copyright. The copy of record is available at the IET Digital Library.In the recently deregulated power system scenario, the growing number of distributed generation sources should be considered as an opportunity to improve stability and power quality along the grid. To make progress in this direction, this work proposes a reactive current injection control scheme for distributed inverters under voltage sags. During the sag, the inverter injects, at least, the minimum amount of reactive current required by the grid code. The flexible reactive power injection ensures that one phase current is maintained at its maximum rated value, providing maximum support to the most faulted phase voltage. In addition, active power curtailment occurs only to satisfy the grid code reactive current requirements. As well as, a voltage control loop is implemented to avoid overvoltage in non-faulty phases, which otherwise would probably occur due to the injection of reactive current into an inductive grid. The controller is proposed for low-power rating distributed inverters where conventional voltage support provided by large power plants is not available. The implementation of the controller provides a low computational burden because conventional PI-based control loops may apply. Selected experimental results are reported in order to validate the effectiveness of the proposed control scheme.Peer ReviewedPostprint (updated version

Techno-Economic Analysis of PV Inverter Based Controllers on Low Voltage Distribution Networks

Voltage-rise due to increasing installation of photovoltaic (PV) systems is a major technical issue in low voltage distribution networks. A cost-effective approach to address the overvoltage problem is to control the active and reactive power provided by the existing PV inverters. Prior research used electro-magnetic transient (EMT) simulation tools to develop inverter control strategies for overvoltage prevention. These type of simulation requires high computational resources and simulation time, and is therefore not suitable for long time period studies (e.g., annual) with many inverters. With the anticipated high penetration of PV, there is a desire for a suitable tool for long time-horizon simulation studies to perform technical and economic analysis. This research work describes the use of quasi-steady-state time-series (QSTS) software (GridLAB-D) to implement inverter overvoltage prevention strategies (formerly developed using EMT simulation), allowing previously infeasible long-term techno-economic analysis of such controllers. A co-simulation framework is used to coordinate the PV inverter controllers implemented in Python on a 12-house low voltage distribution network model developed in GridLAB-D. Three PV inverter controllers are implemented to evaluate the long term technical and economic aspects, including voltage profile analysis, energy generation and consumption, system losses, and transformer loading. Two different pricing structures, real-time pricing (RTP) and flat rate tariff, have been considered in the economic analysis. It is shown that with high penetration of PV and use of effective inverter controllers, the financial benefit to the end-users increases significantly when a net metering policy is used to trade electricity in either tariff scheme. This, however, caused a reduction in the utility electricity sales, and governmental taxes, possibly leading to increased electric rates over time. In addition a 216 house 3 phase distribution feeder is developed in GridLAB-D which can further be used for evaluating different PV inverter controller for large test case system

Voltage Regulation of Low Voltage Distribution Networks

The modern voltage distribution systems consist of distributed generation (DG), like photovoltaics (PV) and wind. These resources are inexhaustible and environmentally friendly. The existing low voltage (LV) distribution networks are typically designed for unidirectional power flow. The integration of DG makes the LV distribution networks prone to difficulties related to voltage, frequency, and power quality. The main challenges in the integration of DG occur due to the intermittent nature of DG. The amount of DG compared with the total generation resource on a power system network is measured as penetration. The system undergoes through reverse power flow when there is a high penetration of DG and low loading conditions in the network. The reverse power flow in the network negatively affects the voltage profile of the LV distribution networks. Thus, voltage regulation is required in LV distribution networks for the integration of DG. Solid State Transformers (SSTs) are power electronic-based transformers that will be a vital component of the future smart grid. The future smart grid will have numerous DG which will require improved controllability to maintain proper coordination between stochastic DG and load. Among its various unique features, the reactive power compensating capabilities of SSTs can be explored in modern distribution systems for voltage regulation under high DG penetrations. SSTs are power electronic devices that show fast and non-linear dynamics which means the simulation models are often complicated and need small time steps for accurate solutions. This prevents real-time and long-term simulation of large distribution systems as the simulations become computationally prohibitive. This work designs a simplified equivalent model of an SST using simple current and voltage sources along with simple modeling equations. These simplified models can be used to perform long-term voltage regulation studies of distribution systems where traditional transformers are replaced with SSTs. Clean energy incentives and the continuous fall in the cost of PV installations have led to a steady growth in residential PV systems. One of the main consequences of higher PV penetration in LV distribution networks is the overvoltage problem. Active power curtailment (APC) of PV inverters has been previously used to curtail the output power of the inverters below its operating point to prevent such overvoltages. However, APC uses a constant droop-based approach to curtail the power, based on the difference between the measured voltage and a critical voltage level. In this thesis, APC is implemented with constant droop and other droop models in a typical LV distribution network in North America, with high PV penetration level. The simulation results show that the system undergoes excessive curtailment resulting in unnecessary energy loss. An adaptive droop-based approach using adaptive dynamic programming (ADP) is proposed as a possible solution to minimize the total energy loss in the system while keeping the system voltage under the critical operating limits. The energy loss due to curtailment decreased by 17.4% after implementing the adaptive-droop based approach using ADP

Towards ‘Smarter’ Systems: Key Cyber-Physical Performance-Cost Tradeoffs in Smart Electric Vehicle Charging with Distributed Generation

The growing penetration of electric vehicles (EV) into the market is driving sharper spikes in consumer power demand. Meanwhile, growing renewable distributed generation (DG) is driving sharper spikes in localised power supply. This leads to growing temporally unsynchronised spikes in generation and consumption, which manifest as localised over- or undervoltage and disrupt grid service quality. Smart Grid solutions can respond to voltage conditions by curtailing charging EVs or available DG through a network of cyber-enabled sensors and actuators. How to optimise efficiency, ensure stable operation, deliver required performance outputs and minimally overhaul existing hardware remains an open research topic. This thesis models key performance-cost tradeoffs relating to Smart EV Charging with DG, including architectural design challenges in the underpinning Information and Communications Technology (ICT). Crucial deployment optimisation balancing various Key Performance Indicators (KPI) is achieved. The contributions are as follows: • Two Smart EV Charging schemes are designed for secondary voltage control in the distribution network. One is optimised for the network operator, the other for consumers/generators. This is used to evaluate resulting performance implications via targeted case study. • To support these schemes, a multi-tier hierarchical distributed ICT architecture is designed that alleviates computation and traffic load from the central controller and achieves user fairness in the network. In this way it is scalable and adaptable to a wide range of network sizes. • Both schemes are modelled under practical latency constraints to derive interlocking effects on various KPIs. Multiple latency-mitigation strategies are designed in each case. • KPIs, including voltage control, peak shaving, user inconvenience, renewable energy input, CO2 emissions and EV & DG capacity are evaluated statistically under 172 days of power readings. This is used to establish key performancecost tradeoffs relevant to multiple invested bodies in the power grid. • Finally, the ICT architecture is modelled for growing network sizes. Quality-of- Service (QoS) provision is studied for various multi-tier hierarchical topologies under increasing number of end devices to gauge performance-cost tradeoffs related to demand-response latency and network deployment

Voltage Management Of Distribution Networks With High Penetration Of Distributed Photovoltaic Generation Sources

Installation of photovoltaic (PV) units could lead to great challenges to the existing electrical systems. Issues such as voltage rise, protection coordination, islanding detection, harmonics, increased or changed short-circuit levels, etc., need to be carefully addressed before we can see a wide adoption of this environmentally friendly technology. Voltage rise or overvoltage issues are of particular importance to be addressed for deploying more PV systems to distribution networks. This dissertation proposes a comprehensive solution to deal with the voltage violations in distribution networks, from controlling PV power outputs and electricity consumption of smart appliances in real time to optimal placement of PVs at the planning stage. The dissertation is composed of three parts: the literature review, the work that has already been done and the future research tasks. An overview on renewable energy generation and its challenges are given in Chapter 1. The overall literature survey, motivation and the scope of study are also outlined in the chapter. Detailed literature reviews are given in the rest of chapters. The overvoltage and undervoltage phenomena in typical distribution networks with integration of PVs are further explained in Chapter 2. Possible approaches for voltage quality control are also discussed in this chapter, followed by the discussion on the importance of the load management for PHEVs and appliances and its benefits to electric utilities and end users. A new real power capping method is presented in Chapter 3 to prevent overvoltage by adaptively setting the power caps for PV inverters in real time. The proposed method can maintain voltage profiles below a pre-set upper limit while maximizing the PV generation and fairly distributing the real power curtailments among all the PV systems in the network. As a result, each of the PV systems in the network has equal opportunity to generate electricity and shares the responsibility of voltage regulation. The method does not require global information and can be implemented either under a centralized supervisory control scheme or in a distributed way via consensus control. Chapter 4 investigates autonomous operation schedules for three types of intelligent appliances (or residential controllable loads) without receiving external signals for cost saving and for assisting the management of possible photovoltaic generation systems installed in the same distribution network. The three types of controllable loads studied in the chapter are electric water heaters, refrigerators deicing loads, and dishwashers, respectively. Chapter 5 investigates the method to mitigate overvoltage issues at the planning stage. A probabilistic method is presented in the chapter to evaluate the overvoltage risk in a distribution network with different PV capacity sizes under different load levels. Kolmogorov–Smirnov test (K–S test) is used to identify the most proper probability distributions for solar irradiance in different months. To increase accuracy, an iterative process is used to obtain the maximum allowable injection of active power from PVs. Conclusion and discussions on future work are given in Chapter 6