Deep Reinforcement Learning for DER Cyber-Attack Mitigation

The increasing penetration of DER with smart-inverter functionality is set to transform the electrical distribution network from a passive system, with fixed injection/consumption, to an active network with hundreds of distributed controllers dynamically modulating their operating setpoints as a function of system conditions. This transition is being achieved through standardization of functionality through grid codes and/or international standards. DER, however, are unique in that they are typically neither owned nor operated by distribution utilities and, therefore, represent a new emerging attack vector for cyber-physical attacks. Within this work we consider deep reinforcement learning as a tool to learn the optimal parameters for the control logic of a set of uncompromised DER units to actively mitigate the effects of a cyber-attack on a subset of network DER

The Combined Effect of Photovoltaic and Electric Vehicle Penetration on Conservation Voltage Reduction in Distribution System

Global conditions over the past dozen years have led to an expanded appetite for renewable energy sources: The diminishing fossil fuel supply, the political instability of countries producing these fossil fuels, the ever-more destructive effects of global warming, and the lowering of costs for renewable energy technologies have made countries around the world reconsider their sources of energy. The proliferation of photovoltaic (PV) systems especially has surged dramatically with the decreasing initial costs for installation, and increasing government support in the form of renewable energy portfolios, feed-in-tariffs, tax incentives, etc. Furthermore, electric vehicles (EV) are also becoming widespread due to recent advances in battery and electric drive technologies, and the desperate need to reduce air pollution in urban areas. Meanwhile, electric utilities are always making an effort to run their system more efficiently by encouraging the use of energy-efficient appliances and customer participation in demand-side management programs. In an attempt to further reduce load demand; many utilities regulate the voltage along their distribution feeders in a particular way that is referred to as conservation voltage reduction (CVR). The key principle of CVR operation is that the ANSI standard voltage band between 114 and 126 volts can be compressed via regulation to the lower half (114–120) instead of the upper half (120–126), producing measurable energy savings at low cost and without harm to consumer appliances. As the penetration of distributed PV and EV charging station increases, this can dramatically change the conventional demand profile as PV system act as negative loads during the daylight hours, and EVs significantly increase load demand during charging. Consequently, traditional means of controlling the voltage by capacitor switching and voltage regulators can be improved in this “smart” grid era by adding a fleet of enabling devices including the smart PV inverter functionalities, such as Volt/VAR control, and intelligent EV charging schemes. This thesis explores how better energy conservation is achieved by CVR in a modern distribution system with advanced distributed PV systems inverters and EV loads. Then it summarizes computer simulations that are conducted on the IEEE 37 and IEEE 123 node test feeders using OpenDSS interfaced with MATLAB

Dynamic Analysis of a Microgrid Powered With an Inverter and Machine-Based Distributed Resources

The proliferation of renewable distributed energy resources, particularly photovoltaic (PV) power systems, and the increasing need for a reliable power supply has led to the concept of microgrids, a mini-grid that consists of locally connected power generation units and needs, able to operate connected or disconnected from the utility grid, using controlled and coordinated methods to provide for the users of the microgrid the best possible conditions for their needs. The main technical issues facing microgrids include some of the following, seamless transition from stand-alone to utility grid connected operation, how to preserve frequency and voltage stability, and provide the lowest cost power among numerous power resources. Technologies that will be used in the future smart grid will be built, tested, and fielded in modern microgrids with many national laboratories, utility companies, and universities using microgrids of all different types for research and development. This dissertation describes the design, fabrication, and testing of a microgrid facility which comprises adjustable resistive and inductive loads, a diesel-powered generator (DG), an advanced inverter PV system, a battery energy storage system (BESS), monitoring, protection, and control devices. The microgrid facility was built with the foresight that it would be used for conducting tests and experiments related to microgrid technical challenges, thus ease of access and expandability were built in which allows it to be used for both research and education purposes. Numerous experimental tests conducted include the following: (a) the dynamic response of a DG to load changes, (b) an advanced PV inverters autonomous functions, (c) advanced inverter islanding test, (d) load sharing among the DG and PV system, (e) PV and battery storage systems load sharing, (d) dynamic performance of an advanced PV inverter and a DG during unintentional islanding under different power export/import conditions, and (e) BESS iv response to utility outage under different PV operating conditions. Attempts to improve reliability and power quality are made by expanding the PV inverter ride-through times during frequency and voltage abnormalities. An economic analysis in terms of Net Present Value (NPV) is conducted on a residential application where a BESS is paired with a PV system to shift solar energy in favor Time-of-Use (ToU) pricing and to provide ancillary grid services

Distributed photovoltaic systems: Utility interface issues and their present status. Intermediate/three-phase systems

The interface issues between the intermediate-size Power Conditioning Subsystem (PCS) and the utility are considered. A literature review yielded facts about the status of identified issues

Distributed photovoltaic systems: Utility interface issues and their present status

Major technical issues involving the integration of distributed photovoltaics (PV) into electric utility systems are defined and their impacts are described quantitatively. An extensive literature search, interviews, and analysis yielded information about the work in progress and highlighted problem areas in which additional work and research are needed. The findings from the literature search were used to determine whether satisfactory solutions to the problems exist or whether satisfactory approaches to a solution are underway. It was discovered that very few standards, specifications, or guidelines currently exist that will aid industry in integrating PV into the utility system. Specific areas of concern identified are: (1) protection, (2) stability, (3) system unbalance, (4) voltage regulation and reactive power requirements, (5) harmonics, (6) utility operations, (7) safety, (8) metering, and (9) distribution system planning and design

Advanced Solutions for Renewable Energy Integration into the Grid Addressing Intermittencies, Harmonics and Inertial Response

Numerous countries are trying to reach almost 100\% renewable penetration. Variable renewable energy (VRE), for instance wind and PV, will be the main provider of the future grid. The efforts to decrease the greenhouse gasses are promising on the current remarkable growth of grid connected photovoltaic (PV) capacity. This thesis provides an overview of the presented techniques, standards and grid interface of the PV systems in distribution and transmission level. This thesis reviews the most-adopted grid codes which required by system operators on large-scale grid connected Photovoltaic systems. The adopted topologies of the converters, the control methodologies for active - reactive power, maximum power point tracking (MPPT), as well as their arrangement in solar farms are studied. The unique L(LCL)2 filter is designed, developed and introduced in this thesis. This study will help researchers and industry users to establish their research based on connection requirements and compare between different existing technologies. Another, major aspect of the work is the development of Virtual Inertia Emulator (VIE) in the combination of hybrid energy storage system addressing major challenges with VRE implementations. Operation of a photovoltaic (PV) generating system under intermittent solar radiation is a challenging task. Furthermore, with high-penetration levels of photovoltaic energy sources being integrated into the current electric power grid, the performance of the conventional synchronous generators is being changed and grid inertial response is deteriorating. From an engineering standpoint, additional technical measures by the grid operators will be done to confirm the increasingly strict supply criteria in the new inverter dominated grid conditions. This dissertation proposes a combined virtual inertia emulator (VIE) and a hybrid battery-supercapacitor-based energy storage system . VIE provides a method which is based on power devices (like inverters), which makes a compatible weak grid for integration of renewable generators of electricity. This method makes the power inverters behave more similar to synchronous machines. Consequently, the synchronous machine properties, which have described the attributes of the grid up to now, will remain active, although after integration of renewable energies. Examples of some of these properties are grid and generator interactions in the function of a remote power dispatch, transients reactions, and the electrical outcomes of a rotating bulk mass. The hybrid energy storage system (HESS) is implemented to smooth the short-term power fluctuations and main reserve that allows renewable electricity generators such as PV to be considered very closely like regular rotating power generators. The objective of utilizing the HESS is to add/subtract power to/from the PV output in order to smooth out the high frequency fluctuations of the PV power, which may occur due to shadows of passing cloud on the PV panels. A control system designed and challenged by providing a solution to reduce short-term PV output variability, stabilizing the DC link voltage and avoiding short term shocks to the battery in terms of capacity and ramp rate capability. Not only could the suggested system overcome the slow response of battery system (including dynamics of battery, controller, and converter operation) by redirecting the power surges to the supercapacitor system, but also enhance the inertial response by emulating the kinetic inertia of synchronous generator

Novel Night and Day Control of PV Solar Farm as STATCOM (PV-STATCOM) for Critical Induction Motor Stabilization and FIDVR Alleviation

Induction motors are globally used in several critical operations such as petrochemicals, mining, process control, etc., where their shutdown during faults causes significant financial loss. System faults can also lead to Fault Induced Delayed Voltage Recovery (FIDVR) causing service disruptions. Dynamic reactive power compensators such as SVC and STATCOM are conventionally employed to mitigate these issues, however, these are very expensive. PV solar plants are growing at unprecedented rate globally and are likely to be installed near such critical motors. This thesis presents several novel applications of a patented technology of utilizing PV solar plants, both during night and day, as STATCOM, termed PV-STATCOM, for mitigating above issues at about 50 times lower cost than equivalent-size STATCOMs. A reactive power modulation based PV-STATCOM control is developed to stabilize remotely located motor both during night and day in a realistic distribution feeder, even when reactive power support according to the pioneering German Grid code fails. This control was field demonstrated for first time in Canada (and perhaps in world) on the 10 kW PV solar system in the utility network of Bluewater Power, Sarnia, Ontario. Another novel control strategy based on active and reactive power modulation of PV-STATCOM is developed. MATLAB/PSCAD simulation studies show that the proposed control can stabilize remotely located motor much faster and with reduced real power curtailment than conventional strategies. A new real and reactive power control of PV-STATCOM is proposed to alleviate FIDVR. Electromagnetic Transients simulation studies on a realistic transmission network show that the proposed control on a 100 km remote solar farm can alleviate FIDVR and stabilize a cluster of motors for wide range of system parameters and operating conditions. PV-STATCOM can alleviate the need of local STATCOM for achieving the same objective. Comprehensive sensitivity and stability analysis of single and two distribution level PV-STATCOMs are performed with: i) equivalent and detailed PV-STATCOM model, and ii) PV-STATCOM control implemented at plant level and inverter level. The impact of modeling details, controller location and system parameters on controller interaction, are investigated

Distributed Machine Learning Approach to Fast Frequency Response-based Inertia Estimation in Low Inertia Grids

Recent updates to the IEEE 1547-2018 standard allow active participation of distributed energy resources (DERs) in power grid services with the goal of increased grid reliability and resiliency. With the rapid growth of DERs towards a low inertia converter-dominated grid, the DERs can provide fast frequency response (FFR) services that can quickly counteract the change in system frequency through inertial support. However, in low voltage grids, frequency and voltage face dynamics coupling due to a high resistance to reactance ratio and cannot be controlled separately as in the bulk electric grid. Due to the coupling effect, the control of one parameter also affects the dynamics of the other parameter. A part of this work highlights the role of DERs to provide grid ancillary services underscoring the challenges of combined voltage and frequency control in low voltage grids. Increasing penetration of renewable energy sources (RES) also decreases the power system inertia, there by affecting the stability of bulk grid. The stochastic nature of RES makes the power system inertia a time-varying quantity. Furthermore, converter-dominated grids have different dynamics compared to conventional grids and therefore estimates of the inertia constant using existing dynamic power system models are unsuitable. This work proposes a novel inertia estimation technique based on convolutional neural networks (CNN) that use local frequency measurements. The model uses a non-intrusive excitation signal to perturb the system and measure frequency using a phase-locked loop. The estimated inertia constants, have significant accuracy for the training, validation, and testing sets. Additionally, the proposed approach can be applied over traditional inertia estimation methods that do not incorporate the dynamic impact of renewable energy sources. The frequency response of power systems changes drastically when multi-area power systems with interconnected tie-lines are considered. Furthermore, higher penetration of RES increases the stochasticity in interconnected power systems. Hence, it is important to estimate the multi-area parameters ensuring communication and coordination between each of the areas. A robust and secure client-server-based distributed machine learning framework is used to estimate power system inertia in a two-area system. The proposed approach can be efficiently optimized to increase the training performance. It is important to analyze the performance of a trained machine learning model in a real-world scenario with unknown dynamics. A pre-trained CNN is tested on a system with model predictive controller (MPC)-based virtual inertia (VI) unit. Results show that the frequency and inertial response of conventional synchronous generators-based system differs drastically as compared to the system with non-synchronous generator-based VI support