An Adaptive Distributed Averaging Integral Control Scheme for Micro-Grids with Renewable Intermittency and Varying Operating Cost

The increasing penetration of intermittent renewable energy resources in micro-grids poses several issues, such as stochastic power generation, demand and supply miss-match, frequency fluctuation, and economic dispatch problems. To address such critical issues, a distributed secondary control scheme based for micro-grids with varying operating cost and intermittent renewable energy resources is proposed for frequency regulation and economic load dispatch. The paper presents an adaptive distributed averaging integral control scheme with conditional uncertainties, namely varying operating costs, and renewable intermittency. The proposed control scheme adapts to the uncertainties by updating the control law parameters dynamically and can maintain overall network stability. The distributed control scheme employs communication channels for exchange of generation data from the neighboring power units for optimal power sharing and consensus among the power units. An additional controller at tertiary control layer of the hierarchical control architecture is also augmented in the control structure to economically dispatch the load and the consensus-based algorithm guarantees optimal load sharing. The proposed communication based control scheme reveals the best combination of performance and flexibility. A performance-based comparative analysis is also presented, validating the effectiveness of the proposed control scheme compared to the prior works. The robustness and performance of the proposed control scheme is illustrated through computer simulations

Frequency and Voltage Control of Islanded Microgrids

Islanded microgrids (MGs), characterized by distributed generators, power consumers, and energy storage systems (ESSs), are designed to signi cantly enhance self-sustainability of future distribution networks and to provide energy for remote communities. In order to have a stable system, both primary and secondary frequency and voltage control of the MG are critical. From a primary control perspective, it is essential to maintain frequency and voltage in acceptable ranges. Conventional controllers are designed to regulate system frequency and voltage solely based on droop control theory, and this is mainly provided by fast-response generation units such as ESSs. Therefore, an intelligent power sharing (IPS) control is necessary to maintain frequency and voltage within acceptable ranges, and to share power not only based on generation units' droop values, but also their operating power capabilities. A mathematical model of small-perturbation stability is presented along with performance analysis. Based on analysis and simulation results, the IPS controller offers advantages such as robust performance under load and renewable energy variations, a dynamic compromise between voltage regulation and accurate reactive power sharing among generators, and enhancement of voltage regulation by an adaptive virtual impedance. From a secondary control perspective, scheduling of generation units based on conventional unit commitment (UC) remains fi xed for the duration between two dispatch intervals; however, demand or renewable generation can continuously change. This stair-pattern scheduling of generation units creates large frequency and voltage excursions at the edge of each dispatch interval. Different from the existing UC mechanisms, a hybrid mid-level the controller is proposed based on communications with a distributed primary controller. It determines optimal power of generation units between two dispatch intervals for the secondary controller while regulating frequency and voltage within desirable ranges. Through several tested scenarios on a CIGRE test system, numerical results show that the mid-level controller can regulate frequency and voltage of the islanded MG. It covers time intervals between those of primary and secondary controllers and avoids the stair-pattern generation scheduling in conventional UCs. Additionally, it reduces both operating cost of MG and degradation of fast-acting generation units' life-cycle. Subsequently, impact of communication delay on islanded MGs is studied. The delay causes local controllers to use outdated power dispatches at the proposed mid-level controller. The outdated reference power deviates frequency and voltage from their nominal values in primary control. Existing primary and secondary controllers use a communication network assuming no time delay or considering a constant time delay. A mathematical model of constant and time-varying delay in islanded MGs is tegrated into the proposed mid-level controller. This formulation addresses the impact of time delay on transient performance of these controllers. A delay-based controller is designed to mitigate frequency oscillation of islanded MGs in the presence of either small or large perturbations. Numerical results are performed on small and large perturbations to evaluate the impact of time delay on realistic 14-bus CIGRE test system

Stability of microgrids and weak grids with high penetration of variable renewable energy

Autonomous microgrids and weak grids with high penetrations of variable renewable energy (VRE) generation tend to share several common characteristics: i) low synchronous inertia, ii) sensitivity to active power imbalances, and iii) low system strength (as defined by the nodal short circuit ratio). As a result of these characteristics, there is a greater risk of system instability relative to larger grids, especially as the share of VRE is increased. This thesis focuses on the development of techniques and strategies to assess and improve the stability of microgrids and weak grids. In the first part of this thesis, the small-signal stability of inertia-less converter dominated microgrids is analysed, wherein a load flow based method for small-signal model initialisation is proposed and used to examine the effects of topology and network parameters on the stability of the microgrid. The use of a back-to-back dc link to interconnect neighbouring microgrids and provide dynamic frequency support is then proposed to improve frequency stability by helping to alleviate active power imbalances. In the third part of this thesis, a new technique to determine the optimal sizing of smoothing batteries in microgrids is proposed. The technique is based on the temporal variability of the solar irradiance at the specific site location in order to maximise PV penetration without causing grid instability. A technical framework for integrating solar PV plants into weak grids is then proposed, addressing the weaknesses in conventional Grid Codes that fail to consider the unique characteristics of weak grids. Finally, a new technique is proposed for estimating system load relief factors that are used in aggregate single frequency stability models

Integration and Control of Distributed Renewable Energy Resources

The deployment of distributed renewable energy resources (DRERs) has accelerated globally due to environmental concerns and an increasing demand for electricity. DRERs are considered to be solutions to some of the current challenges related to power grids, such as reliability, resilience, efficiency, and flexibility. However, there are still several technical and non-technical challenges regarding the deployment of distributed renewable energy resources. Technical concerns associated with the integration and control of DRERs include, but are not limited, to optimal sizing and placement, optimal operation in grid-connected and islanded modes, as well as the impact of these resources on power quality, power system security, stability, and protection systems. On the other hand, non-technical challenges can be classified into three categories—regulatory issues, social issues, and economic issues. This Special Issue will address all aspects related to the integration and control of distributed renewable energy resources. It aims to understand the existing challenges and explore new solutions and practices for use in overcoming technical challenges

REAL-TIME CONGESTION MANAGEMENT IN MODERN DISTRIBUTION SYSTEMS

In this research, the problem of real-time congestion management in a modern distribution system with massive active elements such as electric vehicles (EVs), distributed energy resources (DERs), and demand response (DR) is investigated. A novel hierarchical operation and management framework is proposed that can take advantage of the demand side contribution to manage the real-time congestion. There are five main steps in this framework as 1) the aggregators send their demand to the microgrid operators (MGOs), 2) the MGOs send their demand to the distribution system operator (DSO), 3) the DSO detects the congestions and calls the engaged MGOs to reduce their demand, 4) the MGOs update the electricity price to motivate the aggregators to reduce the overall demand, and 5) the DSO dispatches the system according to the finalized demand. The proposed framework is validated on two modified IEEE unbalanced test systems. The results illustrate two congestion cases at t=8:45 am and t=9:30 am in the modified IEEE 13-bus test system, which needs 363kW and 286 kW load reductions, respectively, to be fully addressed. MG#1 and MG#2 are engaged to maintain the 363 kW reduction at t=8:45, and MG#3 and MG#4 are called to reduce their demands by 386 kW at t=9:30 am. The overall interactions can relieve the congested branches. The DSO’s calculations show three congestions at t=1 pm, t=3 pm, and t=9 pm on the IEEE 123-bus test system. These congestion cases can be alleviated by reducing 809 kW, 1177 kW, and 497 kW from the corresponding MGs at t=1 pm, t=3 pm, and t=9 pm, respectively. The second part of the simulation results demonstrates that the proposed real-time data estimator (RDE) can reduce the DSO’s miss-detected congestion cases due to the uncertain data. There are two miss-detected congestions in the IEEE 13-bus test system at t=1:15 pm and t=1:30 pm that can be filtered for t=1:15 pm and minored for t=1:30 pm using the RDE. The proposed RDE can also reduce the miss-detected congestions from 18 cases to four cases in the IEEE 123-bus test system. As a result, the RDE can minimize the extra costs due to the uncertain data. The overall results validate that the proposed framework can adaptively manage real-time congestions in distribution systems

A novel power management and control design framework for resilient operation of microgrids

This thesis concerns the investigation of the integration of the microgrid, a form of future electric grids, with renewable energy sources, and electric vehicles. It presents an innovative modular tri-level hierarchical management and control design framework for the future grid as a radical departure from the ‘centralised’ paradigm in conventional systems, by capturing and exploiting the unique characteristics of a host of new actors in the energy arena - renewable energy sources, storage systems and electric vehicles. The formulation of the tri-level hierarchical management and control design framework involves a new perspective on the problem description of the power management of EVs within a microgrid, with the consideration of, among others, the bi-directional energy flow between storage and renewable sources. The chronological structure of the tri-level hierarchical management operation facilitates a modular power management and control framework from three levels: Microgrid Operator (MGO), Charging Station Operator (CSO), and Electric Vehicle Operator (EVO). At the top level is the MGO that handles long-term decisions of balancing the power flow between the Distributed Generators (DGs) and the electrical demand for a restructure realistic microgrid model. Optimal scheduling operation of the DGs and EVs is used within the MGO to minimise the total combined operating and emission costs of a hybrid microgrid including the unit commitment strategy. The results have convincingly revealed that discharging EVs could reduce the total cost of the microgrid operation. At the middle level is the CSO that manages medium-term decisions of centralising the operation of aggregated EVs connected to the bus-bar of the microgrid. An energy management concept of charging or discharging the power of EVs in different situations includes the impacts of frequency and voltage deviation on the system, which is developed upon the MGO model above. Comprehensive case studies show that the EVs can act as a regulator of the microgrid, and can control their participating role by discharging active or reactive power in mitigating frequency and/or voltage deviations. Finally, at the low level is the EVO that handles the short-term decisions of decentralising the functioning of an EV and essential power interfacing circuitry, as well as the generation of low-level switching functions. EVO level is a novel Power and Energy Management System (PEMS), which is further structured into three modular, hierarchical processes: Energy Management Shell (EMS), Power Management Shell (PMS), and Power Electronic Shell (PES). The shells operate chronologically with a different object and a different period term. Controlling the power electronics interfacing circuitry is an essential part of the integration of EVs into the microgrid within the EMS. A modified, multi-level, H-bridge cascade inverter without the use of a main (bulky) inductor is proposed to achieve good performance, high power density, and high efficiency. The proposed inverter can operate with multiple energy resources connected in series to create a synergized energy system. In addition, the integration of EVs into a simulated microgrid environment via a modified multi-level architecture with a novel method of Space Vector Modulation (SVM) by the PES is implemented and validated experimentally. The results from the SVM implementation demonstrate a viable alternative switching scheme for high-performance inverters in EV applications. The comprehensive simulation results from the MGO and CSO models, together with the experimental results at the EVO level, not only validate the distinctive functionality of each layer within a novel synergy to harness multiple energy resources, but also serve to provide compelling evidence for the potential of the proposed energy management and control framework in the design of future electric grids. The design framework provides an essential design to for grid modernisation

Microgrids/Nanogrids Implementation, Planning, and Operation

Today’s power system is facing the challenges of increasing global demand for electricity, high-reliability requirements, the need for clean energy and environmental protection, and planning restrictions. To move towards a green and smart electric power system, centralized generation facilities are being transformed into smaller and more distributed ones. As a result, the microgrid concept is emerging, where a microgrid can operate as a single controllable system and can be viewed as a group of distributed energy loads and resources, which can include many renewable energy sources and energy storage systems. The energy management of a large number of distributed energy resources is required for the reliable operation of the microgrid. Microgrids and nanogrids can allow for better integration of distributed energy storage capacity and renewable energy sources into the power grid, therefore increasing its efficiency and resilience to natural and technical disruptive events. Microgrid networking with optimal energy management will lead to a sort of smart grid with numerous benefits such as reduced cost and enhanced reliability and resiliency. They include small-scale renewable energy harvesters and fixed energy storage units typically installed in commercial and residential buildings. In this challenging context, the objective of this book is to address and disseminate state-of-the-art research and development results on the implementation, planning, and operation of microgrids/nanogrids, where energy management is one of the core issues

Operation and Control of DC Microgrid

Power harnessing technology from the renewable energy resources has been developed over the past two decades. This technology enabled us to integrate renewable energy-based power generation to the conventional electric power grid. This study aims to improve the dynamic response and the load regulation using improved control strategies of the dc converters used to interface utility and renewable energy-based power generation. The power sharing between multiple dc microgrids/ac-dc microgrids is also investigated

Design and Implementation of PV-Firming and Optimization Algorithms For Three-Port Microinverters

With the demand increase for electricity, the ever-increasing awareness of environmental issues, coupled with rolling blackouts, the role of renewable energy generation is increasing along with the thirst for electricity and awareness of environmental issues. This dissertation proposes the design and implementation of PV-firming and optimization algorithms for three-port microinverters. Novel strategies are proposed in Chapters 3 and 4 for harvesting stable solar power in spite of intermittent solar irradiance. PV firming is implemented using a panel-level three-port grid-tied PV microinverter system instead of the traditional high-power energy storage and management system at the utility scale. The microinverter system consists of a flyback converter and an H-bridge inverter/rectifier, with a battery connected to the DC-link. The key to these strategies lies in using static and dynamic algorithms to generate a smooth PV reference power. The outcomes are applied to various control methods to charge/discharge the battery so that a stable power generation profile is obtained. In addition, frequency-based optimization for the inverter stage is presented. One of the design parameters of grid-tied single-phase H-bridge sinusoidal pulse-width modulation (SPWM) microinverters is switching frequency. The selection of the switching frequency is a tradeoff between improving the power quality by reducing the total harmonic distortion (THD), and improving the efficiency by reducing the switching loss. In Chapter 5, two algorithms are proposed for optimizing both the power quality and the efficiency of the microinverter. They do this by using a frequency tracking technique that requires no hardware modification. The first algorithm tracks the optimal switching frequency for maximum efficiency at a given THD value. The second maximizes the power quality of the H-bridge micro-inverter by tracking the switching frequency that corresponds to the minimum THD. Real-time PV intermittency and usable capacity data were evaluated and then further analyzed in MATLAB/SIMULINK to validate the PV firming control. The proposed PV firming and optimization algorithms were experimentally verified, and the results evaluated. Finally, Chapter 6 provides a summary of key conclusions and future work to optimize the presented topology and algorithms