Load frequency controllers considering renewable energy integration in power system

Abstract: Load frequency control or automatic generation control is one of the main operations that take place daily in a modern power system. The objectives of load frequency control are to maintain power balance between interconnected areas and to control the power flow in the tie-lines. Electric power cannot be stored in large quantity that is why its production must be equal to the consumption in each time. This equation constitutes the key for a good management of any power system and introduces the need of more controllers when taking into account the integration of renewable energy sources into the traditional power system. There are many controllers presented in the literature and this work reviews the traditional load frequency controllers and those, which combined the traditional controller and artificial intelligence algorithms for controlling the load frequency

Modelling and Simulation Approaches for Local Energy Community Integrated Distribution Networks

Due to the absence of studies of local energy communities (LECs) where the grid is represented, it is very difficult to infer implications of increased LEC integration for the distribution grid as well as for the wider society. Therefore, this paper aims to investigate holistic modelling and simulation approaches of LECs. To conduct a quantifiable assessment of different control architectures, LEC types and market frameworks, a flexible and comprehensive LEC modelling and simulation approach is needed. Modelling LECs and the environment they operate in involves a holistic approach consisting of different layers: market, controller, and grid. The controller layer is relevant both for the overall energy management system of the LEC and the controllers of single components in a LEC. In this paper, the different LEC modelling approaches in the reviewed literature are presented, several multilayered concepts for LECs are proposed, and a case study is presented to illustrate a holistic simulation where the different layers interact.Modelling and Simulation Approaches for Local Energy Community Integrated Distribution NetworkspublishedVersio

An overview of grid-edge control with the digital transformation

Distribution networks are evolving to become more responsive with increasing integration of distributed energy resources (DERs) and digital transformation at the grid edges. This evolution imposes many challenges to the operation of the network, which then calls for new control and operation paradigms. Among others, a so-called grid-edge control is emerging to harmonise the coexistence of the grid control system and DER’s autonomous control. This paper provides a comprehensive overview of the grid-edge control with various control architectures, layers, and strategies. The challenges and opportunities for such an approach at the grid edge with the integration of DERs and digital transformation are summarised. The potential solutions to support the network operation by using the inherent controllability of DER and the availability of the digital transformation at the grid edges are discussed

Location Awareness in Multi-Agent Control of Distributed Energy Resources

The integration of Distributed Energy Resource (DER) technologies such as heat pumps, electric vehicles and small-scale generation into the electricity grid at the household level is limited by technical constraints. This work argues that location is an important aspect for the control and integration of DER and that network topology can inferred without the use of a centralised network model. It addresses DER integration challenges by presenting a novel approach that uses a decentralised multi-agent system where equipment controllers learn and use their location within the low-voltage section of the power system. Models of electrical networks exhibiting technical constraints were developed. Through theoretical analysis and real network data collection, various sources of location data were identified and new geographical and electrical techniques were developed for deriving network topology using Global Positioning System (GPS) and 24-hour voltage logs. The multi-agent system paradigm and societal structures were examined as an approach to a multi-stakeholder domain and congregations were used as an aid to decentralisation in a non-hierarchical, non-market-based approach. Through formal description of the agent attitude INTEND2, the novel technique of Intention Transfer was applied to an agent congregation to provide an opt-in, collaborative system. Test facilities for multi-agent systems were developed and culminated in a new embedded controller test platform that integrated a real-time dynamic electrical network simulator to provide a full-feedback system integrated with control hardware. Finally, a multi-agent control system was developed and implemented that used location data in providing demand-side response to a voltage excursion, with the goals of improving power quality, reducing generator disconnections, and deferring network reinforcement. The resulting communicating and self-organising energy agent community, as demonstrated on a unique hardware-in-the-loop platform, provides an application model and test facility to inspire agent-based, location-aware smart grid applications across the power systems domain

Multi-agent MPC protocols for microgrid energy management and optimization

Navržení efektivního a spolehlivého řízení mikrosítí s vysokým podílem energie z obnovitelných zdrojů, je jednou z výzev při jejich nasazení. Prediktivní řízení (MPC) systému je slibný přístup, jak vyřešit tento problém v určitém časovém horizontu. Tento přístup umožňuje integraci řízení na základě minimalizace funkce, která dává do souvislosti různé druhy nákladů a omezení systému, ve vazbě na výrobu a spotřebu energie. Navržené multiagentní MPC řízení bylo vyvinuto jako dvoustupňová architektura, založená na konsensuálním algoritmu více agentů, který zajišťuje výkonovou rovnováhu v mikrosíti a centralizovaném MPC, který zefektivňuje řízené procesy tak, aby dosáhly vytyčených cílů. Při zkoumání navržených simulací byla ověřena předpokládaná korelace získaných výsledků a řídicích parametrů. Dále byla identifikována a analyzována situace s nejvyšším zlepšením ve srovnání s výsledky referenční řídící architektury. Na základě výsledků testů řídicího protokolu na testovaných datech, které byly měřeny v reálné mikrosíti, je vidět možnost významného snížení nákladů na provoz mikrosítě. Navrhované řešení tedy ukazuje vhodnost jeho implementace a přínos, jak pro provozovatele mikrosítí, tak pro zákazníky distribuční soustavy.One of the challenges of microgrids under the influence of high shares of intermittent renewable energy sources (RES) is an effective and reliable control. Model predictive control (MPC) is a promising approach to solve this problem for a specified time horizon since it allows integrating of a cost-minimizing objective function and system boundaries while taking power demand and supply into account. An agent-based MPC scheme was developed as a two-level architecture based on multi-agent control system (MAS) consensus algorithm providing power balance in the microgrid and centralized MPC that is aspiring to streamline the control processes to reach the targeted objectives. During the examination of the simulated results, the expected correlation of the result properties and control parameters was found. Additionally, the situations with the highest improvement ratio in comparison with the results of the reference control architecture were discovered and analysed. Based on the results, a significant cost reduction can be seen in most of the tested datasets that were measured on a real-life microgrid solution. Therefore, the implementation of the suggested control can prove to be appropriate and beneficial for microgrid operators and grid customers

Resilience-driven planning and operation of networked microgrids featuring decentralisation and flexibility

High-impact and low-probability extreme events including both man-made events and natural weather events can cause severe damage to power systems. These events are typically rare but featured in long duration and large scale. Many research efforts have been conducted on the resilience enhancement of modern power systems. In recent years, microgrids (MGs) with distributed energy resources (DERs) including both conventional generation resources and renewable energy sources provide a viable solution for the resilience enhancement of such multi-energy systems during extreme events. More specifically, several islanded MGs after extreme events can be connected with each other as a cluster, which has the advantage of significantly reducing load shedding through energy sharing among them. On the other hand, mobile power sources (MPSs) such as mobile energy storage systems (MESSs), electric vehicles (EVs), and mobile emergency generators (MEGs) have been gradually deployed in current energy systems for resilience enhancement due to their significant advantages on mobility and flexibility. Given such a context, a literature review on resilience-driven planning and operation problems featuring MGs is presented in detail, while research limitations are summarised briefly. Then, this thesis investigates how to develop appropriate planning and operation models for the resilience enhancement of networked MGs via different types of DERs (e.g., MGs, ESSs, EVs, MESSs, etc.). This research is conducted in the following application scenarios: 1. This thesis proposes novel operation strategies for hybrid AC/DC MGs and networked MGs towards resilience enhancement. Three modelling approaches including centralised control, hierarchical control, and distributed control have been applied to formulate the proposed operation problems. A detailed non-linear AC OPF algorithm is employed to model each MG capturing all the network and technical constraints relating to stability properties (e.g., voltage limits, active and reactive power flow limits, and power losses), while uncertainties associated with renewable energy sources and load profiles are incorporated into the proposed models via stochastic programming. Impacts of limited generation resources, load distinction intro critical and non-critical, and severe contingencies (e.g., multiple line outages) are appropriately captured to mimic a realistic scenario. 2. This thesis introduces MPSs (e.g., EVs and MESSs) into the suggested networked MGs against the severe contingencies caused by extreme events. Specifically, time-coupled routing and scheduling characteristics of MPSs inside each MG are modelled to reduce load shedding when large damage is caused to each MG during extreme events. Both transportation networks and power networks are considered in the proposed models, while transporting time of MPSs between different transportation nodes is also appropriately captured. 3. This thesis focuses on developing realistic planning models for the optimal sizing problem of networked MGs capturing a trade-off between resilience and cost, while both internal uncertainties and external contingencies are considered in the suggested three-level planning model. Additionally, a resilience-driven planning model is developed to solve the coupled optimal sizing and pre-positioning problem of MESSs in the context of decentralised networked MGs. Internal uncertainties are captured in the model via stochastic programming, while external contingencies are included through the three-level structure. 4. This thesis investigates the application of artificial intelligence techniques to power system operations. Specifically, a model-free multi-agent reinforcement learning (MARL) approach is proposed for the coordinated routing and scheduling problem of multiple MESSs towards resilience enhancement. The parameterized double deep Q-network method (P-DDQN) is employed to capture a hybrid policy including both discrete and continuous actions. A coupled power-transportation network featuring a linearised AC OPF algorithm is realised as the environment, while uncertainties associated with renewable energy sources, load profiles, line outages, and traffic volumes are incorporated into the proposed data-driven approach through the learning procedure.Open Acces

Distributed control strategy for DC microgrids based on average consensus and fractional-order local controllers

A novel distributed secondary layer control strategy based on average consensus and fractional-order proportional-integral (FOPI) local controllers is proposed for the regulation of the bus voltages and energy level balancing of the energy storage systems (ESSs) in DC microgrids. The distributed consensus protocol works based on an undirected sparse communication network. Fractional-order local controllers increase the degree of freedom in the tuning of closed-loop controllers, which is required for DC microgrids with high order dynamics. Therefore, here, FOPI local controllers are proposed for enhanced energy balancing of ESSs and improved regulation of the bus voltages across the microgrid. The proposed control strategy operates in both islanded and grid-connected modes of a DC microgrid. In both modes, the average voltage of the microgrid converges to the microgrid desired reference voltage. The charging/discharging of ESSs is controlled independent of the microgrid operating mode to maintain a balanced energy level. The performance of the proposed distributed control strategy is validated in a 38- V DC microgrid case study, simulated by Simulink real-time desktop, consisting of 10 buses and a photovoltaic renewable energy source

Decentralised control method for DC microgrids with improved current sharing accuracy

© The Institution of Engineering and Technology 2016. A decentralised control method that deals with current sharing issues in dc microgrids (MGs) is proposed in thisstudy. The proposed method is formulated in terms of 'modified global indicator' concept, which was originally proposedto improve reactive power sharing in ac MGs. In this work, the 'modified global indicator' concept is extended tocoordinate dc MGs, which aims to preserve the main features offered by decentralised control methods such as no need ofcommunication links, central controller or knowledge of the microgrid topology and parameters. This global indicator isinserted between current and voltage variables by adopting a virtual capacitor, which directly produces an output currentsharing performance that is less relied on mismatches of the multi-bus network. Meanwhile, a voltage stabiliser iscomplementary developed to maintain output voltage magnitude at steady state through a shunt virtual resistance. Theoperation under multiple dc-buses is also included in order to enhance the applicability of the proposed controller. Adetailed mathematical model including the effect of network mismatches is derived for analysis of the stability of theproposed controller. The feasibility and effectiveness of the proposed control strategy are validated by simulation andexperimental results

Ultimate boundedness of droop controlled Microgrids with secondary loops

In this paper we study theoretical properties of inverter-based microgrids controlled via primary and secondary loops. Stability of these microgrids has been the subject of a number of recent studies. Conventional approaches based on standard hierarchical control rely on time-scale separation between primary and secondary control loops to show local stability of equilibria. In this paper we show that (i) frequency regulation can be ensured without assuming time-scale separation and, (ii) ultimate boundedness of the trajectories starting inside a region of the state space can be guaranteed under a condition on the inverters power injection errors. The trajectory ultimate bound can be computed by simple iterations of a nonlinear mapping and provides a certificate of the overall performance of the controlled microgrid.Comment: 8 pages, 1 figur

Control of an islanded microgrid

This thesis presents a detailed investigative process into the study of the control of an islanded microgrid. This investigation is done through the research and exploration of multiple existing control techniques for the control of a microgrid and then by analysing them to identify the areas where the existing methods can be altered in order to reduce or mitigate common operational issues. The final goal was to use the gathered information to develop an innovative strategy that may be used to control an islanded microgrid. However, due to various challenges faced over the course of the project – this goal was not achieved. In light of this, the aim of this thesis was for it to became a research focused development of a body of work that may be useful or potentially serve as a point of reference for future studies in the control of an islanded microgrid. 1. P & PI Controller Regulation & Response Times 2. Natural Load Sharing Amongst Distributed Generators 3. Secondary Frequency-Load Control Mechanisms 4. Controllable Storage Systems 5. Automated Load Shedding in Microgrids 6. Stabilizer Control Strategies By developing this list of factors and considerations, this thesis project aims to be a useful resource for future studies performed in the topic of islanded microgrid control. The aspiration is that by collating extensive background, theoretical and technical research in this project, the efficiency of those who may want to continue work in this area of study will be improved