A Case Study on Application of Fuzzy Logic based Controller for Peak Load Shaving in a Typical Household\u27s Per Day Electricity Consumption

The cost of electricity for consumers depends on the cost of generation, transmission, and distribution of power. The electrical load consumed by consumers per day is not constant throughout the day. The utilities must be capable of meeting the load demand, which means they must have enough electricity generation potential and necessary infrastructure. This cost is significant. However, the revenue they generate will only be for the actual use of electricity by the consumers. In general, the electrical power generation is done in stages, always generating a base load. As demand changes throughout the day, additional stages of power generation are brought online to meet the changes in demand. This approach of management is known as supply-side management. Theoretically, if it is possible to manage the load such that there is lower peak demand and the difference between peak load and base load were minimized, the generation capability and grid infrastructure required to provide reliable power would be reduced resulting in lower costs for utility companies and ultimately consumers. This management strategy is referred to as demand-side management or demand response. In this research, a small-scale smart grid is modeled in Simulink to mimic the electrical grid. A Smart controller based on fuzzy logic is developed to control charging and discharging of an electric vehicle battery to provide extra power during peak times and to act as load (storing energy) during off-peak time to provide a more manageable and balanced load as seen by the grid. A comparative study is presented of electricity consumption throughout the day with or without the smart controller. The results show the significant reduction in peak demand, much smoother load curve for the grid, and a decrease in per kilowatt cost of electricity for the given day when newer pricing structures are applied

Accurate Battery Modelling for Control Design and Economic Analysis of Lithium-ion Battery Energy Storage Systems in Smart Grid

Adoption of lithium-ion battery energy storage systems (Li-ion BESSs) as a flexible energy source (FES) has been rapid, particularly for active network management (ANM) schemes to facilitate better utilisation of inverter based renewable energy sources (RES) in power systems. However, Li-ion BESSs display highly nonlinear performance characteristics, which are based on parameters such as state of charge (SOC), temperature, depth of discharge (DOD), charge/discharge rate (C-rate), and battery-aging conditions. Therefore, it is important to include the dynamic nature of battery characteristics in the process of the design and development of battery system controllers for grid applications and for techno-economic studies analyzing the BESS economic profitability. This thesis focuses on improving the design and development of Li-ion BESS controllers for ANM applications by utilizing accurate battery performance models based on the second-order equivalent-circuit dynamic battery modelling technique, which considers the SOC, C-rate, temperature, and aging as its performance affecting parameters. The proposed ANM scheme has been designed to control and manage the power system parameters within the limits defined by grid codes by managing the transients introduced due to the intermittence of RESs and increasing the RES penetration at the same time. The validation of the ANM scheme and the effectiveness of controllers that manage the flexibilities in the power system, which are a part of the energy management system (EMS) of ANM, has been validated with the help of simulation studies based on an existing real-life smart grid pilot in Finland, Sundom Smart Grid (SSG). The studies were performed with offline (short-term transient-stability analysis) and real-time (long-term transient analysis) simulations. In long-term simulation studies, the effect of battery aging has also been considered as part of the Li-ion BESS controller design; thus, its impact on the overall power system operation can be analyzed. For this purpose, aging models that can determine the evolving peak power characteristics associated with aging have been established. Such aging models are included in the control loop of the Li-ion BESS controller design, which can help analyse battery aging impacts on the power system control and stability. These analyses have been validated using various use cases. Finally, the impact of battery aging on economic profitability has been studied by including battery-aging models in techno-economic studies.Aurinkosähköjärjestelmien ja tuulivoiman laajamittainen integrointi sähkövoimajärjestelmän eri jännitetasoille on lisääntynyt nopeasti. Uusiutuva energia on kuitenkin luonteeltaan vaihtelevaa, joka voi aiheuttaa nopeita muutoksia taajuudessa ja jännitteessä. Näiden vaihteluiden hallintaan tarvitaan erilaisia joustavia energiaresursseja, kuten energiavarastoja, sekä niiden tehokkaan hyödyntämisen mahdollistaviea älykkäitä ja aktiivisia hallinta- ja ohjausjärjestelmiä. Litiumioniakkuihin pohjautuvien invertteriliitäntäisten energian varastointijärjestelmien käyttö joustoresursseina aktiiviseen verkonhallintaan niiden pätö- ja loistehon ohjauksen avulla on lisääntynyt nopeasti johtuen niiden kustannusten laskusta, modulaarisuudesta ja teknisistä ominaisuuksista. Litiumioniakuilla on erittäin epälineaariset ominaisuudet joita kuvaavat parametrit ovat esimerkiksi lataustila, lämpötila, purkaussyvyys, lataus/ purkausnopeus ja akun ikääntyminen. Akkujen ominaisuuksien dynaaminen luonne onkin tärkeää huomioida myös akkujen sähköverkkoratkaisuihin liittyvien säätöjärjestelmien kehittämisessä sekä teknis-taloudellisissa kannattavuusanalyyseissa. Tämä väitöstutkimus keskittyy ensisijaisesti aktiiviseen verkonhallintaan käytettävien litiumioniakkujen säätöratkaisuiden parantamiseen hyödyntämällä tarkkoja, dynaamisia akun suorituskykymalleja, jotka perustuvat toisen asteen ekvivalenttipiirien akkumallinnustekniikkaan, jossa otetaan huomioon lataustila, lataus/purkausnopeus ja lämpötila. Työssä kehitetyn aktiivisen verkonhallintajärjestelmän avulla tehtävät akun pätö- ja loistehon ohjausperiaatteet on validoitu laajamittaisten simulointien avulla, esimerkiksi paikallista älyverkkopilottia Sundom Smart Gridiä simuloimalla. Simuloinnit tehtiin sekä lyhyen aikavälin offline-simulaatio-ohjelmistoilla että pitkän aikavälin simulaatioilla hyödyntäen reaaliaikasimulointilaitteistoa. Pitkän aikavälin simulaatioissa akun ikääntymisen vaikutus otettiin huomioon litiumioniakun ohjauksen suunnittelussa jotta sen vaikutusta sähköjärjestelmän kokonaistoimintaan voitiin analysoida. Tätä tarkoitusta varten luotiin akun ikääntymismalleja, joilla on mahdollista määrittää akun huipputehon muutos sen ikääntyessä. Akun huipputehon muutos taas vaikuttaa sen hyödynnettävyyteen erilaisten pätötehon ohjaukseen perustuvien joustopalveluiden tarjoamiseen liittyen. Lisäksi väitöstutkimuksessa tarkasteltiin akkujen ikääntymisen vaikutusta niiden taloudelliseen kannattavuuteen sisällyttämällä akkujen ikääntymismalleja teknis-taloudellisiin tarkasteluihin.fi=vertaisarvioitu|en=peerReviewed

Lithium-ion BESS integration for smart grid applications : ECM modelling approach

Lithium-ion battery energy storage systems (BESS) with their present state of technology and economic maturity possess huge potential for catering short-term flexibility requirements in smart grid environment. However, it is essential to model in detail the complexity of non-linear battery system characteristics and control of their adjoining power electronic interfaces. More detailed and accurate modelling of components, enables improved overall power system optimization studies by considering both, component and system level aspects simultaneously. Therefore, this paper develops an equivalent circuit model (ECM) for Lithium-ion battery and Lithium-ion nickel-manganese-cobalt (NMC) battery cell is modelled as a second order equivalent circuit (SOEC), including C-rate, temperature, state-of-charge and age effects. Secondly, detailed controller design methodology for DC/DC- and DC/AC-converter interfaces are developed to enable advanced grid integration studies. Overall, BESS integration design was validated by simulation studies in Simulink Simpowersystems platform.©2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.fi=vertaisarvioitu|en=peerReviewed

Control and Energy Management of Standalone Interconnected AC Microgrids

This thesis considered microgrids as local area distribution mini-power grids formed by distributed generation sources, energy storage systems and loads. They are reliable and can operate at different voltages and frequencies to meet the requirements of the load. Microgrids have limited renewable energy source (RES) capacity, which can only supply a limited load and increasing the load beyond a specifically designed limit can lead to stability issues. Irrespective of its limited capacity, there has been an increased widespread deployment of renewable energy-based microgrids worldwide orchestrated by the 2015 Paris Agreement and the war in Ukraine and as a solution to meet the global demand for energy in electricity deficit zones aimed to achieve universal access to affordable, reliable, and sustainable energy. Fast forward to the future, flooded singly operated microgrids face the problem of more curtailing of RES and load shedding. Multiple microgrids can be interconnected to mitigate the limitations of single microgrids and improve supply reliability, enhance power supply availability, stability, reserve capacity, reduce investment in new generating capacity and control flexibility. As a result, this thesis proposes a new structure and control technique for interconnecting multiple standalone AC microgrids to a common alternating current (AC) bus using a back-to-back power electronic converter and a traditional transformer. Each microgrid considered in this thesis comprises a renewable energy source (RES), battery, auxiliary unit, and load. The battery maintains the AC bus voltage and frequency and balances the difference in power generated by the RES and that consumed by the load. Each microgrid battery’s charge/discharge is maintained within the safest operating limit to maximise the RES power utilisation. The back-to-back converters are used to decouple the connecting standalone microgrid frequencies and facilitate power exchange between microgrids. The transformer is used to transmit electric power over long distances efficiently. The control technique for all the connecting bidirectional back-to-back converters is developed to manage the bidirectional power flow between each microgrid and other microgrids in the network and to balance the energy in the global bus of the interconnected microgrid with no communication. The control strategy uses a frequency signalling mechanism to limit the power demand of individual global converters and adjusts its droop coefficients accordingly and in proportion to deviation in frequency. The global droop controllers of the global connecting converters receive information about the status of the frequencies of individual microgrids using a low bandwidth communication link to enhance network power flow. MATLAB/Simulink results validate the performance of the proposed structure and control strategy. A decentralised control scheme is further proposed for the standalone interconnected AC microgrid structure. This thesis presented a high-level global droop controller that exchanges power between the interconnected microgrids. Renewable power curtailment and auxiliary power supplement mechanisms are designed based on the bus frequency signalling technique to achieve balance and continuity of supply. In case of power shortage in one microgrid, priority will first be given to power import from other microgrids. A power supplement is used if the power imported is insufficient to control the battery state of charge (SOC). Similarly, in case of a power surplus, priority will be given to power export, and if this is not enough, power from RES will be curtailed. Performance evaluation shows that the proposed controller maximises renewable power utilisation and minimises auxiliary power usage while providing better load support. The performance validation of the proposed structure and control strategy has been tested using MATLAB/Simulink. Furthermore, this thesis investigated a centralised control and energy management of multiple interconnected standalone AC microgrids using the Nelder-Mead simplex algorithm (Fminsearch optimisation toolbox in MATLAB) based on the new proposed model. The main objective is to minimise the total cost of energy from the auxiliary unit produced from gas. The results obtained are compared with those obtained from an unoptimised system. The performance evaluation investigation results are compared with the unoptimised results to determine the percentage optimal performance of the system. The comparison outcome shows that the proposed optimisation method minimises the total auxiliary energy cost by about 9% compared with the results of the unoptimised benchmark

Frequency and voltage control of island system using power hardware in the loop

Power generation via Distributed Generation (DG) plants coupled with inverters can participate in Frequency and Voltage stabilization of the microgrid which is important to grid operators. This paper explores the realization of improved regulation of frequency and voltages in a low voltage microgrid using droop-controlled power converters. The test bed consists of a Power Hardware in the Loop (PHIL) setup, which includes a grid-forming battery inverter, local loads, and DG plants. In the PHIL setup, the grid-forming battery inverter was responsible for setting the network voltage, which served the loads initially before the distributed energy resources were energized. Additional loads were then switched on triggering a frequency drop in the network. Changes in the load requirement and performance of the DGs were examined through the PHIL setup with the energy storage system further supporting as require. The results showed notable improvement in the overall system frequency and voltage regulation

Control de voltaje óptimo para sistemas de almacenamiento de energía de batería (BESS) acoplados a microrredes de AC utilizando algoritmos LQG

La presente investigación desarrolla una estrategia de control óptimo de voltaje para sistemas perturbados de Almacenamiento de Energía por Baterías (BESS) acoplados en AC a Micro-redes eléctricas Híbridas (MRH) en AC/DC. La estrategia propuesta se basa principalmente en un Control Lineal Cuadrático Gaussiano (LQG), método que posibilita el control de sistemas no lineales perturbados como los BESS. El estudio permite obtener una ley de control optima por realimentación dinámica lineal para los sistemas BESS acoplados mediante convertidores electrónicos de voltaje en cascada. El estudio se implementó en un sistema MR tipo benchmark que opera en condiciones normales, sin fallas y en modo aislado. Los resultados obtenidos se validaron y compararon con un control clásico PI usando simulación digital en Matlab / Simulink. Además, se analizará el comportamiento dinámico del voltaje de la planta, en dos casos; máxima demanda y mínima demanda, en un punto de operación.The present research develops an optimal voltage control strategy of disturbed Battery Energy Storage Systems (BESS) coupled in AC Hybrid Microgrids (HMG) in AC / DC. The proposed strategy is mainly based on a Gaussian Linear Quadratic Control (LQG), a method that enables the control of disturbed non-linear systems such as BESS. The study allows to obtain an optimal control law by linear dynamic feedback for BESS systems coupled by electronic voltage converters in cascade. The study was implemented in a benchmark HMG system that operates under normal conditions, without failures and in isolated mode. The results obtained were validated and compared with a classic PI control using digital simulation in Matlab / Simulink. Furthermore, the dynamic behavior of the plant voltage will be analyzed in two cases; maximum demand and minimum demand, at one point of operation

Exploring Cyber Security Issues and Solutions for Various Components of DC Microgrid System

Nowadays, considering the growing demand for the DC loads and simplified interface with renewable power generation sources, DC microgrids could be cost effective solution for the power supply in small scale area. the supervisory control and data acquisition (SCADA) system maintain the bidirectional power communication through the internet connectivity with the microgrid. However, this intelligent and interactive feature may pose a cyber-security threat to the power grid. this work aims to exploring cyber-security issues and their solutions for the DC microgrid system. To mitigate the adverse effects of various cyber-attacks such as the False Data Injection (FDI) attack, Distributed Denial of Service (DDoS) attack etc., two new techniques based on non-linear and proportional-integral (PI) controllers have been proposed. Simulation results obtained from MATLAB/Simulink software demonstrate the effectiveness of the proposed methods in mitigating the adverse effects of cyber-attacks on the DCMG system performance

Control of Solar Photovoltaic (PhV) Power Generation In Grid-connected and Islanded Microgrids

With the ever increasing electricity demand, fast depletion of fossil fuel and the growing trend towards renewable energy resources, the integration of green distributed energy resources (DERs) such as solar photovoltaic (PhV) generation and wind power in the utility grid is gaining high popularity in the present years. The capability of these modular generators needs to be harnessed properly in order to achieve the maximum benefit out of such integrated systems. Most DERs are connected to the utility grid or microgrids with the help of power electronics interface. They are capable of producing both active and reactive power with the proper control of the inverter interface. This dissertation focuses on examination of the capability of the renewable energy based DERs, such as solar PhV array and battery energy storage system (BESS) in providing voltage support in grid connected low-voltage microgrids and both voltage and frequency support in islanded microgrids. In addition, active and reactive (a.k.a. nonactive) power control capability of the PhV generators to supply the local loads assigned by the microgrid central operator in grid connected mode is also investigated. The control methods are developed by using a Proportional and Integral (PI) controller. A new method of Maximum Power Point Tracking (MPPT) of solar array including the MPPT at solar PhV array side and a new control method of transferring this MPP power to the inverter side insuring the DC voltage stability by using the concept of power balance at various conversion stages is proposed and studied. The dissertation also proposes a new coordinated control method for voltage and frequency regulation of microgrid with solar PhV generator operating at MPP and backed up by battery energy storage systems. A coordinated active and reactive power control for solar PhV generator with MPPT control and battery storage is also proposed and investigated. Various case studies are presented to validate the proposed methods. The simulation results clearly prove the effectiveness of the proposed control method

Control Hierarchies for Critical Infrastructures in Smart Grid Using Reinforcement Learning and Metaheuristic Optimization

The objective of this work is to develop robust control framework for interdependent smart grid infrastructures comprising two critical infrastructures: 1) power distribution networks that are characterized by high penetration of distributed energy resources (DERs), and 2) DC-rail transportation systems in congested urban areas. The rising integration of DERs into the power grid is causing a paradigm shift in the power distribution network. Consequently, new control challenges for efficient and robust operation of the power grid have surfaced. For instance, the intermittency of renewable energy resources necessitates coordinated control of power flows, voltage regulators, and protection device settings of the online resources in the system. This can be achieved with the help of an active distribution network, equipped with a distribution management system that provides online solutions to control problems, in real-time, by having full or partial observability. Besides, the increasing electrification of other critical infrastructures, such as transportation and communication, necessitates controllers that can accommodate the over-arching control requirements of interdependent critical infrastructures. Present control approaches lack the amalgamation of active distribution management and the flexibility to accommodate other critical infrastructures. In this work two levels of control hierarchies, viz. 1) Primary Controller and 2) Secondary Controller, have been designed for the power distribution system. These controllers can provide active distribution management, which can be expanded for seamless integration of other critical infrastructures. Besides, a real-time simulation-in-the-loop testbed has been developed, so that both transient and steady state performance of the controllers can be evaluated simultaneously. This testbed has been developed using OPAL-RT and DSpace. The effectiveness of these controllers have been tested in three types of active distribution networks: 1) A modified IEEE 5-bus system equipped with a grid-connected microgrid that consists of two DERs, 2) A modified IEEE 13-bus system equipped with an islanded community microgrid (C_-Grid) comprising four DERs, and 3) A modified IEEE-30 bus system comprising five grid-connected distributed generations (DGs). The DERs used for this work are battery energy storage systems and photovoltaic systems. The Primary Controller has been designed for regulating voltage, frequency and current in the system, while maintaining stability of these parameters, in both grid-tied and islanded operating modes. These design approaches consider multiple points of coupling among the DERs, which is lacking in the existing literature that is primarily focused on single point of common coupling. Besides, this work shows a method of incorporating communication latency, which may exist between Primary and Secondary Controller, into the control design. This facilitates performance analysis of the primary controller, when it is subjected to communication latency, and accordingly develop mitigation techniques. The Secondary Controller has been designed using a reinforcement learning technique called Adaptive Critic Design (ACD). ACD can facilitate seamless integration of a power distribution network with other critical infrastructures. The ACD based algorithm functions as a distribution management system where its control objectives are to balance load and generation, to take preventive or corrective measures for mitigating failures and improving system resiliency, to minimize the cost of energy incurred by the loads by dispatching the DERs, and to maintain their state of health. Alongside DERs, the impact of DC-rail transportation on the power distribution network has been investigated here, with an objective of efficiently and economically reducing congestion in power substations. Hybrid energy storage systems, comprising battery, supercapacitor and flywheel, have been used as wayside energy storage technologies for this purpose. These storage technologies reduce congestion by supplying energy during acceleration and coasting of the trains, and replenish their energy by recapturing the regenerative braking energy during deceleration of the same. The trains consume/regenerate energy at a very high rate during acceleration/deceleration, thereby requiring storage technologies with both high energy and power densities. Hence, the three aforementioned storage technologies have been investigated for both standalone and hybrid operations, by considering system performance and resiliency alongside the percentage of energy recovered, without comprising the cost-recuperation over time. This has been achieved using a two-stage method, where the first stage comprises the development of detailed mathematical model of the rail system and the storage technologies. This mathematical model has been optimized using Genetic Algorithm, in order to obtain optimal combinations of type and size of the storage technologies for minimum cost, within the system constraints. In the second stage, a detailed simulation model has been developed by capturing all the dynamics of the transportation network, which could not be entirely represented in the mathematical model. The optimal sizes obtained from the first stage have been used in the second stage to evaluate their performance and accordingly adjust their values. Thus, the mathematical model provides initial values in a large search space, and these values are further tuned based on the results from simulation model