• Refine Query
  • Source
  • Publication year
  • to
  • Language
  • 49
  • 6
  • 4
  • 2
  • 1
  • 1
  • Tagged with
  • 75
  • 75
  • 75
  • 45
  • 42
  • 25
  • 22
  • 20
  • 20
  • 19
  • 18
  • 18
  • 14
  • 13
  • 12
  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
31

Virtual Power Plant Optimization Utilizing the FCR-N Market : A revenue maximization modelling study based on building components and a Battery Energy Storage System. Based on values from Sweden's first virtual power plant, Väla.

Edwall, Bill January 2020 (has links)
Renewable energy resources are projected to claim a larger part of the Swedish power mix in coming years. This could potentially increase frequency fluctuations in the power grid due to the intermittency of renewable power generating resources. These fluctuations can in turn cause issues in the power grid if left unchecked. In order to resolve these issues, countermeasures are employed. One such countermeasure is for private actors to regulate power; in exchange they are financially compensated through reserve markets. The reserve market studied in this thesis is called Frequency Containment Reserve – Normal (FCR-N). Currently hydroelectric power provides almost all regulated power within this market. As the need for power regulation is expected to increase in the coming years, there exists a need to study other technologies capable of power regulation. This thesis focuses on one such technology called, virtual power plants. While virtual power plants are operating in other parts of the world, there were no virtual power plants operating in Sweden. As a result, the nature of an optimized virtual power plant and the economic benefits of optimization had not been previously investigated. To answer such questions, this thesis modelled and optimized the revenue of a virtual power plant. The examined virtual power plant consisted of cooling chillers, lighting, ventilation fans and a battery energy storage system. Where varying their total power demand allowed for them to provide power regulation. With the virtual power plant market in Sweden being in its infancy, this thesis serves as a first look into how an optimized virtual power plant using these components could function. To put the economic results of the optimization into context, a comparative model was constructed. The comparative model was based on a semi-static linear model. This is what the thesis’s industry partner Siemens currently uses. For the simulated scenarios, the optimized model generated at least 85% higher net revenues than the semi-static linear model. The increase in revenue holds potential to increase the uptake of virtual power plants on the Swedish market, thus increasing stability in the power grid and easing the transition to renewable energy. / Då förnyelsebara energiresurser antas omfatta en större roll av den svenska elproduktionen inom kommande år, så kan detta leda till att frekvensfluktueringar i elnätet ökar. Detta sker på grund av att den oregelbundna elproduktionen från förnyelsebara energiresurser inte matchas med konsumtion. Om dessa fluktueringar inte hanteras kan det i sin tur leda till skadliga störningar inom elnätet. För att motverka detta och således stabilisera elnätet används diverse lösningar. Ett sätt att åstadkomma ökad stabilisering i elnätet är att låta privata aktörer kraftreglera. De privata aktörerna som står för kraftregleringen gör detta i utbyte mot ekonomisk kompensation, genom att delta i reservmarknader. Den reservmarknad som studerades inom detta examensarbete kallas Frequency Containment Reserve – Normal (FCR-N). I nuläget står vattenkraft för nästan all reglerad kraft inom den här marknaden. Men då behovet av kraftreglering antas öka inom kommande år så behövs nya teknologier studeras som kan bistå med kraftregleringen. Den studerade teknologin inom detta examensarbete var ett virtuellt kraftverk. Då inga virtuella kraftverk var i bruk i Sverige då denna uppsats skrevs fanns det osäkerheter kring hur man optimalt styr ett virtuellt kraftverk och de ekonomiska fördelarna som detta skulle kunna leda till. Detta examensarbete modellerade och optimerade ett virtuellt kraftverk ur ett vinstperspektiv. Det virtuella kraftverket var uppbyggt utav kylmaskiner, ljus, ventilationsfläktar och ett batterisystem. Deras kraftkonsumtion styrdes på ett sådant sätt som lätt de bidra till kraftreglering på reservmarknaden. För att kunna analysera de ekonomiska resultaten från det optimerade virtuella kraftverket, så byggdes en jämförelsemodell. Denna jämförelsemodell är baserad på en semistatisk linjär modell, vilket är det som examensarbetets industripartner Siemens använder. Den ekonomiska jämförelsens resultat påvisade att inkomsten från den optimerade modellen var minst 85% högre än den semistatiskt linjära modellen, inom de studerade scenarierna. Denna inkomstökning skulle potentiellt kunna öka användningen av virtuella kraftverk på den svenska reservmarknaden vilket i sin tur skulle medföra högre stabilitet på elnätet. Genom att öka stabiliteten på elnätet kan således förnyelsebara energiresurser i sin tur lättare implementeras.
32

Applications of battery energy storage to mitigate disturbances and uncertainties in power systems with high penetration of renewable energy resources

Sharma, Roshan 30 April 2021 (has links)
Solar photovoltaic (PV) is the fastest-growing energy resource. The price of energy generation from residential PV has dropped from $0.50 to $0.10 per kWh in the past decade. One challenge with this resource is that the amount of power available depends on the solar irradiance and temperature. Abrupt changes in solar irradiance can cause disturbances to the hosting electricity network and lead to voltage and frequency oscillations. The impact is more severe in a weak grid with high penetration of such resources. Evolving grid interconnection standards are imposing requirements to limit the impacts of these disturbances on the grid. Battery energy storage (BES) technology has also experienced a significant price drop (e.g., from $1100 to $156 per kWh for lithium-ion batteries) in the past decade. Therefore, complementary PV+BES solutions are increasingly considered. A BES of sufficient capacity equipped with appropriate controls can respond to both abrupt and long-term PV power variations. Properly formulating the problem and developing efficient control systems is crucial. These define the scope and objective of this research. This research develops two BES solutions. In the first one, the BES is co-located with the PV and connects to its dc output terminals. The BES controller ensures that the PV+BES system exhibits a desirable power ramp rate set by the user. In the second solution, the BES is not co-located with the PV. It detects the disturbances from their signatures on its locally measured signals and takes proper actions. An approach based on capacitor emulation combined with a droop mechanism is developed and optimally designed to provide dynamic and static supports. The BES can respond to the disturbances from more than one PV system and non-PV sources, such as load disturbances. The dissertation presents detailed modeling and control of the BES system. Optimal control techniques are developed to ensure robust and fast responses. For the simulation study, the proposed BES systems are implemented in a hybrid dc/ac study system and the effect on both dc and ac subsystems are investigated. The real-time results obtained by implementing the proposed controllers on laboratory-scale hardware prototypes are also presented.
33

Improved renewable energy power system using a generalized control structure for two-stage power converters

Kim, Rae-Young 28 September 2009 (has links)
The dissertation presents a generalized control structure for two-stage power converters operated in a renewable energy power system for smart grid and micro grid systems. The generalized control structure is based on the two-loop average-mode-control technique, and created by reconstructing the conventional control structure and feedback configuration. It is broadly used for both dc-dc and dc-ac power conversion based on the two-stage converter architecture, while offering several functionalities required for renewable energy power systems. The generalized control structure improves the performance and reliability of renewable energy power systems with multiple functionalities required for consistent and reliable distributed power sources in the applications of the smart grid and micro grid system. The dissertation also presents a new modeling approach based on a modification of the subsystem-integration approach. The approach provides continuous-time small-signal models for all of two-stage power converters in a unified way. As a result, a modeling procedure is significantly reduced by treating a two-stage power converter as a single-stage with current sinking or sourcing. The difficulty of linearization caused by time-varying state variables is avoided with the use of the quasi-steady state concept. The generalized control structure and modeling approach are demonstrated using the two-stage dc-dc and dc-ac power conversion systems. A battery energy storage system with a thermoelectric source and a grid-connected power system with a photovoltaic source are examined. The large-signal averaged model and small-signal model are developed for the two demonstrated examples, respectively. Based on the modeling results, the control loops are designed by using frequency domain analysis. Various simulations and experimental tests are carried out to verify the compensator designs and to evaluate the generalized control structure performance. From the simulation and experimental results, it is clearly seen that the generalized control structure improves the performance of a battery energy storage system due to the unified control concept. The unified control concept eliminates transient over-voltage or over-current, extra energy losses, power quality issues, and complicated decision processes for multiple-mode control. It is also seen that the generalized control structure improves the performance of a single-phase grid-connected system through increased voltage control loop bandwidth of the active ripple current reduction scheme. As a result of the increased loop bandwidth, the transient overshoot or undershoot of the dc-link voltage are significantly reduced during dynamic load changes. / Ph. D.
34

A High-Efficiency Grid-Tie Battery Energy Storage System

Qian, Hao 25 October 2011 (has links)
Lithium-ion based battery energy storage system has become one of the most popular forms of energy storage system for its high charge and discharge efficiency and high energy density. This dissertation proposes a high-efficiency grid-tie lithium-ion battery based energy storage system, which consists of a LiFePO4 battery based energy storage and associated battery management system (BMS), a high-efficiency bidirectional ac-dc converter and the central control unit which controls the operation mode and grid interface of the energy storage system. The BMS estimates the state of charge (SOC) and state of health (SOH) of each battery cell in the pack and applies active charge equalization to balance the charge of all the cells in the pack. The bidirectional ac-dc converter works as the interface between the battery pack and the ac grid, which needs to meet the requirements of bidirectional power flow capability and to ensure high power factor and low THD as well as to regulate the dc side power regulation. A highly efficient dual-buck converter based bidirectional ac-dc converter is proposed. The implemented converter efficiency peaks at 97.8% at 50-kHz switching frequency for both rectifier and inverter modes. To better utilize the dc bus voltage and eliminate the two dc bus bulk capacitors in the conventional dual-buck converter, a novel bidirectional ac-dc converter is proposed by replacing the capacitor leg of the dual-buck converter based single-phase bidirectional ac-dc converter with a half-bridge switch leg. Based on the single-phase bidirectional ac-dc converter topology, three novel three-phase bidirectional ac-dc converter topologies are proposed. In order to control the bidirectional power flow and at the same time stabilize the system in mode transition, an admittance compensator along with a quasi-proportional-resonant (QPR) controller is adopted to allow smooth startup and elimination of the steady-state error over the entire load range. The proposed QPR controller is designed and implemented with a digital controller. The entire system has been simulated in both PSIM and Simulink and verified with hardware experiments. Small transient currents are observed with the power transferred from rectifier mode to inverter mode at peak current point and also from inverter mode to rectifier mode at peak current point. The designed BMS monitors and reports all battery cells parameters in the pack and estimates the SOC of each battery cell by using the Coulomb counting plus an accurate open-circuit voltage model. The SOC information is then used to control the isolated bidirectional dc-dc converter based active cell balancing circuits to mitigate the mismatch among the series connected cells. Using the proposed SOC balancing technique, the entire battery storage system has demonstrated more capacity than the system without SOC balancing. / Ph. D.
35

A Coordinated Voltage Management Method Utilizing Battery Energy Storage Systems and Smart PV Inverters in Distribution Networks with High PV and Wind Penetrations

Alrashidi, Musaed Owehan 16 August 2021 (has links)
Electrical distribution networks face many operational challenges as various renewable distributed generation (DG), such as solar photovoltaic (PV) systems and wind, become part of their structure. Unlike conventional distribution systems, where the only unpredictable aspect is the load level, the intermittent nature of DG poses additional uncertainty levels for distribution system operators (DSO). The voltage quality problem considers the most restrictive issue that hinders high DG integration into distribution grids. Voltage deviates from the nominal grid voltage limits due to the excess power from the DG. DSOs are accustomed to improving the voltage profile by optimal adjustments of the on-load tap changers, voltage regulator taps and capacitor banks. Nevertheless, due to the frequent variability of the output energy from DG, these devices may fail in doing the needful. Battery energy storage systems (BESS) and smart PV inverter functionalities are regarded as promising solutions to promote the seamless integration of renewable resources into distribution networks. BESS are utilized to store the surplus energy during the high penetration of renewable DG that causes high voltage levels and discharge the stored energy when the distribution grid is heavily loaded, which leads to the low voltage levels. Smart PV inverters regulate the network voltage by controlling the reactive power injection or absorption at the inverter end. This dissertation proposes a management strategy that coordinates BESS and smart PV inverter reactive power capability to improve voltage quality in the distribution systems with high PV and wind penetrations. The proposed management method is based on a bi-level optimization algorithm consisting of upper and lower optimization levels. The proposed method determines the optimal location, capacity, numbers and BESS charging and discharging rates to support the distribution system voltage and to ensure optimal deployment of BESS. Case studies are conducted to evaluate the proposed voltage control method. The large size PV system and wind turbine impacts are studied and simulated on the modified IEEE-34 bus test feeder. In addition, the proposed method is applied to the modified IEEE low voltage test feeder to investigate the effectiveness of installing residential rooftop PV systems on the distribution system's voltage. Experimental results show promising outcomes of the proposed method in controlling the distribution networks' voltage. In addition, a day-ahead forecast of PV power output is developed in this dissertation to assist the DSOs to accurately predict the future amounts of PV energy available and reinforcing the decision-making process of batteries operation. Hybrid forecasting models are proposed based on machine learning algorithms, which utilize support vector regression and backpropagation neural network, optimized with three metaheuristic optimization algorithms, namely Social Spider Optimization (SSO), Particle Swarm Optimization (PSO) and Cuckoo Search Optimization (CSO). These algorithms are used to improve the predictive efficacy of the selected algorithms, where the optimal selection of their hyperparameters and architectures plays a significant role in yielding precise forecasting outcomes. / Doctor of Philosophy / The need for more renewable energy has grown significantly, and many countries are embracing these technologies. However, the integration of distributed generation (DG), such as PV systems and wind turbines, poses several operational problems to the distribution system. The voltage problem represents the most significant issue that needs to be addressed. The traditional voltage control equipment may not cope with the rapid fluctuation and may impact their service life. The continuous developments in the battery energy storage systems (BESS) and the smart PV inverter technologies result in increasing the hosting capacity of DG. BESS can store the excess power from the distributed generators and supply this energy to the grid for different operational objectives. On the other hand, the advanced PV inverter's reactive power capability can be exploited from which the grid can attain many benefits. This dissertation aims at providing a reliable control method to the voltage profile in distribution networks embedded with high PV and wind energy by optimal coordination between the operation of the BESS and the smart PV inverter. In addition, the solar forecasting can mitigate the uncertainty associated with PV system generation. In this dissertation, the PV power forecasting application is applied in the distribution system to control the voltage. Through utilizing PV power forecasting, the decision-making for battery operation can be upheld and reinforced. The BESS can store the surplus energy from the PV system as needed and supply it back in low PV power incidents. Experimental results indicate that proper coordination between the BESS and smart PV inverter is beneficial for distribution system operation that can seamlessly integrate PV and wind energy.
36

Powering Stability : Grid-Connected Batteries Influence on Peak Electricity Pricing

Holm, Emil, Shayeganfar, Parsa January 2024 (has links)
Battery Energy Storage Systems (BESSs) have become an increasingly popular feature of the electrical grid in the California ISO (CAISO) as a means to address the challenges posed by renewable energy variability and escalating peak demand. Due to their ability to reduce peak load demand on traditional generators and extend the benefits of the merit order effect, they have been theorized and claimed to reduce peak electricity prices. The purpose of this study is to test these claims within CAISO and understand what effects BESSs have had on peak electricity prices. Our findings show that there has been a significant decrease in prices after the introduction of BESSs into the grid although we found no significant effects of an increasing utilization of BESSs on peak electricity prices. We conclude that BESS utilization in CAISO has had no effect on peak electricity prices. We are contributing to the literature on the tangible market impacts of BESSs, highlighting the need for further empirical research in this domain.
37

Grid-connected micro-grid operational strategy evaluation : Investigation of how microgrid load configurations, battery energy storage system type and control can support system specification

Mancuso, Martin January 2018 (has links)
Operational performance of grid-connected microgrid with integrated solar photovoltaic (PV) electricity production and battery energy storage (BES) is investigated.  These distributed energy resources (DERs) have the potential to reduce conventionally produced electrical power and contribute to reduction of greenhouse gas emissions.  This investigation is based upon the DER’s techno-economic specifications and theoretical performance, consumer load data and electrical utility retail and distribution data.  Available literature provides the basis for DER specification and performance.  Actual consumer load profile data is available for residential and commercial consumer sector customers.  The electrical utility data is obtained from Mälarenergi, AB.  The aim is to investigate how to use simulations to specify a grid connected microgrid with DERs (PV production and a BES system) for two consumer sectors considering a range of objectives.  An open-source, MATLAB-based simulation tool called Opti-CE has successfully been utilized.  This package employs a genetic algorithm for multi-objective optimization.  To support attainment of one of the objectives, peak shaving of the consumer load, a battery operational strategy algorithm has been developed for the simulation.  With respect to balancing peak shaving and self-consumption one of the simulations supports specification of a commercial sector application with 117 kWp PV power rating paired with a lithium ion battery with 41.1 kWh capacity.  The simulation of this system predicts the possibility to shave the customer load profile peaks for the month of April by 20%.  The corresponding self-consumption ratio is 88%.  Differences in the relationship between the load profiles and the system performance have been qualitatively noted.  Furthermore, simulation results for lead-acid, lithium-ion and vanadium-redox flow battery systems are compared to reveal that lithium ion delivers the best balance between total annualized cost and peak shaving performance for both residential and commercial applications.
38

Design and Implementation of a Supervisory Controller for PV and Storage

Persson, Björn January 2018 (has links)
Battery energy storage systems are a key factor for enabling a continuous increase of the fraction of photovoltaics in the Swedish electricity grid. One big challenge is to utilise all potential services of such a storage system. The aim of this study was to improve the supervisory controller for an existing battery storage and photovoltaic solution marketed by the Swedish company Ferroamp AB. This has been done by developing a combined peak reduction and time-of-use bill management algorithm, together with a simulation and evaluation software for optimisation of algorithm parameters. The algorithms and tools were evaluated using an installation made by Ferroamp AB and Vattenfall Eldistribution AB as a case study. Sensitivity analyses has been performed on economic parameters and length of the algorithm training data set. Improvement of economic profit, in this case study, were 300 % compared to the currently used algorithm and 32 % compared to a conventional threshold peak reduction algorithm. Despite this improvement, the battery energy storage system is shown to be non-profitable, with the economic profit only covering 36 % of the investment costs, not taking interest rate into account. Like in many other studies, power storage was found more profitable than energy storage. An increase of the grid power tariff and the grid energy fee of 30 % to 40 % is found to make the system viable. One interesting finding is that by using the proposed optimal algorithm, 55 % of the cycle life of the battery storage is still accessible for other services when considering 10 years of economic depreciation time for the system.
39

A case study about the potential of battery storage in Culture house : Investigation on the economic viability of battery energy storage system with peak shaving & time-of-use application for culture house in Skellefteå.

Singh, Baljot January 2021 (has links)
The energy demand is steadily increasing, and the electricity sector is undergoing a severe change in this decade. The primary drivers, such as the need to decarbonize the power industry and megatrends for more distributed and renewable systems, are resulting in revolutionary changes in our lifestyle and industry. The power grid cannot be easily or quickly be upgraded, as investment decisions, construction approvals, and payback time are the main factors to consider. Therefore, new technology, energy storage, tariff reform, and new business models are rapidly changing and challenging the conventional industry. In recent times, industrial peak shaving application has sparked an increased interest in battery energy storage system (BESS).  This work investigated BESS’s potential from peak shaving and Time-of-use (TOU) applications for a Culture-house in Skellefteå. Available literature provides the knowledge of various BESS applications, tariff systems, and how battery degradation functions. The predicted electrical load demand of the culture-house for 2019 is obtained from a consultant company Incoord. The linear optimization was implemented in MATLAB using optimproblem function to perform peak shaving and time-of-use application for the Culture-hose BESS. A cost-optimal charging/discharging strategy was derived through an optimization algorithm by analyzing the culture-house electrical demand and Skellefteå Kraft billing system. The decisional variable decides when to charge/discharge the battery for minimum battery degradation and electricity purchase charges from the grid.   Techno-economic viability is analyzed from BESS investment cost, peak-power tariff, battery lifespan, and batter aging perspective. Results indicate that the current BESS price and peak-power tariff of Skellefteå Kraft are not suitable for peak shaving. Electricity bill saving is too low to consider TOU application due to high battery degradation. However, combining peak shaving & TOU does generate more profit annually due to additional savings from the electricity bill. However, including TOU also leads to higher battery degradation, making it not currently a viable application. A future scenario suggests a decrease in investment cost, resulting in a shorter payback period.  The case study also analyses the potential in the second-life battery, where they are purchased at 80 % State of Health (SoH) for peak shaving application. Second-life batteries are assumed to last until 70 % or 60 % before End of Life (EOL). The benefit-cost ratio indicates that second-life batteries are an attractive investment if batteries can perform until 60% end of life, it would be an excellent investment from an economic and sustainability perspective. Future work suggests integrating more BESS applications into the model to make BESS an economically viable project.
40

Chytré dobíjení EV a BESS pro zvýšení FV hostingové kapacity distribučních sítí / EV smart charging and BESS in increasing the PV hosting capacity of distribution networks

Filip, Robin January 2021 (has links)
Diplomová práce se zabývá dopadem nabíjení elektrických vozidel a bateriových úložišť na schopnost distribučních sítí nízkého napětí absorbovat fotovoltaické systémy. Převážně venkovské, příměstské a převážně městské regiony s různými stupni penetrace nekontrolovaně i kontrolovaně nabíjených elektromobilů jsou analyzovány Monte Carlo simulacemi. Hostingová kapacita je také analyzována, jestliže jsou elektrická vozidla jak nahrazena, tak doplněna domácími bateriovými úložišti. Práce je zakončena krátkou analýzou využitelnosti BESS.

Page generated in 0.1479 seconds