Planning of Smart Microgrids with High Renewable Penetration Considering Electricity Market Conditions

In this paper, a new method for optimal sizing of distributed generation (DG) is presented in order to minimize electricity costs in smart microgrids (MGs). This paper presents a study of the effect of wholesale electricity market on smart MGs. The study was performed for the Ekbatan residential complex which includes three smart MGs considering high penetration of renewable energy resources and a 63/20 kV substation in Tehran, Iran. The role of these smart MGs in the pool electricity market is a price maker, and a game-theoretical (GT) model is applied for their bidding strategies. The objective cost function considers different cost parameters in smart MGs, which are optimized using particle swarm optimization (PSO). The results show that applying this method is effective for economic sizing of DGs.© 2019 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

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

An Overview of Modeling Approaches Applied to Aggregation-Based Fleet Management and Integration of Plug-in Electric Vehicles †

The design and implementation of management policies for plug-in electric vehicles (PEVs) need to be supported by a holistic understanding of the functional processes, their complex interactions, and their response to various changes. Models developed to represent different functional processes and systems are seen as useful tools to support the related studies for different stakeholders in a tangible way. This paper presents an overview of modeling approaches applied to support aggregation-based management and integration of PEVs from the perspective of fleet operators and grid operators, respectively. We start by explaining a structured modeling approach, i.e., a flexible combination of process models and system models, applied to different management and integration studies. A state-of-the-art overview of modeling approaches applied to represent several key processes, such as charging management, and key systems, such as the PEV fleet, is then presented, along with a detailed description of different approaches. Finally, we discuss several considerations that need to be well understood during the modeling process in order to assist modelers and model users in the appropriate decisions of using existing, or developing their own, solutions for further applications

Optimized siting and sizing of distribution-network-connected battery energy storage system providing flexibility services for system operators

This paper develops a two-stage model to site and size a battery energy storage system in a distribution network. The purpose of the battery energy storage system is to provide local flexibility services for the distribution system operator and frequency containment reserve for normal operation (FCR-N) for the transmission system operator. In the first stage, the priority is to fulfil the flexibility needs of the distribution system operator by managing congestions or interruptions of supply in the local network. Thus, the first stage allocates the battery to ensure reliable electricity supply in the local distribution network. The minimum required size of the battery is also determined in the first stage. The second stage optimally sizes the battery energy storage system to boost the profit by providing frequency containment reserve for normal operation. The first and second stages both solve stochastic optimization problems to design the battery energy storage system. However, the first stage considers worst-case scenarios while the second stage utilizes the most probable scenarios derived from the historical data. To validate the proposed model, real-world data from the years 2021 and 2022 in Finland are employed. The battery placement is conducted for both the IEEE 33-bus system and a Finnish case study. The profitability of the model is compared across different cases for the Finnish case study. Finally, the paper assesses the impacts of cycle aging on the battery's total profit.© 2023 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).fi=vertaisarvioitu|en=peerReviewed

optimizing the operation of energy storage using a non linear lithium ion battery degradation model

Abstract Given their technological and market maturity, lithium-ion batteries are increasingly being considered and used in grid applications to provide a host of services such as frequency regulation, peak shaving, etc. Charging and discharging these batteries causes degradation in their performance. Lack of data on degradation processes combined with requirement of fast computation have led to over-simplified models of battery degradation. In this work, the recent experimental evidence that demonstrates that degradation in lithium-ion batteries is non-linearly dependent on the operating conditions is incorporated. Experimental aging data of a commercial battery have been used to develop a scheduling model applicable to the time constraints of a market model. A decomposition technique that enables the developed model to give near-optimal results for longer time horizons is also proposed

Energy Storage and Green Hydrogen Systems in Electricity Markets: A Modelling and Optimization Framework with Degradation and Uncertainty Considerations

Mención Internacional en el título de doctorThe increasing penetration of renewable energy in electrical systems requires advances in increasing their controllability. Energy Storage Systems (ESSs) are one of the solutions, since they allow the management of generated energy. Green hydrogen production systems, on the other hand, can utilize electricity to produce hydrogen. This energy carrier which can be sold for revenue generation and can be produced using Alkaline Electrolyzers (AELs). To coordinate these systems in renewable energy plants, advanced control techniques are needed. Complex processes such as degradation, partial loading and the effect of uncertainties must be considered. These considerations add to the complexity, which can obstruct control process, hence a simplistic formulation is required. This dissertation addresses this issue by implementing the effect of both ESS and AEL degradation into short-term planning keeping a linear formulation. Moreover, electrolyzer partial loading effect and operational states are also considered. Novel approaches in their inclusion into short-term planning for electricity market participation are proposed, analyzing their long-term economical significance. Due to the nature of spot electricity markets, which require the commitment of energy delivery beforehand, the uncertainty of renewable source and electricity prices may affect the performance of the system. Various stochastic approaches for short-term optimization are evaluated, with the proposal of novel strategies. The long-term impact of including risk-aware strategies is also analyzed in a simulation framework, whose results indicate that conservative approaches do not necessarily yield better outcomes. The present study commences with the modelling and formulation of a standalone ESS participating in the day-ahead market. A renewable energy source is incorporated into this model, creating a Hybrid Farm (HF) for multi-market participation. Lastly, a green hydrogen production system is also integrated, allowing the involvement in the hydrogen market. A novel algorithm for operation under uncertainties is proposed, which has been found to outperform a classical Montecarlo approach. Throughout the research, Python was employed as the programming language of choice. The generated code has been uploaded to a public repository. Real historical data was used to validate the findings and provide a more realistic representation of the systems under study.Programa de Doctorado en Ingeniería Eléctrica, Electrónica y Automática por la Universidad Carlos III de MadridPresidenta: Mónica Chinchilla Sánchez.- Secretario: Joaquín Eloy-García Carrasco.- Vocal: Pedro Vicente Jover Rodrígue

Evaluation of renewable energy generation and storage for industrial buildings

This research focuses on the financial aspects of the underutilised industrial renewable energy generation and storage market in Australia, where the developed methodology is applied to two distribution warehouses and a large energy consuming manufacturer. Throughout Australia the residential and utility scale renewable energy market is booming, however the industrial market has been lagging behind at a fraction of the residential generation capacity in 2020. This lack of uptake in the industrial market is attributed to perceived costs and lack of industry knowledge. This research simplifies the results of solar PV and energy storage design into key financial metrics that communicate the optimal year of installation for a business. To achieve this a methodology was developed to process the energy metering data from the business to drive renewable system design for a balance of generation output and capital cost for installation years 2021, 2025 and 2030. These systems are simulated with System Advisor Model (SAM) using location specific weather data and projected electricity cost rises by state up to 2030. The results are used to size energy storage systems of 4 chemistry types, pairing with solar PV while balancing simple payback and net present value. The resulting solar PV systems achieved a simple payback period ranging from 4 years in 2021 down to under 2 years in 2030 while systems equipped with energy storage typically doubled the simple payback period. Leveraging the differences in energy storage chemistries altered which storage technology had the lowest Levelized Cost of Electricity (LCOE) with lithium-ion the cheapest in 2021 but changing to Vanadium Redox by 2030. Collaborating with industry partners increases renewables penetration into the medium scale market by improving participation and simplifying complex designs, while informing what key objectives the industry requires to commit to a sustainable and renewable energy future

Prospects for Electric Mobility: Systemic, Economic and Environmental Issues

The transport sector, which is currently almost completely based on fossil fuels, is one of the major contributors to greenhouse gas emissions. Heading towards a more sustainable development of mobility could be possible with more energy efficient automotive technologies such as battery electric vehicles. The number of electric vehicles has been increasing over the last decade, but there are still many challenges that have to be solved in the future. This Special Issue “Prospects for Electric Mobility: Systemic, Economic and Environmental Issues” contributes to the better understanding of the current situation as well as the future prospects and impediments for electro mobility. The published papers range from historical development of electricity use in different transport modes and the recent challenges up to future perspectives