Optimal Combinations of Utility Level Renewable Generators for a Net Zero Energy Microgrid Considering Different Utility Charge Rates

High initial investment and the intermittent nature of resources are major challenges for large scale renewable generation. The size of photovoltaic (PV) and wind turbine (WT) farms in the microgrid needs optimized to avoid curtailment and to efficiently meet the demand of a power system. Battery energy storage systems (BESSs) may also be used to improve flexibility. This paper explores the optimal sizing for PV and wind generators, as well as a BESS at the utility level for a large grid-connected net zero energy (NZE) hybrid microgrid considering characteristics such as initial investment, levelized cost of energy (LCOE), operating costs, net present cost (NPC), and renewable fraction. Multi-objective formal optimizations were formulated as single objective problems with constraints and solved using the HOMER Pro computational engine. Ten optimizations with different utility charge rates are performed using actual data for the load profile, weather, and utility buy-back rates of Glasgow, KY. Simulation results demonstrated that various utility charge rates result in different optimal sizes for the solar PV and the WT farms, as well as for the BESS capacity

Microgrid system

Due to the growing awareness of the harmful impact of conventional fossil fuels and advancements in renewable energy technologies, microgrid has grown in popularity. This chapter aims to provide holistic learning of the microgrid system. This chapter is not only helpful for readers who are new to the world microgrid energy systems but also provide essential information to experts of this field. The chapter highlights the need and merits of adoption of microgrid systems while also highlighting the barriers in its implementation. The chapter also provides the various methods of categorization of microgrid while also emphasizing critical points of multiple categories. The different aspect of the deployment of microgrids, such as its architecture, mode of operations, control strategies, monitoring methods, protection schemes, and energy management strategies are categorically explained. The fundamental requirement of the protection system and its functions are described to provide the overview of protection schemes used in the microgrid in this chapter. Various protection schemes will be discussed in the other following chapter giving more emphasis on new protection strategies.https://www.springer.com/series/7818hj2021Electrical, Electronic and Computer Engineerin

Control Strategies of DC–DC Converter in Fuel Cell Electric Vehicle

There is a significant need to research and develop a compatible controller for the DC–DC converter used in fuel cells electric vehicles (EVs). Research has shown that fuel cells (FC) EVs have the potential of providing a far more promising performance in comparison to conventional combustion engine vehicles. This study aims to present a universal sliding mode control (SMC) technique to control the DC bus voltage under varying load conditions. Additionally, this research will utilize improved DC–DC converter topologies to boost the output voltage of the FCs. A DC–DC converter with a properly incorporated control scheme can be utilized to regulate the DC bus voltage–. A conventional linear controller, like a PID controller, is not suitable to be used as a controller to regulate the output voltage in the proposed application. This is due to the nonlinearity of the converter. Furthermore, this thesis will explore the use of a secondary power source which will be utilized during the start–up and transient condition of the FCEV. However, in this instance, a simple boost converter can be used as a reference to step–up the fuel cell output voltage. In terms of application, an FCEV requires stepping –up of the voltage through the use of a high power DC–DC converter or chopper. A control scheme must be developed to adjust the DC bus or load voltage to meet the vehicle requirements as well as to improve the overall efficiency of the FCEV. A simple SMC structure can be utilized to handle these issues and stabilize the output voltage of the DC–DC converter to maintain and establish a constant DC–link voltage during the load variations. To address the aforementioned issues, this thesis presents a sliding mode control technique to control the DC bus voltage under varying load conditions using improved DC–DC converter topologies to boost and stabilize the output voltage of the FCs

The Future of Power Storage in South Eastern Europe

The European Commission’s Joint Research Centre (JRC) and the Ministry of Energy and Industry of Albania held a joint workshop on the future role of energy storage in South Eastern Europe on 21 -22 October in Tirana. The workshop was attended by 40 specialists from academia, government, regulatory bodies, power industry and consultancies from both EU accession and candidate countries as well as from EU Member States. The participants actively discussed the technical, financial and regulatory challenges of the energy systems of the Western Balkans, and options of how these could be overcome. The event served as a forum for sharing and critically reflecting experience gained in Western Europe during the last decade. The workshop held in Tirana was part of the Enlargement and Integration Action. The present report summarizes the interventions of the participants, the discussions and conclusions of the workshop.JRC.F.6-Energy Technology Policy Outloo

Optimal planning and sizing of an autonomous hybrid energy system using multi stage grey wolf optimization

The continuous increase in energy demand and the perpetual dwindling of fossil fuel coupled with its environmental impact have recently attracted research focus in harnessing renewable energy sources (RES) across the globe. Representing the largest RES, solar and wind energy systems are expanding due to the growing evidence of global warming phenomena. However, variability and intermittency are some of the main features that characterize these RES as a result of fluctuation in weather conditions. Hybridization of multiple sources improves the system’s efficiency and reliability of supply due to the varying nature of the RES. Also, the unavailability of solar radiation (SR) and wind speed (WS) measuring equipment in the meteorological stations necessitates the development of prediction algorithms based on Artificial Intelligent (AI) techniques. This thesis presents an autonomous hybrid renewable energy system for a remote community. The hybrid energy system comprises of a photovoltaic module and wind turbine as the main source of energy. Batteries are used as the energy storage devices and diesel generator as a backup energy supply. A new hybrid Wavelet Transform and Adaptive Neuro-Fuzzy Inference System (WT-ANFIS) is developed for the SR prediction, while a hybrid Particle Swarm Optimization (PSO) and ANFIS (PSO-ANFIS) algorithm is developed for the WS prediction. The prediction accuracy of the proposed WT-ANFIS model was validated by comparison with the conventional ANFIS model, Genetic Algorithm (GA) and ANFIS (GA-ANFIS), and PSO-ANFIS models. The proposed PSO-ANFIS for the WS prediction is also compared with ANFIS and GA-ANFIS models. Also, Root Mean Square Error (RMSE), Correlation Coefficient (r) and Coefficient of Determination (R²) are used as statistical indicators to evaluate the performance of the developed prediction models. Additionally, a techno-economic feasibility analysis is carried out using the SR and WS data predicted to assess the viability of the hybrid solar-wind-battery-diesel system for electricity generation in the selected study area. Finally, a new cost-effective Multi Stage – Grey Wolf Optimization (MS-GWO) algorithm is applied to optimally size the different system components. This is aimed at minimizing the net present cost (NPC) while considering reliability and satisfying the load demand. MS-GWO is evaluated by comparison with PSO, GWO and PSO-GWO algorithms. From the results obtained, the statistical evaluators used for model performance assessment of the SR prediction shows that the hybrid WT-ANFIS model’s accuracy outperforms the PSO-ANFIS model by 65% RMSE and 9% R². Also, from the simulation results, the optimal configuration has an NPC of $1.01 million and cost of energy (COE)$0.110/kWh, with an operating cost of $4,723. The system is environmentally friendly with a renewable fraction of 98.3% and greenhouse gas emission reduction of 65%. Finally, a comparison is done between the proposed MS-GWO algorithm with the PSO, GWO and PSO-GWO algorithms. Based on this comparison, the proposed hybrid MS-GWO algorithm outperforms the individual PSO, GWO and PSO-GWO by 3.17%, 2.53% and 2.11% in terms of NPC and reduces the computational time by 53%, 46% and 36% respectively. Therefore, it can be concluded that the proposed MS-GWO technique can be applied for optimal sizing application globally

Control and estimation techniques applied to smart microgrids : a review

DATA AVAILABILITY : No data was used for the research described in the article.The performance of microgrid operation requires hierarchical control and estimation schemes that coordinate and monitor the system dynamics within the expected manipulated and control variables. Smart grid technologies possess innovative tools and frameworks to model the dynamic behaviour of microgrids regardless of their types, structures, etc. Various control and estimation technologies are reviewed for developing dynamic models of smart microgrids. The hierarchical system of a microgrid control consists of three architectural layers, primary, secondary and tertiary, which need to be supported by real-time monitoring and measurement environment of the system variables and parameters. Various control and estimation schemes have been devised to handle the dynamic performance of microgrids in the function of control layers requirement. Firstly, control schemes in the innovative grid environment are evaluated to understand the dynamics of the developed technologies. Six control technologies, linear, non-linear, robust, predictive, intelligent and adaptive, are mainly used to model the control design within the layer(s) regardless of the types of microgrids. Secondly, the estimation technologies are evaluated based on the state of variables, locations and modelling of microgrids that can efficiently support the performance of the controllers and operating microgrids. Finally, a future vision for designing hierarchical and architectural control techniques for the optimal operation of intelligent microgrids is also provided. Therefore, this study will serve as a fundamental conceptual framework to select a perfect optimal design modelling strategy and policy-making decisions to control, monitor and protect the innovative electrical network.http://www.elsevier.com/locate/rserhj2023Electrical, Electronic and Computer Engineerin

Система автоматизованого проектування гібридних установок

Робота публікується згідно наказу Ректора НАУ від 27.05.2021 р. №311/од "Про розміщення кваліфікаційних робіт здобувачів вищої освіти в репозиторії університету" . Керівник роботи: д. т. н., проф., зав. кафедри авіаційних комп’ютерно-інтегрованих комплексів, Синєглазов Віктор МихайловичОднією з основних тенденцій останніх десятиліть є пошук і впровадження альтернативних джерел енергії, в тому числі і сонячної енергії. Враховуючи, що цей вид енергії стає все більш привабливим і більш доступним з кожним роком, проблеми залежності від умов навколишнього середовища так само стають все більш актуальними. Так як окремі джерела енергії не в змозі забезпечити виконання вимог навантаження внаслідок невизначеності умов навколишнього середовища, слід розглядати гібридизацію системи, в сторону використання додаткових джерел енергії (в тому числі і резервних) в поєднанні з системами накопичення і зберігання енергії. Гібридна сонячна енергетична система – система, яка використовує відновлювану енергію сонця в комбінації з традиційними джерелами енергії (наприклад, дизель-генератори використовують дизельне паливо і в деяких випадках мають доступ до енергомережі для продажу і купівлі електричної енергії), а також із застосуванням системи зберігання і накопичення енергії. Дана система має ряд переваг, так як вона може використовуватися в незалежному режимі, що дозволяє впроваджувати її в місцях, де немає доступу до енергомережі, так і підвищувати загальну якість електроенергії при експлуатації у разі виникнення проблем на підстанція в режимі з підключенням до енергомережі. Отже, при побудові даного виду систем вимагається застосування методів багатокритеріальної структурно-параметричної оптимізації з дотриманням набору технічних і економічних обмежень, що потребує більш детального вивчення, побудови моделей процесів, які протікають в елементах ГСЕС і розроблення системи автоматизованого проектування

Sizing hybrid green hydrogen energy generation and storage systems (HGHES) to enable an increase in renewable penetration for stabilising the grid.

A problem that has become apparently growing in the deployment of renewable energy systems is the power grids inability to accept the forecasted growth in renewable energy generation integration. To support forecasted growth in renewable generation integration, it is now recognised that Energy Storage Technologies (EST) must be utilised. Recent advances in Hydrogen Energy Storage Technologies (HEST) have unlocked their potential for use with constrained renewable generation. HEST combines Hydrogen production, storage and end use technologies with renewable generation in either a directly connected configuration, or indirectly via existing power networks. A levelised cost (LC) model has been developed within this thesis to identify the financial competitiveness of the different HEST application scenarios when used with grid constrained renewable energy. Five HEST scenarios have been investigated to demonstrate the most financially competitive configuration and the benefit that the by-product oxygen from renewable electrolysis can have on financial competitiveness. Furthermore, to address the lack in commercial software tools available to size an energy system incorporating HEST with limited data, a deterministic modelling approach has been developed to enable the initial automatic sizing of a hybrid renewable hydrogen energy system (HRHES) for a specified consumer demand. Within this approach, a worst-case scenario from the financial competitiveness analysis has been used to demonstrate that initial sizing of a HRHES can be achieved with only two input data, namely “ the available renewable resource and the load profile. The effect of the electrolyser thermal transients at start-up on the overall quantity of hydrogen produced (and accordingly the energy stored), when operated in conjunction with an intermittent renewable generation source, has also been modelled. Finally, a mass-transfer simulation model has been developed to investigate the suitability of constrained renewable generation in creating hydrogen for a hydrogen refuelling station

Opening of Ancillary Service Markets to Distributed Energy Resources: A Review

Electric power systems are moving toward more decentralized models, where energy generation is performed by small and distributed power plants, often from renewables. With the gradual phase out from fossil fuels, however, Distribution Energy Resources (DERs) are expected to take over in the provision of all regulation services required to operate the grid. To this purpose, the opening of national Ancillary Service Markets (ASMs) to DERs is considered an essential passage. In order to allow this transition to happen, current opportunities and barriers to market participation of DERs must be clearly identified. In this work, a comprehensive review is provided of the state-of-the-art of research on DER integration into ASMs. The topic at hand is analyzed from different perspectives. First, the current situation and main trends regarding the reformation processes of national ASMs are analyzed to get a clear picture of the evolutions expected and adjustment required in the future, according to the scientific community. Then, the focus is moved to the strategies to be adopted by aggregators for the effective control and coordination of DERs, exploring the challenges posed by the uncertainties affecting the problem. Coordination schemes between transmission and distribution system operators, and the implications on the grid infrastructure operation and planning, are also investigated. Finally, the review deepens the control capabilities required for DER technologies to perform the needed control actions