Meshed microgrids have been used in a plethora of specialised applications that demand increased system resilience, from data centres to the international space station. When resilience maximisation ...is the desideratum, topology design is the fundamental factor determining the overall system performance. Very few published papers on this problem are found in literature and they take into consideration partial available topologies, or they fail to quantify resilience or assess microgrid stability. To address these gaps on microgrid topology planning (MTP), this paper proposes a holistic optimal topology design framework, comprised of six stages: (a) graph generator to extract all possible connected, non-isomorphic networks for a given number of nodes, (b) optimal asset positioning upon each generated graph using mixed-integer linear programming, (c) small-signal stability assessment and (d) post-outage flow matrix calculation for each microgrid to quantify repercussions from fault/damage of all interconnecting lines, (e) quantification of resilience metrics originally applied to distribution systems to assess vulnerability and criticality of each line, along with classic graph-theoretical indicators and finally, (f) aggregation of said metrics to rank the produced microgrid topologies. The proposed methodology is evaluated through detailed discrete simulations to assess its efficacy and the dynamic stability of the optimal microgrid topology.
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•A novel 5-step resilient topology design for isolated DC microgrids is presented.•Assets are optimally sized and positioned on buses with the focus on resilience.•Small-signal stability check is included to identify inherent topology instability.•Microgrid resilience is quantified by metrics deriving from distribution grids.•The superior performance of the optimal topology is proven under worst-case outages.
On becoming a commodity, Microgrids (MGs) have started gaining ground in various sizes (e.g., nanogrids, homegrids, etc.) and forms (e.g., local energy communities) leading an exponential growth in ...the respective sector. From demanding deployments such as military bases and hospitals, to tertiary and residential buildings and neighborhoods, MG systems exploit renewable and conventional generation assets, combined with various storage capabilities to deliver a completely new set of business opportunities and services in the context of the Smart Grid. As such systems involve economic, environmental and technical aspects, their performance is quite difficult to evaluate, since there are not any standards that cover all of these aspects, especially during operational stages. Towards allowing an holistic definition of a MG performance, for both design and operational stages, this paper first introduces a complete set of Key Performance Indicators to measure holistically the performance of a MG’s life cycle. Following, focusing on the MG’s day-to-day operation, a data-driven assessment is proposed, based on dynamic metrics, custom made reference models, and smart meter data, in order to be able to extract its operational performance. Two different algorithmic implementations (i.e., Dynamic Time Warping and t-distributed Stochastic Neighbor Embedding) are used to support the methodology proposed, while real-life data are used from a small scale MG to provide the desired proof-of-concept. Both algorithms seem to correctly identify days and periods of not optimal operation, hence presenting promising results for MG performance assessment, that could lead to a MG Performance Classification scheme.
Space mission cost and feasibility depend mainly on the size and mass of the payload. This paper investigates the optimal photovoltaic (PV) array and battery size and mass for an islanded PV-battery ...powered space microgrid (MG) at the lunar south pole. The PV arrays are considered to be installed on top of towers to increase solar energy harvesting. Considering the dependency of the generated power from PV arrays on the tower height, different tower heights of 10, 50, and 100 m are investigated. The paper presents the methodology to estimate the available power from the PV system using the information of illumination time-series at the location of potential sites with different tower heights. Besides, considering the power demand of several power-consuming units at different operating states, the power demand profile of the lunar base is generated. The optimal sizing of the PV and battery system for a 1-year horizon, without considering battery degradation, results in a total mass of approximately <inline-formula> <tex-math notation="LaTeX">1.5 \times 10^{5}~\text{kg} </tex-math></inline-formula> to <inline-formula> <tex-math notation="LaTeX">3.5 \times 10^{5}~\text{kg} </tex-math></inline-formula> with a tower height of 10 m depending on the solar illumination profiles at different sites. For a 5-year optimization horizon of the same sites with 10 m tower height and considering the battery yearly capacity degradation, total system mass ranges approximately from <inline-formula> <tex-math notation="LaTeX">\mathrm {2 \times 10^{5}~kg} </tex-math></inline-formula> to <inline-formula> <tex-math notation="LaTeX">5.5 \times 10^{5}~\text{kg} </tex-math></inline-formula>. Although increasing the tower height may considerably reduce the total size and mass of the battery and PV system, the mass of the PV tower will increase. Thus, a satisfactory trade-off in selecting the site location and tower height is required. In this regard, 15 highly illuminated sites at different locations and with different PV tower heights are assessed in this paper. To improve the reliability and flexibility of the power system, the multi-microgrid (MMG) concept is deployed to distribute the power-consuming units of the base among different MGs having their local energy production and storage systems. Finally, based on the total power demand served at a candidate site and the corresponding total system mass, a criterion, mass-per-unit-load (MPUL), is used to identify the sites that serve the highest power demand with less total system mass.
Several space organizations have been planning to establish a permanent, manned base on the Moon in recent years. Such an installation demands a highly reliable electrical power system (EPS) to ...supply life support systems and scientific equipment and operate autonomously in a fully self-sufficient manner. This paper explores various technologies available for power generation, storage, and distribution for space microgrids on the Moon. Several factors affecting the cost and mass of the space missions are introduced and analysed to provide a comprehensive comparison among the available solutions. Besides, given the effect of base location on the design of a lunar electrical power system and the mission cost, various lunar sites are introduced and discussed. Finally, the control system requirements for the reliable and autonomous operation of space microgrids on the Moon are presented. The study is complemented by discussing promising future technological solutions that could be applied upon a lunar microgrid.
In recent years, the growing use of Intelligent Personal Agents in different human activities and in various domains led the corresponding research to focus on the design and development of agents ...that are not limited to interaction with humans and execution of simple tasks. The latest research efforts have introduced Intelligent Personal Agents that utilize Natural Language Understanding (NLU) modules and Machine Learning (ML) techniques in order to have complex dialogues with humans, execute complex plans of actions and effectively control smart devices. To this aim, this article introduces the second generation of the CERTH Intelligent Personal Agent (CIPA) which is based on the RASA framework and utilizes two machine learning models for NLU and dialogue flow classification. CIPA-Generation B provides a dialogue-story generator that is based on the idea of adjacency pairs and multiple intents, that are classifying complex sentences consisting of two users’ intents into two automatic operations. More importantly, the agent can form a plan of actions for implicit Demand-Response and execute it, based on the user’s request and by utilizing AI Planning methods. The introduced CIPA-Generation B has been deployed and tested in a real-world scenario at Centre’s of Research & Technology Hellas (CERTH) nZEB SmartHome in two different domains, energy and health, for multiple intent recognition and dialogue handling. Furthermore, in the energy domain, a scenario that demonstrates how the agent solves an implicit Demand-Response problem has been applied and evaluated. An experimental study with 36 participants further illustrates the usefulness and acceptance of the developed conversational agent-based system.
In 2020, residential sector loads reached 25% of the overall electrical consumption in Europe and it is foreseen to stabilise at 29% by 2050. However, this relatively small increase demands, among ...others, changes in the energy consuming behaviour of households. To achieve this, Demand Response (DR) has been identified as a promising tool for unlocking the hidden flexibility potential of residential consumption. In this work, a holistic incentive-based DR framework aiming towards load shifting is proposed for residential applications. The proposed framework is characterised by several innovative features, mainly the formulation of the optimisation problem, which models user satisfaction and the economic operation of a distributed household portfolio, the customised load forecasting algorithm, which employs an adjusted Gradient Boosting Tree methodology with enhanced feature extraction and, finally, a disaggregation tool, which considers electrical features and time of use information. The DR framework is first validated through simulation to assess the business potential and is then deployed experimentally in real houses in Northern Greece. Results demonstrate that a mean 1.48% relative profit can be achieved via only load shifting of a maximum of three residential appliances, while the experimental application proves the effectiveness of the proposed algorithms in successfully managing the load curves of real houses with several residents. Correlations between market prices and the success of incentive-based load shifting DR programs show how wholesale pricing should be adjusted to ensure the viability of such DR schemes.
As microgrids have gained increasing attention over the last decade, more and more applications have emerged, ranging from islanded remote infrastructures to active building blocks of smart grids. To ...optimally manage the various microgrid assets towards maximum profit, while taking into account reliability and stability, it is essential to properly schedule the overall operation. To that end, this paper presents an optimal scheduling framework for microgrids both for day-ahead and real-time operation. In terms of real-time, this framework evaluates the real-time operation and, based on deviations, it re-optimises the schedule dynamically in order to continuously provide the best possible solution in terms of economic benefit and energy management. To assess the solution, the designed framework has been deployed to a real-life microgrid establishment consisting of residential loads, a PV array and a storage unit. Results demonstrate not only the benefits of the day-ahead optimal scheduling, but also the importance of dynamic re-optimisation when deviations occur between forecasted and real-time values. Given the intermittency of PV generation as well as the stochastic nature of consumption, real-time adaptation leads to significantly improved results.
Alternating current (AC) microgrids are expected to operate as active components within smart distribution grids in the near future. The high penetration of intermittent renewable energy sources and ...the rapid electrification of the thermal and transportation sectors pose serious challenges that must be addressed by modern distribution system operators. Hence, new solutions should be developed to overcome these issues. Microgrids can be considered as a great candidate for the provision of ancillary services since they are more flexible to coordinate their distributed generation sources and their loads. This paper proposes a method for compensating microgrid power factor and loads asymmetries by utilizing advanced functionalities enabled by grid tied inverters of photovoltaics and energy storage systems. Further, a central controller has been developed for adaptively regulating the provision of both reactive power and phase balancing services according to the measured loading conditions at the microgrid’s point of common coupling. An experimental validation with a laboratory scale inverter and a real time hardware in the loop investigation demonstrates that the provision of such ancillary services by the microgrid can significantly improve the operation of distribution grids in terms of power quality, energy losses and utilization of available capacity.
A Comprehensive Review on Small Satellite Microgrids Yaqoob, Mohammad; Lashab, Abderezak; Vasquez, Juan C. ...
IEEE transactions on power electronics,
2022-Oct., 2022-10-00, Letnik:
37, Številka:
10
Journal Article
Recenzirano
Odprti dostop
The small satellite (SmallSat) industry has recorded incredible growth recently. Within this class, among mini-, micro-, and nanosatellites, the cube satellite (CubeSat) is primed for an explosion of ...growth. These satellites are fascinating for remote sensing, Earth observation, and scientific applications. Remarkable attention from the space operators makes it valuable because of its low cost, cubic shape, less manufacturing time, lightweight, and modular structure. Among the various subsystems comprising the SmallSat, the electrical power system (EPS) is the most crucial one because unreliable power supply to the rest is most of the time detrimental to the mission. The EPS is formed by electrical sources, storage units, and loads, all interconnected via different power converters, the operation of which must be closely orchestrated to accomplish efficient use of photovoltaic power, optimal battery management, and resilient power delivery. At the same time, the EPS design must address a series of challenges such as size restrictions, high power density, and harsh space environments (e.g., atomic oxygen, radiation, and extreme temperatures), which significantly impact the EPS electrical and electronic equipment. In terms of power systems, a SmallSat EPS can be considered a space microgrid owing to coordination and control of distributed generation, storage, and loads in a small-scale electrical network. From this point of view, this article reviews and explores SmallSat microgrid's research developments, energy transfer and architectures, converter topologies, latest technologies, main challenges, and some potential solutions, which will enable building a more robust, resilient, and efficient EPS. The research gaps and future developments are underlined before this article is concluded.
Accurately forecasting power generation in photovoltaic (PV) installations is a challenging task, due to the volatile and highly intermittent nature of solar-based renewable energy sources. In recent ...years, several PV power generation forecasting models have been proposed in the relevant literature. However, there is no consensus regarding which models perform better in which cases. Moreover, literature lacks of works presenting detailed experimental evaluations of different types of models on the same data and forecasting conditions. This paper attempts to fill in this gap by presenting a comprehensive benchmarking framework for several analytical, data-based and hybrid models for multi-step short-term PV power generation forecasting. All models were evaluated on the same real PV power generation data, gathered from the realisation of a small scale pilot site in Thessaloniki, Greece. The models predicted PV power generation on multiple horizons, namely for 15 min, 30 min, 60 min, 120 min and 180 min ahead of time. Based on the analysis of the experimental results we identify the cases, in which specific models (or types of models) perform better compared to others, and explain the rationale behind those model performances.
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