Enhancing Self-Consumption Ratio in a Smart Microgrid by Applying a Reinforcement Learning-Based Energy Management System

Опубликована: Янв. 1, 2024

This study presents an updated version of the CityLearn Gym environment by adding a stochastic vehicle-to-building model. To this end, EVs are modeled as local mobile storage. Indeed, model is developed to evaluate random behavior considering their uncertainties. Then, integrated within use reinforcement learning-based energy management system control and optimize smart microgrid's consumption storage systems. A real-world microgrid in Norway has been utilized provide flexibility enhancing self-energy solar generation finding optimal policy for systems which batteries EVs. The proposed designed using soft actor-critic (SAC) algorithm coordinate among different flexible sources defining priority resources direct charging signals. Three scenarios investigated shared scenario PV can be between buildings had best performance. performance evaluated five indicators. results demonstrate that self-consumption ratio increased up 11% daily peak power reduced 21% compared baseline RBC.

Язык: Английский

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Renewable energy allocation in Multi-Owned Buildings for Sustainable Transition: A novel Evidence-Based Decision-Making framework

Energy and Buildings, Год журнала: 2024, Номер 320, С. 114601 - 114601

Опубликована: Июль 26, 2024

Adopting Renewable Energy Systems (RES) in Multi-Owned Buildings (MOBs) is critical for achieving sustainability goals, yet the equitable allocation of energy from a jointly-owned RES to individual apartments remains overlooked practice and literature. Current practices, rooted models common cost allocation, fail address dynamic traits disregard entitlement each apartment, necessitating tailored approach renewable MOBs. This paper emphasises introduces novel, evidence-based decision-making framework assessing nine distinct their suitability diverse MOB typologies, characterised by physical social factors, presents ranked list. Our findings reveal extensive variation model depending on building typology. Equal minimised financial disparities, while demand-based was significantly effective older, mid-rise buildings with fewer tenants. Conversely, flat-fee found unsuitable regardless type. Furthermore, study demonstrates that suitable typology may not always align objectives installation, thus endorsing an 'objective proximity' analysis. The proposed serves as valuable guide stakeholders, including owners' corporations, policymakers, industries, make well-informed decisions smooth transition energy. It lays foundation potential expansion other types underscoring necessity adaptive policies promoting adoption.

Язык: Английский

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Impact of Electric Vehicles Consumption on Energy Efficient and Self-Sufficient Performance in Building: A Case Study in the Brazilian Amazon Region

Energies, Год журнала: 2024, Номер 17(16), С. 4060 - 4060

Опубликована: Авг. 16, 2024

The growth of electric vehicles (EVs) and their integration into existing future buildings bring new considerations for energy efficiency (EE) balance when combined with renewable energy. However, an label, such as Near Zero Energy Building (NZEB) or Positive (PEB), the introduction EVs may result in declassification EE label due to additional required charging infrastructure. This underscores increasing relevance demand-side management techniques effectively manage utilize consumption generation buildings. paper evaluates influence vehicle (EV) on NZEB/PEB-labeled Brazilian Labeling Program (PBE Edifica). Utilizing on-site surveys, computational modeling, thermos-energetic analysis software tools OpenStudio v. 1.1.0 EnergyPlus 9.4.0, classification was conducted a building city Belem, State Para, Brazil. Subsequently, power flow simulations employing probabilistic models Monte Carlo approaches were executed OpenDSS 10.0.0.2 examine impact EV integration, both without implementation techniques. Analyses using labeling methodology demonstrated that has level C NZEB self-sufficiency classification. assessment building’s total base (current) scenario carried out two scenarios, (2) (1) supply management. Scenario 01 generated 69.28% increase consumption, reducing D resulting loss class. 02 resulted smaller 40.50%, guaranteed return class lost 1, but it not enough C. results highlight need immediate comprehensive strategies, findings show scenarios present difference 41.55% consumption. Nonetheless, these strategies are if other restrictions measures applied systems.

Язык: Английский

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AI-driven sustainable cities: A Nordic-inspired requirement framework

SHS Web of Conferences, Год журнала: 2024, Номер 198, С. 03001 - 03001

Опубликована: Янв. 1, 2024

This paper examines the integration of AI and data technologies into sustainable urban development, emphasizing Norway's unique cultural environmental context. It first explores how concepts like trust sustainability inform planning operations. Then, study assesses AI's potential to enhance and, through case studies, it identifies challenges opportunities in adopting these technologies. Finally, proposes a Nordic requirement framework for integration, promoting aligned with values adaptable broader European contexts.

Язык: Английский

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Designing Tariff for Charging Electric Vehicles at Home with Equity in Mind – The Tripartite Tariff

Sustainable Cities and Society, Год журнала: 2024, Номер unknown, С. 106018 - 106018

Опубликована: Ноя. 1, 2024

Язык: Английский

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Evaluation of annual and temporal photovoltaic (PV) surplus energy in industrial buildings: A Case study of 36 industrial parks in Wuhan, China

Energy and Buildings, Год журнала: 2024, Номер unknown, С. 115193 - 115193

Опубликована: Дек. 1, 2024

Язык: Английский

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