Multi-objective optimization study of regional integrated energy systems coupled with renewable energy, energy storage, and inter-station energy sharing

Renewable Energy, Год журнала: 2024, Номер 225, С. 120328 - 120328

Опубликована: Март 12, 2024

Язык: Английский

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A review on battery energy storage systems: Applications, developments, and research trends of hybrid installations in the end-user sector

Journal of Energy Storage, Год журнала: 2024, Номер 86, С. 111192 - 111192

Опубликована: Март 16, 2024

The sharp and continuous deployment of intermittent Renewable Energy Sources (RES) especially Photovoltaics (PVs) poses serious challenges on modern power systems. Battery Storage Systems (BESS) are seen as a promising technology to tackle the arising technical bottlenecks, gathering significant attention in recent years. Particularly, they gaining increasing interest context hybrid PV-BESS installations, enabling various benefits for both residential non-residential end-users. aim this work is provide detailed overview BESS-related aspects, focusing applications, developments, research trends installations end-user sector. To extent, an explicit provided, Distributed Resource, while description their available configurations, presented. Additionally, beneficial effect BESS controllable RES integration importance Flexibility through Demand Side Management (DSM) also extensively discussed, along with operation within DSM framework. considered key further exploitation due specific characteristics. Moreover, main dimensions identified topics receiving substantial current literature. Notably, noteworthy amount papers examined, categorised into four topics, namely Techno-economic Analysis, Operational Control, System Sizing, Response, consisting diverse subjects. Finally, each paper provided scope thoroughly examining most important perspectives existing literature, identifying any possible gaps, providing remarks future directions.

Язык: Английский

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Energy management of the hybrid power system based on improved intelligent Perturb and Observe control using battery storage systems

Energy Reports, Год журнала: 2024, Номер 11, С. 1611 - 1626

Опубликована: Янв. 21, 2024

With the increase in demand for electrical energy, renewable energy systems have become unable to meet this demand, especially difficult weather conditions, so hybrid (HESs) been resorted as a suitable solution. These HESs require special control manage energy. In work, an HES consisting of diesel generator system, storage and photovoltaic (PV) system will be implemented solve problem inability provide conditions. The proposed is great importance industrial economic field because it provides solution compensate excess with possibility storing using at critical times. efficient management algorithm (EMA) designed obtain significant from sun, protect battery, store prevent power shortages grid, use first contribution paper lies improving effectiveness Perturb Observe (P&O) maximum point tracking fuzzy logic (FLC), strategy contributes significantly obtaining PV greatly increasing its durability. stored batteries harnessed extend "off" time avoid any possible problems. EMA effective organizing work between various parts HES. latter was Matlab environment completion comparative study classical P&O technique based on FLC technique, these suggested solutions proved their improved reliability face climate change increased load demand.

Язык: Английский

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Flexible coupling and grid-responsive scheduling assessments of distributed energy resources within existing zero energy houses

Journal of Building Engineering, Год журнала: 2024, Номер 87, С. 109047 - 109047

Опубликована: Март 16, 2024

Язык: Английский

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Exploring the impacts of heterogeneity and stochasticity in air-conditioning behavior on urban building energy models

Sustainable Cities and Society, Год журнала: 2024, Номер 103, С. 105285 - 105285

Опубликована: Фев. 20, 2024

Язык: Английский

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Demand flexibility and cost-saving potentials via smart building energy management: Opportunities in residential space heating across the US

Advances in Applied Energy, Год журнала: 2024, Номер 14, С. 100171 - 100171

Опубликована: Март 6, 2024

Leveraging demand-side flexibility resources (e.g., buildings) is a crucial and cost-effective strategy for addressing the operational infrastructure-related challenges in power grids pursuing deep decarbonization with high renewable energy penetration. However, demand opportunities financial benefits residential space heating, which are sizeable resources, through emerging building management solutions (i.e., smart control phased change material (PCM) thermal storage) across US not fully understood. In this paper, we systematically assess cost-saving/revenue potentials heating detailed building-level simulations five consecutive years at 5-min temporal resolution 20 metro areas high-heating-demand regions of US. The results show degree synergy between PCM storage control, enables substantial potential, reaching 98.5% peak load shifting, electricity 338.3% cost reductions, By achieving such performance, adopting financially viable 50% tested areas. reveal that further enhanced by higher volatilities prices. Active has lower efficiency but much than passive storage. Based on findings, recommendations integrating systems within provided.

Язык: Английский

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Design and operational strategy optimization of a hybrid electric heating system with phase change materials for energy storage in nearly zero energy buildings

Journal of Energy Storage, Год журнала: 2024, Номер 82, С. 110528 - 110528

Опубликована: Янв. 18, 2024

Язык: Английский

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Deep and Machine Learning Models to Forecast Photovoltaic Power Generation

Energies, Год журнала: 2023, Номер 16(10), С. 4097 - 4097

Опубликована: Май 15, 2023

The integration and management of distributed energy resources (DERs), including residential photovoltaic (PV) production, coupled with the widespread use enabling technologies such as artificial intelligence, have led to emergence new tools, market models, business opportunities. accurate forecasting these has become crucial decision making, despite data availability reliability issues in some parts world. To address challenges, this paper proposes a deep machine learning-based methodology for PV power forecasting, which includes XGBoost, random forest, support vector regressor, multi-layer perceptron, LSTM-based tuned introduces ConvLSTM1D approach task. These models were evaluated on univariate time-series prediction low-volume production across various forecast horizons. proposed benchmarking analysis considers technical economic impacts, can provide valuable insights decision-making tools resources. results indicate that forest model approaches yielded most performance, demonstrated by lowest RMSE, MAPE, MAE different scenarios proposed.

Язык: Английский

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Many-objective day-ahead optimal scheduling of residential flexible loads integrated with stochastic occupant behavior models

Applied Energy, Год журнала: 2023, Номер 347, С. 121348 - 121348

Опубликована: Июнь 16, 2023

Язык: Английский

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Comparative assessment of multi-objective optimization of hybrid energy storage system considering grid balancing

Renewable Energy, Год журнала: 2023, Номер 216, С. 119107 - 119107

Опубликована: Авг. 2, 2023

Язык: Английский

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