Performance analysis of optimal designed hybrid energy systems for grid-connected nearly/net zero energy buildings

Within the context of the Smart City, the need for intelligent approaches to manage and coordinate the diverse range of supply and conversion technologies and demand applications has been well established. The wide-scale proliferation of sensors coupled with the implementation of embedded computational intelligence algorithms can help to tackle many of the technical challenges associated with this energy systems integration problem. Nonetheless, barriers still exist, as suitable methods are needed to handle complex networks of actors, often with competing objectives, while determining design and operational decisions for systems across a wide spectrum of features and time-scales. This review looks at the current developments in the smart energy sector, focussing on techniques in the main application areas along with relevant implemented examples, while highlighting some of the key challenges currently faced and outlining future pathways for the sector. A detailed overview of a framework developed for the EU H2020 funded Sharing Cities project is also provided to illustrate the nature of the design stages encountered and control hierarchies required. The study aims to summarise the current state of computational intelligence in the field of smart energy management, providing insight into the ways in which current barriers can be overcome.

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“…Technology selection is also crucial. In [102] for example, Monte Carlo simulations are used to evaluate hybrid energy system solutions.…”

Section: Zero-energy and Nearly-zero-energy Buildingsmentioning

confidence: 99%

Smart energy systems for sustainable smart cities: Current developments, trends and future directions

et al. 2019

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“…Uncertainty/Reliability Analysis Factors Considered for Reliability Analysis [7] PV/WT/BDG N None [8] PV/WT, PV/BDG, WT/BDG, PV/WT/BDG Y Solar radiation, wind velocity, cooling load, other electricity load.…”

Section: Ref Energy Production Systemmentioning

confidence: 99%

“…(2) energy efficiency technologies (e.g., HVAC, lighting, and appliances) [5,6]; (3) energy production technologies (e.g., combined cooling, heat and power, battery, photovoltaic panel, and wind turbine) [7,8]. A schematic diagram of the approaches is shown in Figure 1.…”

Section: Introductionmentioning

confidence: 99%

Optimal Distribution of Renewable Energy Systems Considering Aging and Long-Term Weather Effect in Net-Zero Energy Building Design

Alghassab

Alvarez-Alvarado

et al. 2020

Sustainability

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Generation system interruptions in net-zero energy buildings (NZEBs) may result in missing the net-zero targets by a great margin. Consequently, it is significant to incorporate a realistic reliability model for renewable energy systems (RESs) that considers aging and long-term weather conditions. This study proposed a robust design optimization method that deals with the selection of RES to achieve NZEB. Different case studies were evaluated: 1. Deterministic approach; 2. Markov chain-based reliability without the aging effect; 3. Markov chain-based reliability with the aging effect. The results showed that the optimal sizes of RES, considering the aging effect, were much larger than the other two cases based on the annual energy balance. Moreover, the consideration of the aging effect on the reliability assessment of the generation system for NZEB opens a pathway for a more robust and economic design of RES.

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“…When the amount of this kind of resident consumers becomes large, peak load shifting can be achieved. The objective of minimizing the power interactive with the main grid is formulated as follows:

\begin{matrix} right \min G_{1} = & left \sum_{t = 1}^{24} (P_{t}^{p v, n e t} + P_{t}^{n e t, l o a d} & right \\ right & left + P_{t}^{b a t, n e t} + P_{t}^{n e t, b a t}) \end{matrix}

…”

Section: Residential Vpp Modelingmentioning

confidence: 99%

Residential virtual power plant with photovoltaic output forecasting and demand response

Cui

Wang

Lin

et al. 2019

Asian Journal of Control

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Decreasing conventional power supply is promoting the development of the distributed renewable energy sources, such as solar power and wind power.Recently rooftop photovoltaic has been widely applied, and accordingly efficient energy management is getting increasingly important for fully use of renewable energy and the peak shaving of the main grid. This paper investigates the residential energy management as a small-scale virtual power plant (VPP) connected to the main grid includes distributed energy resources, energy storages and residential loads. The self-organizing map (SOM) and the radical basis function (RBF) networks are adopted to classify the weather types and predict hourly photovoltaic output precisely. In a time-of-use electricity market, price-based demand response is applied to adjust the demand. The residential VPP has two goals: maximum profit by selling surplus power to grid and minimum power purchased from grid. The two goals are integrated as an optimization object by introducing a weight parameter. The algorithm combining receding horizon optimization and linear programming is proposed to solve the optimization problem in residential VPP. Numerical simulation tests can help to find the most suitable value of the weight parameter. Different scenarios are simulated and discussed to demonstrate the performance of the VPP and the proposed algorithm.

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Performance analysis of optimal designed hybrid energy systems for grid-connected nearly/net zero energy buildings

Cited by 47 publications

References 39 publications

Smart energy systems for sustainable smart cities: Current developments, trends and future directions

Smart energy systems for sustainable smart cities: Current developments, trends and future directions

Optimal Distribution of Renewable Energy Systems Considering Aging and Long-Term Weather Effect in Net-Zero Energy Building Design

Residential virtual power plant with photovoltaic output forecasting and demand response

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