Assessing electrical bottlenecks at feeder level for residential net zero-energy buildings by integrated system simulation

Bætens, Ruben; Coninck, Roel De; Roy, Juan Van; Verbruggen, Bart; Driesen, Johan; Helsen, Lieve; Sælens, Dirk

doi:10.1016/j.apenergy.2011.12.098

Cited by 191 publications

(117 citation statements)

References 35 publications

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“…Self-consumption is defined as PV electricity production that is directly consumed in the house, i.e. self-consumed electricity, relative to the total PV electricity production (Baetens et al, 2012). Solar fraction is defined as the self-consumed PV electricity production relative to the total load (Lund, 2005).…”

Section: Final Energy Solar Fraction Self-consumption and Seasonalmentioning

confidence: 99%

Control Algorithms for PV and Heat Pump System Utilizing Thermal and Electrical Storage

Psimopoulos¹,

Leppin²,

Luthander³

et al. 2016

Proceedings of EuroSun2016

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In this study a detailed model of a single-family house with an exhaust air heat pump and photovoltaic system is developed in the simulation software TRNSYS. The model is used to evaluate three control algorithms using thermal and electrical storage in terms of final energy, solar fraction, self-consumption and seasonal performance factor. The algorithms are tested and compared with respect to energetic improvement for 1) use of the heat pump plus storage tank for domestic hot water and space heating, 2) use of the electrical storage in batteries and (3) use of both electrical and thermal storage. Results show the highest increase of self-consumption to 50.5%, solar fraction to 40.6% and final energy decrease to 6923 kWh by implementing the third algorithm in a system with 9.36 kW PV capacity and battery storage of 10.8 kWh. The use of electrical energy storage has higher positive impact compared to the thermal storage with the settings and component sizes used. The combined use of thermal storage and batteries leads to final energy savings that are nearly the same as the combined savings of thermal storage and batteries separately, showing that they are mostly independent of one another for the settings of this study.

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Section: Final Energy Solar Fraction Self-consumption and Seasonalmentioning

confidence: 99%

Control Algorithms for PV and Heat Pump System Utilizing Thermal and Electrical Storage

Psimopoulos¹,

Leppin²,

Luthander³

et al. 2016

Proceedings of EuroSun2016

View full text Add to dashboard Cite

show abstract

“…• Supply cover factor or self-production rate (γ S ), which represents the fraction of energy produced by the ORC (or PV) which is used to cover instantaneous electrical consumption (Equation (6)) (Baetens et al 2012).…”

Section: Performance Criteriamentioning

confidence: 99%

Performance of a reversible heat pump/organic Rankine cycle unit coupled with a passive house to get a positive energy building

Dumont

Carmo

Fontaine

et al. 2016

Journal of Building Performance Simulation

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This paper presents an innovative technology that can be used to deliver more renewable electricity production than the total electrical consumption of a building while covering the heat demand on a yearly basis. The technology concept uses a heat pump (HP), slightly modified to revert its cycle and generate electricity, coupled to a solar thermal collector roof. This reversible HP/organic Rankine cycle unit presents three operating modes: direct heating, HP and organic Rankine cycle. This work focuses on describing the dynamic model of the multi-component system followed by a techno-economic analysis of the system under different operational conditions. Sensitivity studies include: building envelope, climate, appliances, lighting and heat demand profiles. It is concluded that the HP/ORC unit can turn a single-family house into a PEB under certain weather conditions (electrical production of 3012 kWh/year and total electrical consumption of 2318 kWh/year) with a 138.8 m 2 solar roof in Denmark.

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“…At the distribution level, the main negative impacts are the overload of feeders and transformers and the risks of overvoltage and power quality disturbances (Bollen and Hassan, 2011). Such issues are illustrated, for example, in Baetens et al (2012) for a net zero energy neighborhood with building-integrated photovoltaic (PV) systems. The fraction of local PV supply wasted by E. Georges, J.E.…”

Section: Introductionmentioning

confidence: 99%

“…In the centralized approach, the problem is studied across a portfolio of buildings with different consumption load profiles, PV orientations, system sizes and often include a model of the electricity grid (Strbac et al, 2010, Csetvei, Østergaard and Nyeng, 2011, Baetens et al, 2012, Nykamp et al, 2012. As load profiles differ for each end-user, the surplus electricity produced by a decentralized unit can be consumed by another end-user (IEA, 2014).…”

Section: Introductionmentioning

confidence: 99%

“…The method is illustrated with a case-study of a typical American house equipped with PV panels, an air-to-air heat pump, a water heater and an electrical storage for different buy-back prices. The potential for load matching is characterized in terms of percentage of the electricity production consumed on-site and the proportion of the demand covered by decentralized electricity generation (Baetens et al, 2012 andVan Roy et al, 2013). Guidelines for optimal control of the electrical load and for rightsizing of PV panels are proposed.…”

Section: Introductionmentioning

confidence: 99%

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A general methodology for optimal load management with distributed renewable energy generation and storage in residential housing

Georges

Braun

Lemort

2016

Journal of Building Performance Simulation

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In the U.S., buildings represent around 40% of the primary energy consumption and 74% of the electrical energy consumption (U.S. DOE, 2012). Incentives to promote the installation of on-site renewable energy sources have emerged in different states, including net metering programs. The fast spread of such distributed power generation represents additional challenges for the management of the electricity grid and has led to increased interest in smart control of building loads and demand response programs. This paper presents a general methodology for assessing opportunities associated with optimal load management in response to evolving utility incentives for residential buildings that employ renewable energy sources and energy storage. An optimal control problem is formulated for manipulating thermostatically controlled domestic loads and energy storage in response to the availability of renewable energy generation and utility net metering incentives. The methodology is demonstrated for a typical American house built in the 1990s and equipped with a single-speed air-to-air heat pump, an electric water heater and PV collectors. The additional potential associated with utilizing electrical batteries is also considered. Load matching performance for on-site renewable energy generation is characterized in terms of percentage of the electricity production consumed on-site and the proportion of the demand covered. For the purpose of assessing potential, simulations were performed assuming perfect predictions of the electrical load profiles. The method also allows determination of the optimal size of PV systems for a given net-metering program.Results of the case study showed significant benefits associated with control optimization including an increase of load matching between 3 and 28%, with the improvement dependent on the net-metering tariff and available storage capacity. The estimated cost savings for the consumer ranged from 6.4 to 27.5% compared to no optimization with a unitary buy-back ratio, depending on the available storage capacity. Related reduction in CO2 emissions were between 11 and 46%. Optimal load management of the home thermal systems allowed an increase in the optimal size of the PV system in the range of 13 to 21%.

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Assessing electrical bottlenecks at feeder level for residential net zero-energy buildings by integrated system simulation

Cited by 191 publications

References 35 publications

Control Algorithms for PV and Heat Pump System Utilizing Thermal and Electrical Storage

Control Algorithms for PV and Heat Pump System Utilizing Thermal and Electrical Storage

Performance of a reversible heat pump/organic Rankine cycle unit coupled with a passive house to get a positive energy building

A general methodology for optimal load management with distributed renewable energy generation and storage in residential housing

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