Increasing Energy Self-Consumption in Residential Photovoltaic Systems with Heat Pumps in Poland

Pater, Sebastian

doi:10.3390/en16104003

Cited by 12 publications

(6 citation statements)

References 30 publications

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“…Pater [30] analyzed the results of the year-round operation of a grid-connected hybrid photovoltaic system with an air-source heat pump for the preparation of domestic hot water (DHW) in a residential building in Krakow, Poland in the context of the increasing self-consumption rate of energy. Simulations in TRNSYS showed that due to the increase in ambient temperature, the PV efficiency in the summer period was almost 2% lower compared to the winter period, while the average annual energy efficiency of the PV systems included in the simulations was 17.34%.…”

Section: Introductionmentioning

confidence: 99%

Simulation and Performance Analysis of an Air-Source Heat Pump and Photovoltaic Panels Integrated with Service Building in Different Climate Zones of Poland

Ołtarzewska,

Krawczyk

2024

Energies

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In recent years, due to the global energy crisis, the idea of a photovoltaic-assisted air-source heat pump (PV-ASHP) has become increasingly popular. This study provides a simulation in TRNSYS and the analysis of the use of a PV-ASHP system in a service building in different climate zones of Poland. For each of the six cities—Kolobrzeg, Poznan, Krakow, Warsaw, Mikolajki, and Suwalki, the effect of changing five system parameters (area, efficiency, type, and location of photovoltaic panels, and the use of a heat pump control strategy) on the amount of energy generated and consumed was determined. We also estimated the extent to which the photovoltaic panels could cover the energy requirements for the heat pump (HP) operation and the system could provide thermal comfort in the service room. Finally, a simplified analysis of the operating costs and capital expenditures was made. The results highlighted the issue of the incoherence of renewable energy sources and the need to store surplus energy under Polish climatic conditions. Abandoning the HP control strategy increased energy consumption by 36–62%, depending on the location and Variant, while the change in the place of the PV panels on the roof slope reduced energy generation by 16–22%. When applied to an ASHP in a service building, the use of PV panels to power it seems to be cost-effective.

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Section: Introductionmentioning

confidence: 99%

Simulation and Performance Analysis of an Air-Source Heat Pump and Photovoltaic Panels Integrated with Service Building in Different Climate Zones of Poland

Ołtarzewska,

Krawczyk

2024

Energies

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“…Currently, there is extensive research into distributed energy systems that rely on complementary energy time scales of various energy sources. These systems have reached the level of scaled-up applications to some extent [4,5]. New varieties of CSP-based hybrid renewable energy systems, such as CSP-wind [6] and CSP-PV-wind [7] systems, have been investigated.…”

Section: Introductionmentioning

confidence: 99%

Capacity-Operation Collaborative Optimization for Wind-Solar-Hydrogen Multi-Energy Supply System

Liu,

Zhai,

et al. 2023

Applied Sciences

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In pursuit of widespread adoption of renewable energy and the realization of decarbonization objectives, this study investigates an innovative system known as a wind-solar-hydrogen multi-energy supply (WSH-MES) system. This system seamlessly integrates a wind farm, photovoltaic power station, solar thermal power station, and hydrogen energy network at the power grid level. Central to the study is the introduction of a bi-level collaborative optimization model—an innovative algorithmic framework specifically tailored for complex multi-energy systems. This model co-optimizes both the capacity planning of essential system components and their annual load distribution, adeptly navigating the complexities of optimizing capacity and annual load distribution under uncertain energy sources and load conditions. A layered methodology synergistically combines linear programming with an advanced version of non-dominated sorting genetic algorithm-II. When applied to a real-world case study in Zhangbei, China, this approach identifies an optimal system capacity, leading to annual green power generation of 201.56 GW and a substantial reduction of over 173,703 tons of CO2 emissions. An economic analysis further reveals that each 1% reduction in CO2 emissions corresponds to a modest 1.7% increase in the system’s levelized cost of energy. Moreover, a comprehensive exploration of the impacts of various capacity parameters on the WSH-MES system’s performance is conducted. These insights offer invaluable guidance for the large-scale advancement of efficient renewable energy utilization and the attainment of decarbonization targets.

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“…In the housing sector, conventional heating resources such as natural gas and oil are being replaced with heat pumps. As was presented in [3], large communities could be heated by heat pumps, along with energy provided by solar power plants. Heat pumps offer notable advantages, as they are characterised by their environmental friendliness and efficiency.…”

Section: Introductionmentioning

confidence: 99%

A Machine Learning Application for the Energy Flexibility Assessment of a Distribution Network for Consumers

Rober,

Maruša,

Beković

2023

Energies

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This paper presents a step-by-step approach to assess the energy flexibility potential of residential consumers to manage congestion in the distribution network. A case study is presented where a selected transformer station exhibits signs of overloading. An analysis has been performed to evaluate the magnitude of the overloading and the timing of the overload occurrence based on their historical load data. Based on the historical load data, the four most prominent consumers have been chosen for the flexibility assessment. Temperature load dependency has been evaluated for the selected consumers. The paper’s novel approach focuses on selecting individual consumers with the highest energy flexibility potential, and analysing their load patterns to address transformer overloading. To achieve this, machine learning algorithms, specifically, multiple linear regression and support vector machines, were used for load profile forecasting during the overload occurrences. Based on the forecast and measured load patterns, flexibility scenarios were created for each consumer. The generated models were evaluated and compared with the forecasting based on the average load of the past days. In the results, three potential consumers were identified who could resolve the transformer overloading problem. The machine learning models outperformed the average-based forecasting method, providing more realistic estimates of flexibility potential. The proposed approach can be applied to other overloaded transformer stations, but with a limited number of consumers.

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Increasing Energy Self-Consumption in Residential Photovoltaic Systems with Heat Pumps in Poland

Cited by 12 publications

References 30 publications

Simulation and Performance Analysis of an Air-Source Heat Pump and Photovoltaic Panels Integrated with Service Building in Different Climate Zones of Poland

Simulation and Performance Analysis of an Air-Source Heat Pump and Photovoltaic Panels Integrated with Service Building in Different Climate Zones of Poland

Capacity-Operation Collaborative Optimization for Wind-Solar-Hydrogen Multi-Energy Supply System

A Machine Learning Application for the Energy Flexibility Assessment of a Distribution Network for Consumers

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