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Self-Consumption of Photovoltaic Electricity in Residential Buildings
Abstract
Worldwide installations of photovoltaics (PV) have increased rapidly due to national subsidies and decreasing prices. One important market segment is building-applied PV systems, for which the generated electricity can be self-consumed. Self-consumption is likely to become important both for the profitability and to facilitate integration of high shares of PV in the power system. The purpose of this doctoral thesis is to examine opportunities and challenges with distributed PV in the power system on four system levels: detached houses, communities, distribution systems and national level. This was done through literature studies and computer simulations. Previous research has shown a larger potential to increase the PV self-consumption in detached houses by using battery storage rather than shifting the household appliance loads. This thesis shows that, on the community level, the self-consumption increased more when sharing one large storage instead of individual storages in each house. On the distribution system level, PV power curtailment was identified as an effective solution to reduce the risk of overvoltage due to high PV penetration levels. However, the curtailment losses were high: up to 28% of the electricity production had to be curtailed in the studied distribution grid with a PV penetration of 100% of the yearly electricity consumption. However, the penetration of distributed PV on a national level is not likely to reach these levels. Around 12% of the Swedish households were estimated to have PV systems in 2040, although the uncertainties in the results were high, mainly related to the development of the electricity prices. The low profits from both PV but especially battery systems reduce future market shares. If residential batteries could also be used for primary frequency control, the profitability and thus the market shares for PV and battery systems could increase. The overall conclusions are that improved self-consumption can increase the profitability of PV systems and lower the negative impacts on grids with high PV penetration. Energy storage has a large potential to increase the self-consumption, but the profitability is still low for a storage that is only used to increase the self-consumption.
... Large-scale integration of PV systems into the power system can lead to several problems, such as overvoltages, component overloading and harmonic distortions, which can lead to a decrease of the lifetime of power grid components and expensive grid reinforcements [31]. However, the most challenging problem when it comes to PV systems, or generally almost all RES, is their intermittent generation profiles. ...
... When it comes to the hosting capacity for PV, low PV hosting capacity is often due to the mismatch between the load and the PV generation. It is shown that improved load matching, or synergies between the load and the generation, will improve the hosting capacity for new generation and new load [31,40]. Common ways to improve the load matching is by installing battery storage or deploying demand side management (DSM) strategies, including EV smart charging. ...
... The use of this kind of ratio is common, especially in the assessment of PV self-consumption and self-sufficiency as conducted in [31,64]. In this thesis, several R PV values were simulated. ...
The world is now in a transition towards a more sustainable future. Actions to reduce the green-house gases (GHG) emissions have been promoted and implemented globally, including switching to electric vehicles (EVs) and renewable energy technologies, such as solar photovoltaics (PV). This has led to a massive increase of EVs and PV adoption worldwide in the recent decade.
However, large integration of EVs and PV in buildings and electricity distribution systems pose new challenges such as increased peak loads, power mismatch, component overloading, and voltage violations, etc. Improved synergy between EVs, PV and other building electricity load can overcome these challenges. Coordinated charging of EVs, or so-called EV smart charging, is believed to a promising solution to improve the synergy.
This licentiate thesis investigates the synergy between residential EV charging and PV generation with the application of EV smart charging schemes. The investigation in this thesis was carried out on the individual building, community and distribution grid levels. Smart charging models with an objective to reduce the net-load (load - generation) variability in residential buildings were developed and simulated. Reducing the net-load variability implies both reducing the peak loads and increasing the self-consumption of local generation, which will also lead to improved power grid performance. Combined PV-EV grid hosting capacity was also assessed.
Results show that smart charging schemes could improve the PV self-consumption and reduce the peak loads in buildings with EVs and PV systems. The PV self-consumption could be increased up to 8.7% and the peak load could be reduced down to 50%. The limited improve
ment on self-consumption was due to low EV availability at homes during midday when the solar power peaks. Results also show that EV smart charging could improve the grid performance such as reduce the grid losses and voltage violation occurrences. The smart charging
schemes improve the grid hosting capacity for EVs significantly and for PV slightly. It can also be concluded that there was a slight positive correlation between PV and EV hosting capacity in the case of residential electricity distribution grids.
Keywords: Electric vehicle, Smart charging, Photovoltaics, Residential buildings, Electricity
use, Self-consumption, Distribution Grid, Hosting capacity
... fluctuations [8], and improving the self-consumption of energy -in this case electricity -is therefore preferred to mitigate the aforementioned challenges without curtailing the power output of RESs. Luthander [9] showed that battery storage is the most common and most effective approach to improve self-consumption, revealing that battery storage increases the self-consumption between 11 and 41 percentage points in recent studies. In contrast, the same study [9] found that demand-side management (DSM) typically offers less self-consumption improvement, ranging between 2 and 18 percentage points increase. ...
... Luthander [9] showed that battery storage is the most common and most effective approach to improve self-consumption, revealing that battery storage increases the self-consumption between 11 and 41 percentage points in recent studies. In contrast, the same study [9] found that demand-side management (DSM) typically offers less self-consumption improvement, ranging between 2 and 18 percentage points increase. ...
... As final measures, we use the self-consumption ( sc ) and selfsufficiency ( ss ) to gauge the performance of the two case-studies. These are defined as [9]: ...
Scenario-based stochastic model predictive control traditionally considers the optimal strategy to be the expectation of the optimal strategies across all scenarios. However, while the stochastic problem involving uncertainties can be substantiated by a large number of scenarios, the expectation of the respective optimal control strategies derived from all scenarios as the optimal control strategy to the problem is challenging to justify. We therefore propose a different approach in which we artfully have the optimization program find the common optimal strategy across all scenarios for the first prediction step at each sample time, which, if it exists, yields the true optimal strategy with greater confidence. We demonstrate the efficacy of the proposed formulation through a case study of a research villa in Borås, Sweden, that is equipped with a battery and a photovoltaic system. We compute a covariance matrix that contains time-dependent information of the data and use it to generate autocorrelated scenarios from the probabilistic forecasts that serve as the uncertain input to the energy management system. We justify the credibility of the optimal solution derived from the proposed formulation with compelling reasoning and quantitative results such as improved self-consumption of photovoltaic power.
... Large-scale integration of PV systems into the power system can lead to several problems, such as overvoltages and component overloading as previously explained in Figure 2.8 (c). These can lead to a decrease in the lifetime of power grid components and expensive grid reinforcements [63]. However, the most challenging problem when it comes to PV systems, or generally almost all RES, is their intermittent generation profiles. ...
... When it comes to the hosting capacity for PV, low PV hosting capacity is often due to the mismatch between the load and the PV power generation. It was shown that improved load matching, or synergies between the load and the generation, have the potential to improve the hosting capacity for new generation and load [63,70]. Common ways to improve load matching are by installing battery storage or deploying demand-side management strategies, including EV smart charging. ...
This doctoral thesis investigates the synergy between EV charging and PV power generation with the application of EV smart charging and V2G schemes. The investigation was carried out through simulation studies on the system levels of residential buildings, workplaces, distribution grid, and city-scale. Smart charging and V2G optimization models with an objective to reduce the net-load (load minus generation) variability were developed and simulated.
The results show that the PV-EV synergy can be improved with the proposed smart charging schemes. However, the levels of improvement depend highly on the user mobility behavior from and to the destined charging locations. PV-EV synergy is limited in residential buildings due to low EV occupancy during high solar power production, but has high potential at workplace charging stations due to high EV occupancy during the same time. In the case studies presented in this thesis, it was found that the implementation of smart charging can improve the synergy by up to around 9 percentage points in residential buildings and up to around 40 percentage points in workplaces. On a city-scale level, both optimal sizing and V2G play essential roles in improving city-scale generation-load synergy, as they can increase the load matching from 33% to 84%. The results also show that improved synergy leads to enhanced power grid performance and combined PV-EV grid hosting capacity.
In conclusion, the thesis demonstrates that EV smart charging schemes can improve PV-EV synergy, leading to enhanced performance of urban energy systems.
... It was assumed that the charging efficiency was constant regardless of the charging power. The simulations had a 15 min resolution, which was one of the most common temporal resolutions for DSM schemes and self-consumption studies; see [9,35,36]. Furthermore, even though a perfect forecast was assumed in this study, the practical side on the forecast horizon was also considered. Higher forecast resolution, e.g., 1 min, was not so common for two of the main variables in this study, i.e., solar power production and electricity consumption, especially for electricity consumption [37]. ...
... The computation time of the optimization process was expected to be higher when the smart charging scheme resolution was higher. Even though the studies in [9,35] showed that 15 min resolution was sufficient for a self-consumption study, future studies using a higher resolution are recommended in order to find out the trade-offs between the computation speed and the accuracy. ...
The integration of photovoltaic (PV) and electric vehicle (EV) charging in residential buildings has increased in recent years. At high latitudes, both pose new challenges to the residential power systems due to the negative correlation between household load and PV power production and the increase in household peak load by EV charging. EV smart charging schemes can be an option to overcome these challenges. This paper presents a distributed and a centralized EV smart charging scheme for residential buildings based on installed photovoltaic (PV) power output and household electricity consumption. The proposed smart charging schemes are designed to determine the optimal EV charging schedules with the objective to minimize the net load variability or to flatten the net load profile. Minimizing the net load variability implies both increasing the PV self-consumption and reducing the peak loads. The charging scheduling problems are formulated and solved with quadratic programming approaches. The departure and arrival time and the distance covered by vehicles in each trip are specifically modeled based on available statistical data from the Swedish travel survey. The schemes are applied on simulated typical Swedish detached houses without electric heating. Results show that both improved PV self-consumption and peak load reduction are achieved. The aggregation of distributed smart charging in multiple households is conducted, and the results are compared to the smart charging for a single household. On the community level, both results from distributed and centralized charging approaches are compared.
... When energy sharing is enabled in the building cluster, the required optimal capacity of TES can be reduced, compared with the scenario in which energy sharing is not allowed. This is because the district-level electric demand can match the district-level renewable supply better as discussed previously and shown by Luthander et al. [53], and thus a smaller sized TES is needed to compensate the energy mismatch. The integration of TES does not affect LCOE too much, as both the renewable energy generations and the costs increase. ...
... The results have revealed how those factors influence the design of PV systems and the system techno-economic performance, and thus help promote the PV deployment. More importantly, this study has demonstrated the feasibility for transferring the existing Swedish building cluster into smart electricity prosumers with higher self-consumption rates and energy efficiency and more Self-consumption and self-sufficiency scheme as proposed in [53], the diameters of the bubbles represents the capacity of the PV system. intelligence, which offers good solutions for EU to achieving the '32% share of renewable energy source' target. ...
Smart grid is triggering the transformation of traditional electricity consumers into electricity prosumers. This paper reports a case study of transforming an existing residential cluster in Sweden into electricity prosumers. The main energy concepts include (1) click-and-go photovoltaics (PV) panels for building integration, (2) centralized exhaust air heat pump, (3) thermal energy storage for storing excess PV electricity by using heat pump, and (4) PV electricity sharing within the building cluster for thermal/electrical demand (including electric vehicles load) on a direct-current micro grid. For the coupled PV-heat pump-thermal storage-electric vehicle system, a fitness function based on genetic algorithm is established to optimize the capacity and positions of PV modules at cluster level, with the purpose of maximizing the self-consumed electricity under a non-negative net present value during the economic lifetime. Different techno-economic key performance indicators, including the optimal PV capacity, self-sufficiency, self-consumption and levelized cost of electricity, are analysed under impacts of thermal storage integration, electric vehicle penetration and electricity sharing possibility. Results indicate that the coupled system can effectively improve the district-level PV electricity self-consumption rate to about 77% in the baseline case. The research results reveal how electric vehicle penetrations, thermal storage, and energy sharing affect PV system sizing/positions and the performance indicators, and thus help promote the PV deployment. This study also demonstrates the feasibility for transferring the existing Swedish building clusters into smart electricity prosumers with higher self-consumption and energy efficiency and more intelligence, which benefits achieving the ‘32% share of renewable energy source’ target in EU by 2030.
... However, they were averaged to a 15-min resolution in order to match the resolution of the simulation setup intended for load matching assessment in this study. The use of 15-min resolution was motivated by the findings in [33,63], which showed that 15-min resolution was sufficient for a load matching assessment. ...
Renewable energy and electric vehicles (EVs) are crucial technologies for achieving sustainable cities. However, intermittent power generation from renewable energy sources and increased peak load due to EV charging can pose technical challenges for the power systems. Improved load matching through energy system optimization can minimize these challenges. This paper assesses the optimal urban-scale energy matching potentials in a net-zero energy city powered by wind and solar energy, considering three EV charging scenarios: opportunistic charging, smart charging, and vehicle-to-grid (V2G). A city on the west coast of Sweden is used as a case study. The smart charging and V2G schemes aim to minimize the mismatch between generation and load, and are formulated as quadratic programming problems. The simulation results show that the optimal load matching performance is achieved in a net-zero energy city with the V2G scheme and a wind-PV electricity
production share of 70:30. The load matching performance in the optimal net-zero energy city is increased from 68% with opportunistic charging to 73% with smart charging and further to 84% with V2G. It is also shown that a 2.4 GWh EV battery participating in the V2G scheme equals 1.4 GWh stationary energy storage in improving urban-scale load matching performance. The findings indicate that EVs have a high potential to provide flexibility to urban energy systems.
... Battery storage systems (BSSs) are becoming more and more useful as their prices have considerably decreased [4]. A widely adopted strategy to alleviate this power management issue is to prioritize PV power self-consumption [5][6][7][8]. In all major world regions, especially in developed countries, feed-in tariffs (FIT) for residential solar power are reduced, on average, to a quarter of their value 10 years ago [9][10][11][12]. ...
For increased penetration of energy production from renewable energy sources at a utility scale, battery storage systems (BSSs) are a must. Their levelized cost of electricity (LCOE) has drastically decreased over the last decade. Residential battery storage, mostly combined with photovoltaic (PV) panels, also follow this falling prices trend. The combined effect of the COVID-19 pandemic and the war in Ukraine has caused such a dramatic increase in electricity prices that many consumers have adjusted their strategies to become prosumers and self-sufficient as feed-in subsidies continue to drop. In this study, an investigation is conducted to determine how profitable it is to install BSSs in homes with regards to battery health and the levelized cost of total managed energy. This is performed using mixed-integer linear programming (MILP) in MATLAB, along with its embedded solver Intlinprog. The results show that a reasonable optimized yearly cycling rate of the BSS can be reached by simply considering a non-zero cost for energy cycling through the batteries. This cost is simply added to the electricity cost equation of standard optimization problems and ensures a very good usage rate of the batteries. The proposed control does not overreact to small electricity price variations until it is financially worth it. The trio composed of feed-in tariffs (FITs), electricity costs, and the LCOE of BSSs represents the most significant factors. Ancillary grid service provision can represent a substantial source of revenue for BSSs, besides FITs and avoided costs.
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