Impact of electricity market feedback on investments in solar photovoltaic and battery systems in Swedish single-family dwellings

The profitability of investments in photovoltaics (PVs) and batteries in private households depends on the market price of electricity, which in turn is affected by the investments made in and the usage of PVs and batteries. This creates a feedback mechanism between the centralised electricity generation system, and household investments in PVs and batteries. To investigate this feedback effect, we connect a local optimisation model for household investments with a European power generation dispatch model. The local optimisation is based on the consumption profiles measured for 2104 Swedish households. The modelling compares three different scenarios for the centralised electricity supply system in Year 2032, as well as several sensitivity cases. Our results show total investment levels of 5–20 GWp of PV and 0.01–10 GWh of battery storage capacity in Swedish households in the investigated cases. These levels are up to 33% lower than before market feedback is taken into account. The profitability of PV investments is affected most by the price of electricity and the assumptions made regarding grid tariffs and taxes. The value of investments in batteries depends on both the benefits of increased self-consumption of PV electricity and market arbitrage

Solar photovoltaic-battery systems in Swedish households - Self-consumption and self-sufficiency

This work investigates the extent to which domestic energy storage, in the form of batteries, can increase the self-consumption of electricity generated by a photovoltaic (PV) installation. The work uses real world household energy consumption data (measurements) as the input to a household energy consumption model. The model maximizes household self-sufficiency, by minimizing the amount of electricity purchased from the grid, and thereby also maximizing the level of self-consumption of PV electricity, i.e., the amount of PV-generated electricity that is consumed in-house. This is done for different combinations of PV installation sizes (measured in array-to-load ratio; ALR: ratio of the PV capacity to the average annual electric load of a household) and battery capacities for different categories of single-family dwellings in Sweden (i.e., northern latitudes). The modeling includes approximately 2000 households (buildings). The results show that the use of batteries with capacities within the investigated range, i.e., 0.15-100 kW h, can increase the level of self-consumption by a practical maximum of 20-50 percentage points (depending on the load profile of the household) compared to not using a battery. As an example, for a household with an annual electricity consumption of 20 MW h and a PV installation of 7 kW,,, this range in increased self-consumption of PV-generated electricity requires battery capacities in the range of 1524 kW h (actual usable capacity), depending on the load profile of the specific household. The practical maximum range is determined by the seasonality of PV generation at Swedish latitudes, i.e., higher levels of increased self-consumption are possible, however, it would require substantially larger batteries than the up to 100 kW h investigated in this work. Thus, any additional marginal increment in battery capacity beyond the range investigated results in a low level of utilization and poor additional value. Furthermore, our results reveal that when a battery is used to store PV-generated electricity in-house, self-sufficiency increases (as compared to not using a battery) by 12.5-30 percentage points for the upper range of the investigated PV capacities (ALR. of 6). (C) 2016 Elsevier Ltd. All rights reserved

Modelling interactions between distributed energy technologies and the centralised electricity supply system

Renewable electricity generators, such as solar photovoltaics (PVs), and variation management technologies, such as battery storage and demand response (DR) systems, can be deployed in a distributed fashion, which can benefit the overall system. Such distributed energy technologies interact with and influence the centralised generation and transmission systems. This thesis investigates these interactions using a cost-minimising investment model (ELIN) to generate scenarios for the future European electricity supply system and analysing the operation of the system in an economic dispatch model (EPOD). Using the EPOD model to study congestion in the European transmission system, we show that while demand-related congestion can be reduced with DR, congestion related to wind power production cannot. Results also demonstrate that solar and wind power correlate with congestion on different time scales. Solar power cross-correlates with hourly congestion with a time displacement of 6-9 hours, whereas wind power correlates with congestion on a weekly time scale. Two approaches are applied to model the effect of household-level phenomena on the centralised electricity supply system. First, a model for electric space heating load is integrated into EPOD, in order to study DR. The results show that DR in Swedish single-family dwellings (SFDs) primarily reduces the system running costs in neighbouring regions outside Sweden. Second, to capture market feedback, a cost-minimising investment model for PVs and batteries for individual households is iteratively linked to EPOD, yielding optimal capacities of up to around 8 GWp of PVs and 8 GWh of batteries in total for Swedish SFDs. It is concluded that capturing market feedback is crucial for avoiding overestimations of the household investments

The roles of transmission and distribution networks in integrating variable renewable electricity generation

Emission reduction targets, together with other factors, such as security of supply, are driving the expansion of variable renewable energy sources for electricity generation, mainly solar and wind power. Trading across the transmission grid is an important measure to handle the increased variability and to balance supply with demand. Connecting generation capacity at the distribution level as distributed generation may confer benefits on the system, although it could also impose new requirements on distribution systems. This work applies a cost-minimising investment model together with several economic dispatch models to study how transmission and distribution grids can be used in future scenarios with high penetration levels of solar and wind power.We show that new congestion patterns arise in the European transmission system as a result of expansion of wind and solar power capacities, due to the low marginal costs of electricity at times of high output from these technologies. Furthermore, our results show that such instances of congestion may be difficult to handle with alternative variation management strategies, such as demand-side management (DSM), whereas for peak-load congestion, DSM may be an alternative to grid capacity expansion. We also find that rapid expansion of solar power generation within Europe could have a significant impact on marginal costs of electricity and could cause significant congestion during sunny seasons if its geographical distribution is uneven. However, we also show that distributed solar power can help to reduce losses if installations are optimised to maximise local consumption

District heating in the Nordic countries – modelling development of present systems to 2050

District heating constitutes a significant part of the total energy use in Sweden, Finland, and Denmark. In a transition to a more sustainable energy system, district heating can play an important role, e.g. through efficiency benefits and possibilities to utilise additional energy sources. In this project a computer-based cost-minimising investment model, describing the development of the production mixes of the national district heating systems in these countries from 2010 to 2050, is constructed using the TIMES model generator. The model is used for a comparative analysis of district heat production in three possible future scenarios, i.e. sets of consistent assumptions about the development in other parts of the energy system, e.g. the electricity supply system. The national district heating system in each country consists of hundreds of physically separate networks, all operating under different conditions. Modelling all these systems individually is, however, practically difficult, due to the time required for modelling and computation. Therefore a type system approach is used, where an entire class of actual systems, with similar production mixes and annual production volumes, is represented by one type system in the model. Based on a review of all networks described in the national district heating production statistics for each country, six type systems are constructed for Sweden and six for Finland, in total describing 85 % of the national annual district heat production in each country respectively. For Denmark, three type systems are constructed, describing 49 % of the national annual district heat production, and the remainder of the national production mix is described by an aggregation of the remaining actual systems. The constructed type systems are then described in the TIMES model. Three scenarios are studied. Two scenarios are designed to represent different pathways to reducing carbon dioxide emissions, one market-based approach with high carbon dioxide emission costs and one focusing on energy efficiency and support for renewable energy sources. The third scenario is a reference development, where current policies are extended into the future. Model results show that the cost-minimal development for the district heating systems in Finland and Denmark may include a transition from coal and natural gas to, primarily, biomass fuelled production facilities. If combined with a decreasing demand for district heat, this can lead to a substantial decrease in the electricity production from combined heat and power plants of up to 50 % in Denmark according to the model results. It can also be seen that a decreasing district heat demand in Sweden may, in the cost-minimal development, lead to difficulties in utilising the heat from waste incineration

The Future of the European Electricity Grid Is Bright: Cost Minimizing Optimization Shows Solar with Storage as Dominant Technologies to Meet European Emissions Targets to 2050

The European roadmap for the power sector dictates an 80–95% cut of existing levels of carbon dioxide emissions is needed by the year 2050 to meet climate goals. This article describes results from a linear cost optimization investment model, ELIN, coupled with a solar technology model, Distributed Concentrating Solar Combined Heat and Power (DCS-CHP), using published investment costs for a comprehensive suite of renewable and conventional electricity generation technologies, to compare possible scenarios for the future electricity grid. The results of these model runs and sensitivity analyses indicate that: (1) solar photovoltaics (PV) with battery storage will likely play a very large role in meeting European targets; (2) concentrating solar power (CSP) with thermal energy storage is at a slight economic disadvantage with respect to PV to compete economically; (3) the economic potential of wind power is only comparable with solar PV if high wind penetration levels are allowed in the best wind sites in Europe; and (4) carbon capture and nuclear technologies are unlikely to compete economically with renewable technologies in creating a low-carbon future grid

The effect of high levels of solar generation on congestion in the European electricity transmission grid

The increasing levels of solar power affect the usage and development of electricity grids, both at local distribution level and with respect to potential congestion within the transmission grid. We use a cost-minimising investment model (ELIN) to determine the development of the European electricity generation system up to Year 2050, for two renewable-dominated scenarios: the Green Base scenario, with a Europe-wide, technology-neutral renewable certificate scheme; and the Net Metering scenario, with an additional net metering support scheme for solar power. The system compositions are extracted from the ELIN results for the years 2022 and 2032, and analysed in an hourly dispatch model (EPOD) to study the effects of solar power on marginal electricity costs and transmission congestion. From the results of the investment model, it is clear that the presence of a net metering subsidy scheme significantly affects both the pace at which solar power continues to expand and the geographical distribution of the new capacity. In the dispatch modelling, it can be seen that high penetration levels of solar power have a strong effect on the marginal costs of electricity, since production is concentrated around a few hours each day. At penetration levels of 20–30% of annual electricity demand, solar power production entails a predictable daily marginal cost difference between the solar peak and the evening price peak, which could make short-term storage competitive. Transmission congestion during summer is consistently higher in the systems from the Net Metering scenario than in those from the Green Base scenario, while the opposite is true during winter. Solar power production correlates strongly with congestion 6–9 h after the solar peak, whereas wind power correlates with congestion with respect to more slowly evolving and longer-term variations

Distributed solar and wind power - Impact on distribution losses

Introducing renewable electricity as distributed generation may be an attractive option in the shift towards a more sustainable electricity system. Yet, it is not clear to what extent an increased use of distributed generation is beneficial from a systems perspective. We therefore investigate the impacts from increased employment of distributed solar and wind power on losses and transformer capacity requirements in distribution systems. The analysis is based on a dispatch model with a simple representation of typical voltage levels in the distribution system. When electricity is transferred between voltage levels, we subtract losses estimated as the transferred energy times a constant loss factor. Our results show that the losses depend on how load is distributed between voltage levels. For total penetration levels up to 40–50% on an energy basis, we find that wind and solar power could potentially reduce distribution losses. Results further indicate that solar photovoltaic capacity in the low voltage level has a limited potential to decrease peak power flows between voltage levels in a setting where seasonal variations in demand and solar output are opposite to each other. Thereby distributed solar generation also has limited potential to defer investments in transformer capacity between voltage levels

Maximizing Value of Wind Power Allocation: a Multi-objective Optimization approach

The trade-off between average output and standard deviation of the aggregated wind power output in Europe was investigated using a multi-objective optimization approach. By varying the allocation of wind power to different regions in Europe and aggregating the output, emphasis can be shifted between variability and average output. In the optimization, the objective of minimizing standard deviation is related to maximizing the aggregated capacity factor. A case where the capacity of wind power was five times the present installation was investigated. It was found, that the standard deviation of the aggregated output for the optimal aggregations range between 8.1 % and 19.5 % with a corresponding range in average output between 18.4 % and 37.3 %