While solar PV generation is well-established on single-family houses, there is still a lack of installations on apartment buildings. To understand the effect of sharing distributed generation, we developed two energy sharing models, a welfare optimization, and a game theoretical (bi-level) model. We introduced two type of players, the owner of distributed generation (e.g. solar PV and energy storage) and the consumers. Furthermore, we included consumer preferences by multiple objectives such as emissions reduction and distributed generation in additions to cost in the model. We applied both models to a numerical example using data from the electricity market in Texas. The results showed that welfare is maximized in both models, but shared differently between the owner of the generation and the consumers. One exception is the bi-level model with uniform price auctions, which results in a reduction in system welfare to maximize owner revenues.

This article appeared in a journal published by Elsevier. The attached copy is furnished to the author for internal non-commercial research and education use, including for instruction at the authors institution and sharing with colleagues.Other uses, including reproduction and distribution, or selling or licensing copies, or posting to personal, institutional or third party websites are prohibited. a b s t r a c tThe increase in PV (photovoltaic) capacities in Germany had since 2011 on some days already significant impacts on spot market prices at the German electricity exchange. The core objective of this paper is to investigate the possible effects of a further uptake of PV on the prices in electricity markets. We analyze two major effects: (i) the direct impact of PV at specific times of the year when PV shifts the supply curve of conventional electricity virtually out of the market, leading to temporarily very low market prices close to Zero; (ii) the indirect impact of PV (and wind) on the costs at which fossil capacities are offered at times when renewable energy sources are scarce. The major effects of these developments on the electricity markets will be: (i) a much higher price volatility from hour-to-hour and day-to-day; (ii) higher prices for electricity from fossil capacities and storage technologies for balancing the intermittent renewable generation; and (iii) growth of balancing markets and intensified competition at the level of decentralized balancing organizations.

This paper analyses the profitability and business models of shared, nonsubsidized PV systems' usage in multiapartment buildings in Austria in the context of legislative amendments which came into force in July 2017. In addition, it compares the Austrian results with those of Germany, where significantly higher retail electricity prices determine the profitability benchmark. To that end, a multiobjective optimization model is developed for the optimal dimensioning of PV systems and energy storage facilities in keeping with different end user objectives, ranging from minimizing annual electricity costs to maximizing self-consumption. The results show that the profitability of shared use of nonsubsidized PV systems is marginal in Austria. This means that, based on individual apartment load profiles, the profitability gap ranges between 0 and 40 euros per apartment, whereas the consideration of the building as total load leads to a small cost-saving potential of about 90 euros for the whole building in the best case and thus profitability. In contrast, significant profitability of shared PV systems in multiapartment buildings can be achieved in Germany, where the renewable energy surcharge results in high retail electricity prices. At present, different business models, accounting and billing concepts, are being tested in these countries to learn about the best-practice concepts.

The economic value of photovoltaic (PV) systems depends on country-specific conditions. This study investigates the impact of grid fees, solar irradiance and local consumption on the profitability and penetration of PV systems and batteries in renewable energy communities. The linear optimization model calculates the optimal investments into PV and storages applied on a test community, which represents the European housing situation. The comparison of eight countries considers individual heat and cooling demands as well as sector coupling. Results show that renewable energy communities have the potential to reduce electricity costs due to community investments and load aggregation but do not necessarily lead to more distributed PV. Besides full-load hours, the energy component of electricity tariffs has the highest impact on PV distribution. Under current market conditions, battery energy storage systems are rarely profitable for increasing PV self-consumption but there is potential with power pricing. Renewable energy communities enable individuals to be a prosumer without the necessity of owning a PV system. This could lead to more (community) PV investments in the short term. Hence, it hinders investments in a saturated PV market.

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