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As decentralized electricity generation is supporting grid development into the prosumer era, this paper investigates the economic viability of adding batteries to residential microgrids powered by photovoltaic units, under various electricity pricing schemes. Batteries bring the benefits of grid-stabilization and congestion relief, and they are also becoming cheaper. The problem identified is that the main grid effectively acts as a lossless storage system, especially under the net-metering scheme, whereas using a battery involves investment costs and energy losses. This mismatch is addressed by analysing residential microgrid projects under seven tariff designs, each in seven countries of the European Union, and compare the economic viability of photovoltaic systems with and without batteries. The findings show that the conditions most favourable to batteries are given by a capacity tariff scheme allowing price arbitrage. Based on these findings, the paper discusses possibilities for further support in order to bring the economic viability of microgrids with batteries on par with that of microgrids without batteries.

Decentralized energy production offers an increased share of renewable energy and autonomy compared to the conventional, grid-only solution. However, under the net-metering scheme, the energy losses in batteries translate into financial losses to an investor seeking to move away from grid-only electricity and set up a residential PV+Battery microgrid. Our paper examines a hypothetical support scheme for such a project, designed to balance the economic disadvantage through partially supporting the acquisition of batteries, and thus ensure that the microgrid solution is more attractive than no investment. For this we develop four case studies based on experiments carried out in Greece, Italy, Denmark and Finland. Using the minimization of the Net Present Cost for each project, we compare the PV+Battery solution to the grid-only scenario over 25 years, for a range of electricity prices. The results illustrate first how the success of this project depends on the price of electricity. Second, we find that under current conditions in the respective countries the need for battery support varies between zero in Denmark and 86% in Italy, which reflects how the disadvantages of net metering can only be counterbalanced by either very high electricity price or very high solar resource. Our paper contributes thus to the discussion about the favourable environment for batteries in residential microgrids.

Climate neutrality is one of the greatest challenges of our century, and a decarbonised energy system is a key step towards this goal. To this end, the electricity system is expected to become more interconnected, digitalised, and flexible by engaging consumers both through microgeneration and through demand side flexibility. A successful use of these flexibility tools depends widely on the evaluation of their effects, hence the definition of methods to assess and evaluate them is essential for their implementation. In order to enable a reliable assessment of the benefits from participating in demand response, it is necessary to define a reference value (“baseline”) to allow for a fair comparison. Different methodologies have been investigated, developed, and adopted for estimating the customer baseline load. The article presents a structured overview of methods for the estimating the customer baseline load, based on a review of academic literature, existing standardisation efforts, and lessons from use cases. In particular, the article describes and focuses on the different baseline methods applied in some European H2020 projects, showing the results achieved in terms of measurement accuracy and costs in real test cases. The most suitable methodology choice among the several available depends on many factors. Some of them can be the function of the Demand Response (DR) service in the system, the broader regulatory framework for DR participation in wholesale markets, or the DR providers characteristics, and this list is not exclusive. The evaluation shows that the baseline methodology choice presents a trade-off among complexity, accuracy, and cost.

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