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This article presents a methodological approach for incorporating household consumption characteristics and investment choices into energy efficiency policy models. The approach used is based on country-level stated preferences survey for evaluating consumer decisions and attitudes toward energy efficiency. The decision-making process was analyzed and modeled with logistic regression and applied onto the existing single-family housing stock. By applying the described framework, policymakers, or any other subsidy providing authority aiming to reach specific energy savings target, can obtain the distribution of financial incentives among different income classes. The developed model provides a framework for cost minimization and energy saving maximization. The model provides the minimal level of subsidies needed to achieve energy savings goals or maximum level of energy savings possible with a predefined budget for energy subsidies. The model accounts for consumer disaggregation and all results are provided per expenditure groups. [ABSTRACT FROM AUTHOR]

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The crucial design elements of a good capacity remuneration mechanism are market orientation, insurance of long-term power system adequacy, and optimal cross-border generation capacity utilization. Having in mind these design elements, this research aims to propose a financially fair pricing mechanism that will guarantee enough new capacity and will not present state aid. The proposed capacity remuneration mechanism is an easy-to-implement linear program problem presented in its primal and dual form. The shadow prices in the primal problem and dual variables in the dual problem are used to calculate the prices of firm capacity which is capacity needed for long-term power system adequacy under capacity remuneration mechanism. In order to test if the mechanism ensures sufficient new capacity under fair prices, the mechanism is tested on the European Network of Transmission System Operators for Electricity (ENTSO-E) regional block consisting of Austria, Slovenia, Hungary, and Croatia with simulation conducted for a period of one year with a one-hour resolution and for different scenarios of the credible critical events from a standpoint of security of supply; different amounts of newly installed firm capacity; different short-run marginal costs of newly installed firm capacity; and different capacity factors of newly installed firm capacity. Test data such as electricity prices and electricity load are referred to the year 2018. The results show that the worst-case scenario for Croatia is an isolated system scenario with dry hydrology that results with high values of indicators expected energy not served (EENS), loss of load expectation (LOLE), and loss of load probability (LOLP) for Croatia. Therefore, new capacity of several hundred MW is needed to stabilize these indicators at lower values. Price for that capacity depends on the range of installed firm capacity and should be in range of 1000–7000 €/MW/year for value of lost load (VoLL) in Croatia of 1000 €/MWh and 3000–22,000 €/MW/year for VoLL of 3100 €/MWh that correlates with prices from already established capacity markets. The presented methodology can assist policymakers, regulators, and market operators when determining capacity remuneration mechanism rules and both capacity and price caps. On the other hand, it can help capacity market participants to prepare the most suitable and near-optimal bids on capacity markets. [ABSTRACT FROM AUTHOR]

One of the major tools for the implementation of low carbon strategy goals is increasing the penetration of renewable sources, which are mostly intermittent in nature, into the power system that also increases the needs for additional storage and flexibility capacity in the system. Among other possible solutions, one very most promising tool is the significant electrification of the transport sector. A slightly modified and already verified power system model used for Croatian low-carbon strategy was used here. The PLEXOS software was used to model the Croatian power system by simulating different scenarios. Two scenarios were examined: with and without electric vehicles. This research aimed to evaluate the total decrease in CO2 emissions from both the transport and power sectors due to the increased number of electrical vehicles. The analysis of the Croatian power system was used to assess the flexibility potential of such a large number of electrical vehicles on power system flexibility while considering the volatile nature of wind and solar. Additionally, a question regarding solar availability and simultaneous low-availability of parked electrical vehicles was also examined. [ABSTRACT FROM AUTHOR]