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• Mechanisms to encourage clean energy in Spain from 2005 to the present are analyzed. • FiT and FiP mechanisms can be effective in promoting new renewable projects. • Experience suggests that excessive support can jeopardize the entire market. • A transitional retribution scheme has proven to be effective if correctly supervised. This research paper delves into the central mechanisms implemented in Spain to foster the adoption of clean energy projects. The study scrutinizes various mechanisms established from 2005 onwards, evaluating their efficacy in achieving the desired outcome of supporting clean energy project implementation. The aim is to comprehensively assess the associated costs, effectiveness, and attainment of renewable energy objectives stemming from implementing diverse support schemes. This paper explores the effectiveness of feed-in tariffs and feed-in premium mechanisms in promoting the integration of new renewable energy generation into the power system. However, the Spanish experience suggests that exhaustive planning control is imperative to prevent excessive support costs that could jeopardize the entire market and cause a significant rise in final energy costs. The research studies the support schemes and associated market distortion and presents the roadmap from regulated tariffs to a "total market" for wind and solar energy. The findings demonstrate that, under proper supervision and planning, a transitional retribution scheme effectively promotes renewable energy plant integration. Finally, the analysis examines the need to regulate the excess benefits that non-emitting power sources receive in a marginal price market, as this can lead to market imbalances and a substantial increase in final costs. These plans serve as a crucial tool in achieving the decarbonization objectives of the European Power System. [ABSTRACT FROM AUTHOR]

• Pioneer Spain: first country to include in grid code the synthetic inertia capability. • Synthetic inertial response of a PV inverter studied based on the Spanish grid code. • Analyzed the role of power plant controller in the dynamic response of the facility. • PV system able to contribute to frequency control providing an inertial response. As the large-scale integration of renewable energy grows, inertia in power systems is reduced, which causes the rate of change of frequency to increase and worsens the frequency nadir during disturbances. There is, therefore, an urgent need to accelerate the development of international standards and regulations that require solar PV systems and other renewable installations to also contribute to stability in the network by emulating inertia. Spain is a pioneer in this field: it is currently the only country that includes the synthetic inertia technical requirement in its grid code. In this context, the present paper analyzes the synthetic inertial response of a PV system model that forms part of an actual PV power plant in Spain under two scenarios, according to its grid code: i) when measurements are conducted at the power conversion PV system level and hence only its control algorithms are executed; and ii) when measurements are conducted at the power plant level and the power plant controller also influences the response of the entire installation. Among its aims, this paper seeks to thoroughly assess the response of an actual PV power conversion system that has the capability of actively contributing to frequency regulation in a network and to critically analyze the suitability of having a power plant controller when the PV facility contributes to power-frequency control by means of an inertial response. The results reveal, at the power conversion PV system level, that the inertia emulation module significantly reduces the response times of the installation to changes in frequency -by more than 68% in the worst case under frequency increases, and by 73% under frequency decreases, thus contributing to more rapid power-frequency regulation in the network. However, at the power plant level, the power plant controller disturbs the PV power conversion system's behavior and causes the opposite effect: response times increase -up to more than 7% in the most unfavorable case when the inertia module is enabled. [ABSTRACT FROM AUTHOR]

Wind power is one of the most important renewable energy sources worldwide. However, integrating these technologies in electricity markets faces challenges due to the intermittent wind speed, resulting in potential imbalances within power grids and subsequent inefficiencies. Traditional approaches for modeling the uncertainty simulate fixed wind power values in operational and planning models, which work well for the short term but are inadequate for medium-term decision-making due to lower forecasting accuracy and the inability to differentiate the imbalance risk faced in each simulated value. This paper proposes a novel methodology for incorporating wind energy imbalance risk into medium-term generation planning models. For this, we first simulate realistic wind power scenarios and perform a fitting distribution process to characterize the hourly wind power behavior. Then, we model the imbalance risk using quadratic-uncertainty cost functions for each simulated value. Subsequently, we conduct a temporal aggregation to reduce the computational burden, preserving the conceptual framework of the imbalance risk modeling. Finally, we propose a medium-term generation planning model that includes the imbalance risk model and the temporal aggregation strategy. Our approach is evaluated in a real-size case study formed by Spain, Portugal, and France's electricity markets, demonstrating accurate wind power imbalance risk modeling and lowered planning costs. • A new methodology to include wind energy imbalance risk in generation planning models. • Introducing a fitting process for modeling the distribution asymmetries of wind power. • Proposing a temporal aggregation method for efficient imbalance risk modeling. • The methodology is validated in Spanish, Portuguese, and French electricity markets. [ABSTRACT FROM AUTHOR]

The increased penetration of renewable energy sources (RESs) as an effective mechanism to reduce carbon emissions leads to an increased weather dependency for power and energy systems. This has created dynamic operation and degradation phenomena, which affect the lifetime estimation of the assets operated with RESs. For the reliable and efficient operation of RES it is crucial to monitor the health of its constituent components and feature selection is a crucial step for building robust and accurate health monitoring approaches. In this context, this paper presents a probabilistic feature selection approach, which probabilistically weights and selects features through a heuristic and iterative process for an improved asset lifetime estimation. Power transformers are key power grid assets and they are used to demonstrate the validity and impact of the proposed approach. The approach is tested on two different photovoltaic power plants operated in Spain and Australia. Results consistently show that the proposed feature-selection approach reduces the prediction error and consistently selects relevant features. The approach has been applied to transformer lifetime estimation, but it can be generally applied to assist in the lifetime estimation of other components operated in RESs. Part of the studies presented here as well as source codes are all open-source under the GitHub repository https://github.com/iramirezg/FeatureSelection. • Probabilistic feature selection approach for improved asset lifetime estimation. • Integration of environmental features for improved renewable-operated asset lifetime. • Systematic and robust feature weighting methodology. • Improved transformer lifetime estimation including sensor and environmental data. • Validated on two real photovoltaic power plant case studies. [ABSTRACT FROM AUTHOR]

The European Commission and EU Member States have recently promoted legislation (under the REPower EU Plan) to accelerate renewable energy projects by allowing the elimination or reduction of environmental assessment and public participation in the approval procedure. To avoid adverse effects on the environment, these regulations propose the exclusion of certain areas (identified through available information on protected and/or environmentally sensitive areas) from the procedure. This paper aims to evaluate whether such measures are effective to avoid damage to biodiversity from the implementation of photovoltaic energy. To this end, we studied the distribution and abundance of a threatened bird species, the Black-bellied Sandgrouse, at two geographic scales: i) regional: Andalusia (southern Spain); ii) local: Campo de Tabernas (an excellent example of the semi-arid ecosystems of southeastern Spain) and evaluated the quality of the information that Administrations have on the species by comparing it with own censuses. We also assessed the effectiveness of the environmental impact procedure for photovoltaic plants planned in Campo de Tabernas. Data from the regional Administration reveal that Andalusian protected areas cover a minimal part (17.7%) of the species' range. Moreover, neither the regional nor the national Administration have reliable and updated information on the distribution of the species in Campo de Tabernas (only 17% of the current distribution area is known). The wrong choices made by developers about where to locate the photovoltaic plants together with wrong decisions of the regional Administration (with land-use planning competences, including the planning of power plant locations) have led to the loss of 630 ha of the species' range in Campo de Tabernas. Public participation of experts prevents, through allegations to the projects, an important part of the impact on the species. Policy implications: the information that the Administrations have on this species does not allow them to make proper decisions on where to apply renewable acceleration. Obtaining complete and updated information on the distribution of endangered species to elaborate detailed wildlife sensitivity areas is essential and urgent before implementing measures to accelerate renewables. • The new EU renewable acceleration directives are analysed here for the first time. • A threatened species becomes locally extinct due to solar power plants' poor planning. • Involving experts in EIA procedure greatly reduces the impact on a threatened species. • The design of renewable go-to areas demands specific research on threatened species. • Current EU legislation to accelerate renewables will negatively affect biodiversity. [ABSTRACT FROM AUTHOR]

This paper presents a model for optimizing the life cycle economic and environmental impacts of a hybrid renewable energy and battery storage system – as energy supply technologies (EST) for off-grid farms. Micro-hydropower and photovoltaics represent the primary renewable energy (RE) sources, with batteries and a diesel generator considered as possible back-up systems. A modified Non-dominated Sorting Genetic Algorithm II (NSGA-II) was developed and applied to a case study farm in Southern Spain and provided different EST solutions to optimize a design based on economic (life cycle costing or LCC) and environmental (life cycle assessment or LCA) constraints. The results highlighted that cases with a strong dependence on batteries could achieve minimum costs and lower impacts for climate change and energy resources (non-renewable fuels). In contrast, the optimal system for minimizing the consumption of material resources (metals/minerals) resulted in higher fuel use, which was up to 25% more expensive. The optimal EST solutions used up to 37% of the total energy generated; however, the results were sensitive to energy production-demand distributions. This methodology can help identify the most cost-effective solutions with the lower environmental impacts for decarbonizing the agricultural sector. [Display omitted] [ABSTRACT FROM AUTHOR]