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A large fraction of heat production from power sources is wasted in the environment, despite its numerous potential energy uses, for example, district heating, seawater desalination, or hydrogen production. In this paper, we use the MIXOPTIM methodology to evaluate performance indicators of mixes of electric power sources with and without cogeneration of heat to assess the benefits it entails. It appears from the study that the cogeneration option is highly interesting for mixes with a large nuclear share. The case of France is analyzed in detail, with an evaluation of the overall potential of cogeneration in terms of economic competitiveness as well as in terms of greenhouse gas emission reduction. [ABSTRACT FROM AUTHOR]

The massive penetration of renewable energy sources (RES) that are variable and not "dispatchable", may weaken the power system supply-demand balance. Nuclear power plants (NPP) contribute in part to this daily and seasonal balance thanks to the "load-following" mode in France for example, but there are still limits to their use. These limits prevent a nuclear power modulation as efficient and quickly as the conventional thermal power plants. The need in terms of power ramps for nuclear in a constrained power system has been quantified in previous studies. Nuclear may compensate for the removal of thermal power plants, in order to fulfill energetic strategies of CO2 reduction. The possibility that nuclear reactors can achieve power ramps of significant values (>5%Pn/min) is put forward and could make possible to replace the services currently provided by thermal power plants. The objective of the study is then to use these power system requirements as the main input parameter for the modelling of a current simplified nuclear reactor capable of responding to frequency control within a specific hypothesis framework. In this paper, a French 1300 MW pressurized water reactor is modelled. Parametric studies are carried out in order to reveal technical and technological constraints when increasing electric power ramp. The study explores ways of design, which may influence reactor flexibility, such as the neutron parameter, Doppler coefficient, or the thermohydraulic parameter, delay in the primary loop. [ABSTRACT FROM AUTHOR]

Wind power can be considered one of the most important green sources of electric power. The prediction of wind power is necessary to boost the power grid operations' efficiency and increase power market competitiveness. Artificial neural networks (ANNs) are widely used in prediction applications, including wind power. The Random Vector Functional Link (RVFL) is an efficient ANN model that can be employed in time-series forecasting applications. However, the configuration process of the RVFL needs to be improved. Thus, in this paper, we presented an optimized RVFL network using a new naturally inspired technique called the Capuchin search algorithm (CapSA). The main function of the CapSA is to boost the configuration of the traditional RVFL and enhance its prediction capability. We implement extensive evaluation experiments using public datasets from four wind turbines located in France, using several evaluation measures called RMSE, MAE, MAPE, and R2. The evaluation outcomes reveal that the CapSA-RVFL obtained the best prediction accuracy compared to the original RVFL and several variants of the RVFL model, which verifies that the application of CapSA has a significant contribution to improving the prediction capability of the RVFL. [ABSTRACT FROM AUTHOR]

Recent economics literature emphasises the inextricable link between economic prosperity and efficient energy supply and consumption, arguing vehemently that much of today's prosperity is predicated on secure and reliable energy use and that modern industry would grind to a halt without the necessary energy infrastructure. France is an example of an advanced country with enormous energy infrastructure. The country's economic growth has been rather sluggish in recent years, despite its robust and efficient energy production and consumption. The current study analyses empirically whether France's current sustainable electricity use defies the theoretical and empirical literature. To achieve this objective, the standard tools of growth empirics were used over the period 1961–2015. The Zivot–Andrews trended and de-trended structural break tests, as well as Autoregressive Distributed lag (ARDL) bounds testing were employed to analyse the data. The findings of this study demonstrated that France's economic growth is stimulated by electricity usage, financial development, capital, import, and export. The study sheds light on the feedback impact between economic growth and power usage as well as capital and economic growth. With these findings, we argue that it is not electricity that has ceased to serve a functional purpose in France, rather there is a need for entrepreneurial innovative capacity to create factors that require an infinite horizon for the continued use of electricity, which seems to be impeding the country's economic growth potential, among other things. [ABSTRACT FROM AUTHOR]