The further penetration of renewable sources in the grid requires the implementation of energy storages in order to smooth out the variability and intermittent nature of renewables. This paper looks at the possibilities for a storage solution to meet an unprecedented situation of having no power input from renewables or an outage from grid sources for five consecutive days in the highest demand period of the year. The study uses as test case a 1000 house estate in the year 2050 with each property using electrical heating and electrical vehicle charging. The magnitude of power and energy estimated, together with the practicalities is then used to assess current storage solutions suitability and the likely possibilities of new innovations in the storage environment.

Determining the energy consumption level is one of the stages of energy efficiency monitoring facilities. The aim of the article is to adapt the energy baseline to the operating conditions of the facility in accordance with the ISO 50000 Standards requirements. The methodology for determining the energy baseline was proposed to achieve the goal. The three-stage procedure for forming a set of relevant variables of the energy baseline, which allows taking into account the significance of variables, the possibility of their measurement, controllability and control, and the procedure for constructing a multifactorial model of the optimal structure for determining the energy baseline are the main scientific results. This methodology was applied to a boiler house of a district heating system. Relevant variables were formed using a three-stage selection of factors that influence the gas consumption efficiency of the boiler house. Combinatorial algorithm of the group method of data handling was used for gas consumption simulation. The search for models of optimal complexity was performed in six classes of basic functions. The selection of better structures of the mathematical model was realized based on the criteria for its appropriateness (regularity, unbiasedness criterion, Schwartz, determination coefficient) and accuracy of the forecast using the morphological criterion. As a result, a multifactor mathematical model of optimal structure was obtained. The percent forecasting error did not exceed 1%. The significance of the results lies in the fact that the proposed methodology can be applied to any facility.

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This paper provides a high accuracy assessment of domestic demand-side management (DSM) approach in the context of distributed renewable energy sources (RES). To determine the potential of domestic DSM for households, a microgrid model of a typical UK residential estate was developed to simulate the impact of RES. The microgrid model comprises of 15 UK households with appropriate allocation of washing machines (WM), tumble dryers (TD) and dishwashers (DW) in accordance to the statistical data. In order to obtain a high accuracy result, the power consumption of the microgrid model utilises real historical high-resolution data of household energy consumption and RES generation. Thereafter, 40% of distributed wind and solar energy are implemented in the model to produce two individual scenarios. The operation of the white appliances in the model is controlled using a domestic DSM based on a load shifting algorithm. The primary criterion of the DSM considered in this paper is the reduction of energy feedback to the grid in order to decrease the utilisation of the grid and to reduce the transmission losses. The results obtained from the model simulation are compared to the baseline model and discussed with respect to the possible benefits of implementation of domestic DSM under the impact of RES. It has been shown that the self-consumption ratio of the microgrid operating under the DSM is increased by 3% for both scenarios. The model analysis provides highly realistic results which can be used for efficiency assessment of various load shifting methods.

This paper investigates the future of Vehicle-to-Grid technologies to be used in the UK in 2030 using the method of cross impact analysis. The paper describes the procedure of the cross impact matrix generation conducted to produce a multiplicity of scenarios of Vehicle-to-Grid futures. Three consistent scenarios (fossil, average and green) have been chosen for further development, interpretation and analysis to predict the implementation of Vehicle-to-Grid technologies for power grid stabilising and balancing in the future.