Recent studies show that energy consumption of buildings has dramatically increased over the last decade, accounting for more than 35% of global energy use. However, with proper operation, significant energy savings can be achieved. Demand response is envisioned as a key enabler of this operation enhancement, as it may contribute to the reduction of demand peaks and maximization of renewable energy exploitation while mitigating potential problems with grid stability. In this article, a system based on artificial intelligence that solves the complex multi-objective problem to bring demand response programs to the residential sector is proposed. Through the application of novel machine learning-based algorithms, a unique control loop is developed to help dwellers determine how and when to use their appliances. The feasibility and validity of the proposed system has been demonstrated in a real-world neighbourhood where a notable reduction and shift of electricity demand peaks has been achieved. Concretely, in accordance with extreme changes in the energy prices, the users have demonstrated the ability to shift their demand to periods with lower prices as well as reducing power consumption during periods with higher prices, thus fully translating the demand peak in time.

Solving the issue of energy security for geographical islands presents a one-of-a-kind problem that has to be tackled from multiple sides and requires an interdisciplinary approach that transcends just technical and social aspects. With many islands suffering in terms of limited and costly energy supply due to their remote location, providing a self-sustainable energy system is of utmost importance for these communities. In order to improve upon the status quo, novel solutions and projects aimed at increasing sustainability not only have to consider optimal utilization of renewable energy potentials in accordance with local conditions, but also must include active community participation. This paper analyzes both of these aspects for island communities and brings them together in an optimization scenario that is utilized to determine the relationship between supposed demand flexibility levels and achievable savings in a setting with variable renewable generation. The results, specifically discussed for a use case with real-world data for the La Graciosa island in Spain, show that boosting community participation and thus unlocking crucial demand flexibility, can be used as a powerful tool to augment novel generation technologies with savings from flexibility at around 7.5% of what is achieved purely by renewable sources.

Apart from numerous technical challenges, the transition towards a carbon-neutral energy supply is greatly hindered by limited economic feasibility of renewable energy sources. This results in their slow and bounded penetration in both commercial and residential sectors that are responsible for over 40% of final energy consumption. This paper aims to demonstrate that combined application of sophisticated planning methodologies at building-level and presents incentive mechanisms for renewables that can result in prosumers, featuring hybrid renewable energy systems (HRES), with economic performance comparable to that of conventional energy systems. The presented research enhances existing planning methodologies by integrating appliance-level demand side management into the decision process and investigates its effect on the planning problem. Moreover, the proposed methodology features an innovative and holistic approach that simultaneously assess electrical and thermal domain in both an isolated and grid-connected context. The analyzed hybrid system consists of solar photovoltaic, wind turbine and battery with thermal supply featuring solar thermal collector and a ground-source heat pump. Overall optimization problem is modeled as a mixed-integer linear program, while ranking of all feasible alternatives is made by the multicriteria decision-making algorithm against several technological, economic, and environmental criteria. A real-life scenario of energy system retrofit for a building in the United Kingdom was employed to demonstrate overall cost savings of 12% in the present market and regulation context.