Energy use in Sweden has increased by nearly 30 % since 1970. The overallelectricity consumption has increased by 170 % during the same period of time. Althoughnuclear and hydro power stations generate more than 70% of the total electricity demand,wind and solar electricity generation has been significantly increased over the last decade.The building sector in Sweden consumes nearly half of the overall electricity demand andis continuously increasing due to several factors, such as population growth, increasedincomes and low electricity price. In order to reduce the energy footprint of Swedishhouseholds, small-scale roof-mounted photovoltaic (PV) installations may be a promisingsolution by increasing the self-consumption of each residency.Taking into account that the electricity price in Sweden varies during a year, a method toevaluate how much energy can be saved by installing a PV system could be useful forpromoting the investments in renewables and energy saving measures. For this purposetwo calculations are needed: a first that forecasts the load demand of a Swedish householdbased on a set of parameters (living area, number of occupants etc.) and a second thatpredicts the electricity generation of a PV system at a specific location. Both of these taskswere estimated on an hour basis.Within the framework of this thesis a method has been developed in Python programminglanguage that performs the above mentioned tasks. For estimating the hourly load demandof a residency an Artificial Neural Network (ANN) has been developed that is beingtrained by data of electricity consumption obtained by an end-use metering campaign of400 Swedish households which has been launched in 2005 by the Swedish Energy Agency(SEA).On the other hand, for estimating the PV electricity generation at a specific location andtime, available data from the Photovoltaic Geographical Information System (PVGIS)were downloaded. PVGIS is an online calculator of PV performance and solar irradiancedeveloped by the European Commission.A sustainable energy system is based on consumers with environmental awareness. Themethods developed in this thesis would try to promote small-scale PV installations inSwedish residencies by informing individuals of how economically and environmentallyprofitable is to invest in renewable energy sources and energy saving measures