SUMMARYElectricity consumption data profiles that include details on the consumption can be generated with a bottom-up load models. In these models the load is constructed from elementary load components that can be households or even their individual appliances. In this work a simplified bottom-up model is presented. The model can be used to generate realistic domestic electricity consumption data on an hourly basis from a few up to thousands of households. The model uses input data that is available in public reports and statistics. Two measured data sets from block houses are also applied for statistical analysis, model training, and verification. Our analysis shows that the generated load profiles correlate well with real data. Furthermore, three case studies with generated load data demonstrate some opportunities for appliance level demand side management (DSM). With a mild DSM scheme using cold loads, the daily peak loads can be reduced 7.2% in average. With more severe DSM schemes the peak load at the yearly peak day can be completely leveled with 42% peak reduction and sudden three hour loss of load can be compensated with 61% mean load reduction.

The public support in PV technologies and increasing markets have resulted in extensive applications of grid-connected PV, in particular in the consumer side and electricity distribution grid. In this paper the effects of a high level of grid connected PV in the middle voltage distribution network have been analyzed. The emphasis is put on static phenomena, including voltage drop, network losses and grid benefits. A multipurpose modeling tool is used for PV analysis in Lisbon and Helsinki climates. All network types studied can handle PV without problems with an amount of PV equaling at least up to the load (1kW p /household). The comb-type network showed the best performance. The PV is unable to shave the domestic load peak in the early evening hours but through orientating the PV panels both to east and west, the noon peak from PV can be reduced by 30 %. PV integration reduces network losses positively up to a 1kW p /hh (100% of annual domestic load) level. For 2 kW p /hh all but the comb-type networks demonstrate clear over-voltage situations and the annual network losses are much higher than without PV.

Irregularities in power output are characteristic of intermittent energy, sources such as wind energy, affecting both the power quality and planning of the energy system. In this work the effects of energy storage to reduce wind power fluctuations are investigated. Integration of the energy storage with wind power is modelled using a filter approach in which a time constant corresponds to the energy storage capacity. The analyses show that already a relatively small energy storage capacity of 3 kWh (storage) per MW wind would reduce the short‐term power fluctuations of an individual wind turbine by 10%. Smoothing out the power fluctuation of the wind turbine on a yearly level would necessitate large storage, e.g. a 10% reduction requires 2–3 MWh per MW wind. Copyright © 2005 John Wiley & Sons, Ltd.

The continuously increasing application of distributed photovoltaics (PV-DG) in residential areas around the world calls for detailed assessment of distribution grid impacts. Both photovoltaic generation and domestic electricity demand exhibit characteristic variations on short and long time scales and are to a large extent negatively correlated, especially at high latitudes. This paper presents a stochastic methodology for simulation of PV-DG impacts on low-voltage (LV) distribution grids, using detailed generation and demand models. The methodology is applied to case studies of power ow in three existing Swedish LV grids to determine load matching, voltage levels and network losses at dierent PV-DG penetration levels. All studied LV grids can handle signicant amounts of PV-DG, up to the highest studied level of 5 kW p PV per household. However, the benets of PV-DG in terms of relative improvement of on-site reduction of demand, mitigated voltage drops and reduced losses were most signicant at a penetration level of 1 kW p PV per household.

Rural electrification (RE) can be modelled as a multifactorial task connected to a large number of variables: decision makers need to choose the appropriate options by considering not only the techno-economic competitiveness but also socio-cultural dynamics and environmental consequences, making the task intricate. Many rural electrification projects have failed due to lack of attention to the issues beyond financial and technical dimensions. This paper presents a standardized approach for decision making concerning the extension of electricity services to rural areas. This approach first determines whether the supply provision should be grid expansion or off-grid on the basis of levelized cost of delivered electricity. If the grid expansion is found nonviable over off-grid options then a multicriteria decision aiding tool, SMAA-2 (Stochastic Multicriteria Acceptability Analysis), will evaluate off-grid technologies by aggregating 24 criteria values. While applying this approach, the delivered costs of electricity by the grid in remote areas within the 1-25 km distances vary in a range of 0.10-7.85 US$/kWh depending on the line lengths and load conditions. In the off-grid evaluation, the solar PV