Increasing the penetration level of Distributed Generation (DG) into the distribution system is a new challenge for traditional electric power systems. Although it is generally recognised that DG has the potential of reducing energy losses in power systems, inappropriate modelling can lead to a misleading predictions for power loss reduction in DG planning. This paper presents an investigation into the impact of load models on the calculation of energy loss. Following a brief introduction the paper proposes detailed modelling of load in DG planning. Load is divided into three categories: residential, industrial and commercial rather than characterised as the traditional constant PQ. A comparative study of real and reactive power losses for various load models and load levels is carried out using the methodology proposed in this paper. In addition, a long term forecasting model is developed to forecast the future customer demand for residential, commercial and industrial sectors in 2020 for the UK, allowing consideration of various factors and aspects, such as, historical load demand, weather data, economic growth and demographic information. A sample power system is adopted to analyse the system performance under various DG scenarios and at various load levels. Simulation results indicate that load models can significantly affect the load losses calculation in DG planning.
[1]
J. Mutale,et al.
Allocation of losses in distribution systems with embedded generation
,
2000
.
[2]
D. Singh,et al.
Effect of Load Models in Distributed Generation Planning
,
2007,
IEEE Transactions on Power Systems.
[3]
Goran Strbac,et al.
Maximising penetration of wind generation in existing distribution networks
,
2002
.
[4]
J.R. Abbad,et al.
Assessment of energy distribution losses for increasing penetration of distributed generation
,
2006,
IEEE Transactions on Power Systems.
[5]
M. Salama,et al.
Impact of Distributed Generation on Voltage Profile in Deregulated Distribution System
,
2002
.
[6]
L. Söder.
Estimation of reduced electrical distribution losses depending on dispersed small scale energy production
,
1996
.