System Implications of Distributed Generation

Abstract

This chapter explores the implications of large-scale implementation of DG in a total energy system that includes both the supply of electricity and the supply of heat. The performance criteria examined are system cost and robustness under stress. The first model is a study of the relative economics of distributed and centralized options for provision of energy services. Widespread use of distributed generation (DG) represents an alternative system architecture for the generation and delivery of electricity and heat. A green-field cost optimization of seasonally varying energy system demands, showed utilization of DG provided overall cost savings of around 25%. In addition, DG technologies produce emissions reductions, and in comparison with CCGT and heat boiler plant, reductions in natural gas use, particularly at peak demand times. This model was used to investigate the implications of introducing DG into an energy system with existing generation plant. Sizeable penetration of DG for base-load application results in the system configuration evolving to mirror the green-field solution, hence ensuring similar system cost and emissions savings. However, a reduced utilization of 46% for existing capacity suggests potentially stranded assets. In addition, problematic economic and technical impacts on the electricity system and industry are suggested from such a rapid penetration of DG technologies. Ongoing modeling investigates endogenous implications of DG penetration including mechanisms for compensating stranded assets, natural gas costs, evolving demand and DG economies of scale. The second model quantifies the potential improvements that DG could bring to the robustness of electricity systems, particularly under conditions of stress. It is hypothesized that a distributed system based primarily upon natural gas cogeneration facilities will be more economical and robust. To determine the reliability advantages of distributed generation, a Monte Carlo simulation was developed to conduct generating capacity adequacy assessments. The model was used to determine the Loss of Load Expectation (hr/yr.) and Loss of Energy Expectation (MWh/yr.) for both a standard test system (consisting of 32 generating units) and for a system consisting of 284 identical 12 MW units. In order to simulate the effects of conflict on the system, the mean time to repair for each unit was increased and the reliability indices re-calculated. The results show that the system consisting of a large number of smaller units is 2 to 5 times less sensitive to changes in the MTTR.