Increasing the capacity of distributed generation in electricity networks by intelligent generator control

The rise of environmental awareness as well as the unstable global fossil fuel market has brought about government initiatives to increase electricity generation from renewable energy sources. These resources tend to be geographically and electrically remote from load centres. Consequently many Distributed Generators (DGs) are expected to be connected to the existing Distribution Networks (DNs), which have high impedance and low X/R ratios. Intermittence and unpredictability of the various types of renewable energy sources can be of time scales of days (hydro) down to seconds (wind, wave). As the time scale becomes smaller, the output of the DG becomes more difficult to accommodate in the DN. With the DGs operating in constant power factor mode, intermittence of the output of the generator combined with the high impedance and low X/R ratios of the DN will cause voltage variations above the statutory limits for quality of supply. This is traditionally mitigated by accepting increased operation of automated network control or network reinforcement. However, due to the distributed nature of RES, automating or reinforcing the DN can be expensive and difficult solutions to implement. The Thesis proposed was that new methods of controlling DG voltage could enable the connection of increased capacities of plant to existing DNs without the need for network management or reinforcement. The work reported here discusses the implications of the increasing capacity of DG in rural distribution networks on steady-state voltage profiles. Two methods of voltage compensation are proposed. The first is a deterministic system that uses a set of rules to intelligently switch between voltage and power factor control modes. This new control algorithm is shown to be able to respond well to slow voltage variations due to load or generation changes. The second method is a fuzzy inference system that adjusts the setpoint of the power factor controller in response to the local voltage. This system can be set to respond to any steady-state voltage variations that will be experienced. Further, control of real power is developed as a supplementary means for voltage regulation in weak rural networks. The algorithms developed in the study are shown to operate with any synchronous or asynchronous generation wherein real and reactive power can be separately controlled. Extensive simulations of typical and real rural systems using synchronous generators (small hydro) and doubly-fed induction generators (wind turbines) have verified that the proposed approaches improve the voltage profile of the distribution network. This demonstrated that the original Thesis was true and that the techniques proposed allow wider operation of greater capacities of DG within the statutory voltage limits

Enabling Competing Energy Storage Technologies: Towards a Carbon-Neutral Power System

Assessment of energy storage technologies at a macro-scale for grid integration, has often focused on singular technologies and neglected competition between them, thus leaving out of the optimization the decision of which energy storage to prioritize. We present a systematic deployment analysis method that enables system-value evaluation in perfect competitive markets and demonstrate its application to 20 different energy storage technologies across 40 distinct scenarios for a representative future power system in Africa. Our results demonstrate the significant benefits of optimizing energy storage with competition compared to without (+10% cost savings) and highlight the relevance of several energy storage technologies in various scenarios. This work provides insights into the role of multi-technology energy storage in carbon-neutral power systems and informs future research and policy decisions