Use of smart meters for frequency and voltage control

A load control scheme that used frequency measurements of a smart meter for controlling domestic appliances to provide primary response was investigated. An experimental rig was developed to test and demonstrate the scheme. The amount of loads to be controlled to limit the frequency drop of the Great Britain (GB) power system to a set of minimum allowable frequencies was found. Operating speeds and the limitations of the components of the load controller in providing primary response are discussed. It is shown that if smart meters are to play any role in primary response then the speed at which the system frequency is measured must be increased very considerably. Load profile of fridges/freezers, washers/dryers and hobs/ovens in the GB power system were constructed. Then the percentages of appliances required to be in the load control scheme to shed the estimated amount of controllable loads, were calculated. It is found that the total controllable load requirement can be provided using fridges and freezers alone. Since many washers/dryers and hobs/ovens do not operate at night, they can not then provide a significant amount of controllable loads. However, using these appliances in the day time, the amount of fridges and freezers in the load control scheme can be reduced significantly. The ability of the proposed smart metering system in the UK to report available demand response from the appliances to the network operator was investigated. It was found that the communication network would not support reporting demand response in near real-time. Using load profiles of appliances for 40,000 houses, it was shown that by installing aggregation devices at distribution transformers and substations, the demand response can be reported to the network operator every minute. By aggregating and sending changes only, the impact of reporting demand response in near real-time on communication network reduces significantly. The ability of a state estimator to estimate distribution network voltages using smart meter measurements obtained on the previous day was evaluated. The improvement 10 of the accuracy of the estimated voltages with the number of nodes providing near real-time measurements obtained from distributed generators was also investigated. It was found that when the voltages are estimated using the previous day’s measurements without using any near real-time measurement, the voltage error at all nodes were high. By using near-real time measurements obtained from distributed generators, the error can be reduced significantly