Ben Potter

A Peak Reduction Scheduling Algorithm for Storage Devices on the Low Voltage Network

Reinforcing the Low Voltage (LV) distribution network will become essential to ensure it remains within its operating constraints as demand on the network increases. The deployment of energy storage in the distribution network provides an alternative to conventional reinforcement. This paper presents a control methodology for energy storage to reduce peak demand in a distribution network based on day-ahead demand forecasts and historical demand data. The control methodology pre-processes the forecast data prior to a planning phase to build in resilience to the inevitable errors between the forecasted and actual demand. The algorithm uses no real time adjustment so has an economical advantage over traditional storage control algorithms. Results show that peak demand on a single phase of a feeder can be reduced even when there are differences between the forecasted and the actual demand. In particular, results are presented that demonstrate when the algorithm is applied to a large number of single phase demand aggregations that it is possible to identify which of these aggregations are the most suitable candidates for the control methodology.

Design, Implementation and Characterisation of a Contactless Power Transfer System for Rotating Applications

This paper describes the design, implementation and characterisation of a contactless power transfer system for rotating applications. The power transfer system is based upon a zero-voltage-switched, full-bridge, DC-DC converter, but utilises a non-standard transformer. This transformer allows power transfer between its primary and secondary windings while also allowing free rotation between these windings. The aim of this research is to develop a solution that could replace mechanical slip-rings in certain applications where a non-contacting system would be advantageous. Based upon the design method presented in this paper, a 2 kW prototype system is constructed. Results obtained from testing the 2 kW prototype are presented and discussed. This discussion considers how the performance of the transformer varies with rotation and also the overall efficiency of the system

A Method for Accurate Transmission Line Impedance Parameter Estimation

Real-time estimation of power transmission line impedance parameters has become possible with the availability of synchronized phasor (synchrophasor) measurements of voltage and current. If sufficiently accurate, the estimated parameter values are a powerful tool for improving the performance of a range of power system monitoring, protection, and control applications, including fault location and dynamic thermal line rating. The accuracy of the parameter estimates can be reduced by unknown errors in the synchrophasors that are introduced in the measurement process. In this paper, a method is proposed with the aim of obtaining accurate estimates of potentially variable impedance parameters, in the presence of systematic errors in voltage and current measurements. The method is based on optimization to identify correction constants for the phasors. A case study of a simulated transmission line is presented to demonstrate the effectiveness of the new method, which is better in comparison with a previously proposed method. The results, as well as limits, and the potential extensions of the new method are discussed.

Control methodologies: Peak reduction algorithms for DNO owned storage devices on the Low Voltage network

The Distribution Network Operators (DNOs) role is becoming more difficult as electric vehicles and electric heating penetrate the network, increasing the demand. As a result it becomes harder for the distribution networks infrastructure to remain within its operating constraints. Energy storage is a potential alternative to conventional network reinforcement such as upgrading cables and transformers. The research presented here in this paper shows that due to the volatile nature of the LV network, the control approach used for energy storage has a significant impact on performance. This paper presents and compares control methodologies for energy storage where the objective is to get the greatest possible peak demand reduction across the day from a pre-specified storage device. The results presented show the benefits and detriments of specific types of control on a storage device connected to a single phase of an LV network, using aggregated demand profiles based on real smart meter data from individual homes. The research demonstrates an important relationship between how predictable an aggregation is and the best control methodology required to achieve the objective.

Small power load disaggregation in office buildings based on electrical signature classification

This paper assesses the application of Non-Intrusive Appliance Load Monitoring (NIALM) methods for disaggregating electricity consumption in office buildings. The focus of the research is on small power equipment, which can represent up to 50% of the electricity use in buildings fitted with high efficiency building services. Research in this field has led to numerous algorithms being developed for use with NIALM systems, however, due to the highly variable nature of electrical appliances no suitable common characteristic has been identified for disaggregation. This paper presents an analysis of a set of electrical signatures based on transient and current-voltage phase shift during steady-state conditions for which subsets of the signatures are considered for identifying different small power loads. The ability of this approach to disaggregate appliance loads is demonstrated with the idea of applying disaggregation techniques during energy audits of office buildings.

A novel battery network modelling using constraint differential evolution algorithm optimisation

A novel battery network system with optimal management of energy is proposed.An optimal management strategy has been implemented.The constraint differential evolution optimisation is applied to above system.The new strategy can remove more peak areas of forecasted demand data.The proposed method is also compared to the self-adaptive control algorithm. The use of battery storage devices has been advocated as one of the main ways of improving the power quality and reliability of the power system, including minimisation of energy imbalance and reduction of peak demand. Lowering peak demand to reduce the use of carbon-intensive fuels and the number of expensive peaking plant generators is thus of major importance. Self-adaptive control methods for individual batteries have been developed to reduce the peak demand. However, these self-adaptive control algorithms of are not very efficient without sharing the energy among different batteries. This paper proposes a novel battery network system with optimal management of energy between batteries. An optimal management strategy has been implemented using a population-based constraint differential evolution algorithm. Taking advantage of this strategy the battery network model can remove more peak areas of forecasted demand data compared to the self-adaptive control algorithm developed for the New York City study case.

Improving the accuracy of synchrophasor-based overhead line impedance measurement

Knowledge of real-time impedance parameters of overhead lines can significantly enhance power system monitoring and control applications such as dynamic line rating and fault location. To ensure high accuracy of the determined parameters, methods for error detection and correction are required. In this paper the impact and correction of systematic errors in the voltage phasors are considered and corrected using an optimization procedure. The effectiveness of the proposed method was demonstrated in a case study involving a laboratory-based overhead line model. In contrast to a least squares-based estimator, a significant improvement in the impedance parameter accuracy was achieved, even when only phasor measurements from similar loading conditions were used.

Synchrophasor-based transmission line impedance measurement

Accurate values of transmission line impedance parameters can enhance the efficiency and reliability of power system operation. The parameter values can be calculated using synchronized phasor measurements of voltage and current at the line ends. The objective of this paper is to investigate how the accuracy and uncertainty of the calculated parameter values depends on the level of noise and distortion in the measured signals during different line loading conditions. The investigation is conducted using a laboratory-based transmission line model and measurement system. The details of the test system and operation are presented in this paper.

Bond graph models of DC-DC converters operating for both CCM and DCM

In this paper, bond graphs are employed to develop a novel mathematical model of conventional switched-mode DC-DC converters valid for both continuous and discontinuous conduction modes. A unique causality bond graph model of hybrid models is suggested with the operation of the switch and the diode to be represented by a modulated transformer with a binary input and a resistor with fixed conductance causality. The operation of the diode is controlled using an if-then function within the model. The extracted hybrid model is implemented on a boost and buck converter with their operations to change from CCM to DCM and to return to CCM. The vector fields of the models show validity in a wide operational area and comparison with the simulation of the converters using PSPICE reveals high accuracy of the proposed model, with the normalised root means square error and the maximum absolute error remaining adequately low. The model is also experimentally tested on a buck topology.

Sub-agent elements for control methods in multi-agent energy management system

Increased penetration of generation and decentralised control are considered to be feasible and effective solution for reducing cost and emissions and hence efficiency associated with power generation and distribution. Distributed generation in combination with the multi-agent technology are perfect candidates for this solution. Pro-active and autonomous nature of multi-agent systems can provide an effective platform for decentralised control whilst improving reliability and flexibility of the grid.