Aggregated power profile of a large network of refrigeration compressors following FFR DSR events

Refrigeration systems and HVAC are estimated to consume approximately 14% of the UK’s electricity and could make a significant contribution towards the application of DSR. In this paper, active power profiles of single and multi-pack refrigeration systems responding DSR events are experimentally investigated. Further, a large population of 300 packs (approx. 1.5 MW capacity) is simulated to investigate the potential of delivering DSR using a network of refrigeration compressors, in common with commercial retail refrigeration systems. Two scenarios of responding to DSR are adopted for the studies viz. with and without applying a suction pressure offset after an initial 30 second shut-down of the compressors. The experiments are conducted at the Refrigeration Research Centre at University of Lincoln. Simulations of the active power profile for the compressors following triggered DSR events are realized based on a previously reported model of the thermodynamic properties of the refrigeration system. A Simulink model of a three phase power supply system is used to determine the impact of compressor operation on the power system performance, and in particular, on the line voltage of the local power supply system. The authors demonstrate how the active power and the drawn current of the multi-pack refrigeration system are affected following a rapid shut down and subsequent return to operation. Specifically, it is shown that there is a significant increase in power consumption post DSR, approximately two times higher than during normal operation, particularly when many packs of compressors are synchronized post DSR event, which can have a significant effect on the line voltage of the power supply

Impact of demand side response on a commercial retail refrigeration system

The UK National Grid has placed increased emphasis on the development of Demand Side Response (DSR) tariff mechanisms to manage load at peak times. Refrigeration systems, along with HVAC, are estimated to consume 14% of the UK’s electricity and could have a significant role for DSR application. However, characterized by relatively low individual electrical loads and massive asset numbers, multiple low power refrigerators need aggregation for inclusion in these tariffs. In this paper, the impact of the Demand Side Response (DSR) control mechanisms on food retailing refrigeration systems is investigated. The experiments are conducted in a test-rig built to resemble a typical small supermarket store. The paper demonstrates how the temperature and pressure profiles of the system, the active power and the drawn current of the compressors are affected following a rapid shut down and subsequent return to normal operation as a response to a DSR event. Moreover, risks and challenges associated with primary and secondary Firm Frequency Response (FFR) mechanisms, where the load is rapidly shed at high speed in response to changes in grid frequency, is considered. For instance, measurements are included that show a significant increase in peak inrush currents of approx. 30% when the system returns to normal operation at the end of a DSR event. Consideration of how high inrush currents after a DSR event can produce voltage fluctuations of the supply and we assess risks to the local power supply system

Power and Energy Analysis for a Commercial Retail Refrigeration System Responding to a Static Demand Side Response

The paper considers the impact of Demand Side Response events on supply power profile and energy efficiency of widely distributed aggregated loads applied across commercial refrigeration systems. Responses to secondary grid frequency static DSR events are investigated. Experimental trials are conducted on a system of refrigerators representing a small retail store, and subsequently on the refrigerators of an operational superstore in the UK. Energy consumption and energy savings during 3 hours of operation, pre and post-secondary DSR, are discussed. In addition, a simultaneous secondary DSR event is realised across three operational retail stores located in different geographical regions of the UK. A Simulink model for a 3Φ power network is used to investigate the impact of a synchronised return to normal operation of the aggregated refrigeration systems post DSR on the local power network. Results show ~1% drop in line voltage due to the synchronised return to operation. An analysis of energy consumption shows that DSR events can facilitate energy savings of between 3.8% and 9.3% compared to normal operation. This is a result of the refrigerators operating more efficiently during and shortly after the DSR. The use of aggregated refrigeration loads can contribute to the necessary load-shed by 97.3% at the beginning of DSR and 27% during 30 minutes DSR, based on a simultaneous DSR event carried out on three retail stores

Analysis, modelling and state estimation for large scale electric demand response

The need for additional reserves increases alongside the intermittency of generation and whilst rotating (conventional) generation is replaced, the system’s inertia reduces and balance volatility increases. Conceptually, any regulation measure from the “generation side” has an equivalent countermeasure from the “demand side”. One of the emerging technologies to provide such balancing services is Demand Response (DR). DR is commercially used, mainly via industrial loads combined with small scale diesel and gas generators. However, there is a lot of potential for DR from residential and commercial loads that remains untapped due to implementation costs, lack of technology expertise, load pattern complexity and the need to simultaneously control numerous sources. The main focus of this thesis is to explore the potential of loads, mainly residential and small commercial, to provide DR services and develop methods focused on accuracy for the most challenging services (frequency regulation), whilst aiming for minimal infrastructure and implementation costs. The main points include analysis of common residential and commercial loads for DR services, focusing on thermostatically controlled loads (TCLs). TCLs are thermal loads which operate via thermostats on a duty cycle (on and off state), between two temperature settings in order to maintain an average set temperature. They use electricity as a primary energy source or for their control and pumps. The next part includes analysis and creation of realistic bottom up models to study aggregated behaviour of TCLs during DR actions, as well as the effect of external factors. Afterwards, a distributed State Estimation algorithm is proposed to increase accuracy of aggregated models and track aggregation models from limited information. A new aggregation framework is proposed, specifically designed for heterogeneous populations, whilst being universal for all TCL types. As such, different TCL types can be aggregated together (e.g. cooling and heating). The results of this thesis show that with proper aggregation modelling, state estimation and dynamic updating in time, accuracy of stochastic aggregated models is improved compared to existing frameworks without the need for expensive thermal sensors. This suggests that with relatively limited information the use of residential and commercial TCLs for DR balancing services, is feasible