DD-DSM: Demonstration of Distributed Demand-side Management as a service to the UK grid operator

One of the challenges of reducing our reliance on fossil fuels for electricity generation is that the low-carbon alternatives, wind, solar, marine and nuclear, are not so easily controllable. This makes it difficult for the grid operator to continuously balance the generation with the demand (a fundamental requirement of power system operation). Energy storage can help but remains expensive on the required scale. Having some control over the demand can be an economic alternative and is known as Demand Side Management (DSM). In many cases, an electrical load, such as air-conditioning, can be operated a little earlier or later without degrading its performance. This is known as Load Shifting and is a very useful aspect of DSM. Loads amenable to DSM can be quite small individually and can be geographically spread throughout the network; a system to employ many such loads for DSM is known as Distributed DSM and is the subject of this project.The team at Loughborough will contribute system modelling and control architecture expertise to a TSB demonstration project, which aims to demonstrate Distributed DSM (D-DSM) as a service to the UK grid operator. This will provide fast response in order to reduce reliance on conventional generation for grid balancing and security and thus permit much greater penetration of renewables and aid in maximising the use of existing assets. The project will deliver a large-scale demonstration of the control of commercial air-conditioning (a/c), with the managed demand aggregating up to the order of megawatts. The project will also deliver a communications, metering and remuneration framework. This framework will be scalable and suitable for extension to other types of distributed demand and to the control of distributed energy resources (e.g. domestic smart appliances and distributed CHP). The value and scope for wide-scale application of the technology across the UK (in terms of financial and carbon savings) will be determined via software modelling and the results of the practical trial.