Scheduling power and energy resources in the Smarter Network Storage project

Electrical Energy Storage (EES) has many applications within power networks. However, installing EES for a single application or to solve a single problem will rarely justify the required investment. Consequently, the aim of Smarter Network Storage (SNS) is to install large scale EES to engage in a variety of network and commercial services. Prioritizing which services to engage in, selecting the most profitable commercial services and managing the battery’s power and energy resources are all new challenges brought about by this approach. The solutions presented in this paper demonstrate that this deployment of EES is realizable, and provides a route to wide-scale adoption. INTRODUCTION Electrical Energy Storage (EES) has many applications within power networks; examples include peak shaving, frequency response, short-term operating reserve and supporting intermittent generation. However, installing EES for just one application is typically insufficient to make the capital investment worthwhile. The principle goal of Smarter Network Storage is to install large scale EES for a variety of system benefits to maximize its value. , the project is installing the largest battery in Europe – 10 MWh/6 MW/7.5 MVA of lithium-ion storage – at a primary substation (33/11kV) in Bedfordshire, England. The primary purpose of the EES is to defer the need to invest in new network infrastructure by reducing the peak demand. To offset investment costs, revenue will be gained from contracts to provide frequency response and short term operating reserve, as well as being offered in a tolling contract to energy traders. Figure 1: A picture showing the site of the storage (left) and the battery racks (right) The aim of the project is to demonstrate that EES on this scale can serve as a network asset, while providing a return on investment. The success of this demonstration project will build confidence in commercial deployment of EES, and prove a route to wide scale adoption. To achieve this, there are commercial and technical challenges. Electricity demand at the substation needs to be forecast over long term time horizons (to allow tendering for commercial contracts) and short term time horizons (to schedule services and state of charge adjustments in the face of demand volatility). Services must be identified, and scheduled to maximize revenue from the EES. A daily schedule is passed to the real-time energy storage management system to control the state of charge, and real and reactive power set-points needed to dispatch the battery in line with contracted services and DNO requirements. TRIAL SITE AND EES SYSTEM Leighton Buzzard primary sub-station was selected as the site for the project. The site is connected to a grid supply point via two 33kV overhead lines. The peak demand is sufficiently high that, for several days per year, one of these lines would not be sufficient to supply all customers in the event of an outage; consequently, the UK distribution network standards state that reinforcement is required [1]. Conventionally, an additional overhead line and 38MVA transformer would be installed; however, this would be far in excess of the reinforcement required. The proposed alternative was to use EES to supply the demand locally when the demand is high, alleviating the load on the overhead lines. These options, along with the local network topology, are shown in Figure 2. The winter demand and line limits are shown in Figure 3. However, the EES is more expensive than building a new overhead line. Consequently, the EES will tender for commercial balancing services when it is not being used for the Peak Shaving service in order to justify its cost and, ultimately, demonstrate a range of ways to achieve a return on the investment. 23rd International Conference on Electricity Distribution Lyon, 15-18 June 2015