Using dynamic optimal power flow to inform the design and operation of active network management schemes

Active Network Management (ANM) schemes are providing the communications and control infrastructure to allow the integration of energy storage and flexible demand in distribution networks. These technologies can be characterised as intertemporal in that their operation at different points in time is linked. This paper provides a discussion of the issues created when optimising an ANM scheme containing intertemporal energy technologies. A technique called Dynamic Optimal Power Flow is discussed and a case study is presented. The requirement to use forecasts of renewable energy resources such as wind power is discussed together with the issues that this creates

Review of HPC applications for future power system analysis tools

One of the major challenges in the energy sector is to ensure secure and sustainable energy supply. A growth in the usage of renewable resources which are usually connected at lower distribution levels will lead towards electricity networks that are more complex. Likewise, technology that will allow active demand participation has been developed and would be introduced in networks. It will enable that the part of the power demand of active customers could be shifted away from peak periods. This means that the number of network nodes with active devices will increase rapidly affected by a number of distributed generators and, even more, by utilization of smart meters and electric vehicles that can act both as a consumer and as a source/storage device. Consequently, operation of these new Smart Grids will require a step-change in capabilities of operational tools due to a considerable rise in the number of control variables and reduced time intervals between which generation outputs and prices are calculated. Calculating frequent prices and power flow for systems with a large number of nodes will require very fast computations. Therefore, as the power grid networks become more granulated and more intelligent, their operation and control will become even more challenging due to the size of the underling mathematical problems that need to be solved in various power systems analysis tools. The objective of this paper is to review ways in which High Performance Computing (HPC) can be used in power system analysis, and discuss possible further developments in this field

Shinnel Glen hydro scheme analysis

This interim report outlines details of work carried out by the University of Strathclyde to analyse potentials of a community hydro project in Shinnel Glen area. The main goal of this report is to provide details of the modelling and analysis carried out to investigate the potential of new distributed generation connections to this already voltage constrained feeder

BHA PV scheme analysis

This report details work carried out by the University of Strathclyde (UoS) to help SP Energy Networks (SPEN) with mass deployment of domestic PV systems on an already constrained distribution network. These installations were proposed by the Berwickshire Housing Association (BHA) and installed within the period February 2015 – January 2016. The key objective of the report is to provide an overview of the analysis used to investigate which proposed PV systems were able to be installed, and what effects they would have on the network. This report is produced as part of the Accelerating Renewable Connections (ARC) project for SPEN, which investigates alternative methods to allow integration of new DG connections onto a distribution network that previously was believed to be at full capacity

Impact of strategic behavior and ownership of energy storage on provision of flexibility

Energy Storage Systems (ESS) are expected to provide additional flexibility to managed variable power flows in future power systems. It is believed that the business case for ESS as an alternative to traditional network reinforcements can be improved if the assets are able to access additional revenue streams by participating in energy and ancillary services markets. To enable this, the storage may need to be operated by private merchants to circumvent the unbundling principle applied in electricity markets today. However, it is not clear if the right incentives are in place for these entities to operate the ESS in a way that provides the required flexibility and supports the wider system benefits sought by the System Operator (SO). This work seeks to evaluate the impact of strategic behavior of an independent trader operating ESS in a nodal electricity market. The results indicated that a strategic bidder operating ESS tends to underuse the assets leading to suboptimal solution in terms of market welfare, as well as congestion and curtailment reduction, removing some of the potential benefits the ESS can provide to the power system

Complexity of future power grids : applications of HPC for OPF operational tools

As the power grid networks become more granulated and smarter, their operation and control are becoming even more challenging due to the size of the underling mathematical problems that need to be solved in various power systems analysis tools. This means that there is a need for the modification of existing algorithms to adapt to the new environment. As the optimal power flow (OPF) presents one of the main tools used in power system operation and control, and the Interior Point Method (IPM) is becoming one of the most frequently used OPF solution algorithm, this poster describes ways in which High Performance Computing (HPC) can be used to improve the performances of the IPM application to the OPF

Participation of customers in active demand side participation programs under different pricing schemes

Operation of the power grid is currently undergoing fundamental and significant changes due to implementation of new technologies and attempts to reduce impact on environment, as well as improve security of supply by diversifying generation mix. This paper outlines a price incentive scheduling tool for consumer-based active demand side management that can prove flexibility necessary for operation of systems with high levels of renewable generation penetration. The scheduling tool helps consumers rescheduling the home appliances corresponding to different pricing notifications based on their energy consumption preferences. The analysis of individual household behaviours is carried out for two price scenarios: (i) predefined electricity price tariff and (ii) forecast real time pricing (RTP) developed on the basis of time series analysis

Commercial integration of storage and responsive demand to facilitate wind energy on the Shetland Islands

The Northern Isles New Energy Solutions (NINES) project seeks to implement Active Network Management (ANM) on the Shetland Islands in a manner which reduces customers’ energy consumption, lowers peak demand and facilitates an increase in the proportion of electricity from wind, in order to take advantage of the unique wind resource of the islands. This presentation focuses on the commercial frameworks and trading arrangements necessary to permit additional wind capacity onto the islanded network through the active use of storage and responsive demand technologies. The network is modelled using a Dynamic Optimal Power Flow (DOPF) framework, which allows the unit scheduling of different combinations of generation, storage and demand to be optimised according to different optimisation goals. This is used as a foundation to explore the value of wind energy and storage in meeting the long-term goals of the network, the forms of trading and markets which may be used to contract services, and the potential for responsive demand to facilitate different forms of connection agreements and curtailment strategies for new wind farms. In modelling the Shetland network using Dynamic Optimal Power Flow (DOPF), the optimum unit commitment schedule is determined across a daily horizon for different network topologies, including variable levels of wind generation, storage and demand-side response - primarily storage heaters and water tanks controllable by the Distribution System Operator via Active Network Management. This informs the level of wind generation which may be accepted onto the network, and allows the creation and testing of commercial agreements both for wind generators keen to utilise the unique resource of the islands, as well as allowing third-party operation of storage, and reducing the peak energy demand of domestic consumers. This allows a greater level of demand to be supplied by non-thermal sources through the time-shifting of demand against the availability of the wind resource. Support of the grid through reserve and response is considered in the context of maintaining system stability, with the aim of procuring services through third-party contractual arrangements. Data collected from the operational history of the islands and technology trials demonstrate the feasibility of these approaches and their potential applicability to other constrained distribution networks with the potential for high levels of wind generation. The data from trials of domestic storage equipment and modelling of wind curtailment demonstrate quantitatively the ways in which commercial integration of modern storage and responsive demand can be used to increase the utilisation of wind energy on islanded networks, which may often have increased renewable resources but limited grid capacity. It is shown that there are a number of trading and connection agreements which can be used to contract for generation and ancillary services to meet these goals

Integration of energy storage to improve utilisation of distribution networks with active network management schemes

Active Network Management (ANM) has been developed over the past decade in the UK as a potential solution to facilitate integration of Distributed Generation (DG) in distribution networks. It is used to manage network limits and allows significantly cheaper and faster connections for DGs, compared to the network reinforcement. However, ANM can help with the DG penetration only to a certain extent as new DG connections in constrained networks will result in curtailment. This paper investigates the levels of energy storage and locations of its placement in reducing curtailment of DGs and improving utilisation of distribution networks with ANM solutions. It evaluates and compares energy storage values of energy storage capacity at different locations, and using the real network and wind data provided by SP Energy Networks (SPEN) Accelerating Renewable Connection (ARC) project

Accelerating renewable connections through coupling demand and distributed generation

The objective of this paper is to investigate the options for using local demand to accelerate the connection of renewable Distributed Generation (DG) capacity. It presents a range of architectures for operating Distributed Energy Systems (DESs) that contain local demand and distributed generation. The concept of a DES is that demand is supplied by local DG either using privately owned distribution assets or a public distribution network owned by a Distribution Network Operator (DNO). Operation of a DES can help manage variability in DG output, reduce curtailment in Active Network Management (ANM) schemes, and assist the DNO in managing network constraints. They also provide a move towards local trading of electricity with potential financial and non-financial benefits to both distributed generators and local demand customers