Simon Gill

Dynamic Optimal Power Flow for Active Distribution Networks

Active Network Management is a philosophy for the operation of distribution networks with high penetrations of renewable distributed generation. Technologies such as energy storage and flexible demand are now beginning to be included in Active Network Management (ANM) schemes. Optimizing the operation of these schemes requires consideration of inter-temporal linkages as well as network power flow effects. Network effects are included in optimal power flow (OPF) solutions but this only optimizes for a single point in time. Dynamic optimal power flow (DOPF) is an extension of OPF to cover multiple time periods. This paper reviews the generic formulation of DOPF before developing a framework for modeling energy technologies with inter-temporal characteristics in an ANM context. The framework includes the optimization of nonfirm connected generation, principles of access for nonfirm generators, energy storage, and flexible demand. Two objectives based on maximizing export and revenue are developed and a case study is used to illustrate the technique. Results show that DOPF is able to successfully schedule these energy technologies. DOPF schedules energy storage and flexible demand to reduce generator curtailment significantly in the case study. Finally, the role of DOPF in analyzing ANM schemes is discussed with reference to extending the optimization framework to include other technologies and objectives.

Wind Turbine Condition Assessment Through Power Curve Copula Modeling

Power curves constructed from wind speed and active power output measurements provide an established method of analyzing wind turbine performance. In this paper, it is proposed that operational data from wind turbines are used to estimate bivariate probability distribution functions representing the power curve of existing turbines so that deviations from expected behavior can be detected. Owing to the complex form of dependency between active power and wind speed, which no classical parameterized distribution can approximate, the application of empirical copulas is proposed; the statistical theory of copulas allows the distribution form of marginal distributions of wind speed and power to be expressed separately from information about the dependency between them. Copula analysis is discussed in terms of its likely usefulness in wind turbine condition monitoring, particularly in early recognition of incipient faults such as blade degradation, yaw, and pitch errors.

The optimal operation of energy storage in a wind power curtailment scheme

Generator curtailment allows Distribution Network Operators to increase the maximum capacity of distributed renewable generation connections to their networks, but curtailment means lost revenue for generators. Energy Storage Systems (ESS) can mitigate curtailment by time-shifting generation away from congested periods and can combine this with other tasks. This paper develops a linear-programming optimization to maximize the revenue generated by an ESS connected to a wind farm in a curtailment scheme. The storage is used for curtailment reduction and price-arbitrage in an external market. A case study is developed and the optimization applied for storage devices with a range of efficiencies and penetrations. The effect of storage efficiency on revenue is shown to be stronger in price arbitrage than in generation-curtailment. An economic analysis is carried out for a Sodium Sulphur battery store and it is clear that, at current costs, more valuable revenue streams are required to achieve economic viability.

Northern Isles New Energy Solutions: Active network management stability limits

The Northern Isles New Energy Solutions (NINES) project is addressing the current and future energy needs of the Shetland Isles by demonstrating the integration of low carbon energy sources using smart grid technology. In so doing, NINES will facilitate a major step towards a low carbon future for Shetland whilst leading and informing the wider international low carbon energy transition. The principal objective of the NINES project is to enable more renewable connections in a geographical area that is deemed to have the richest renewable energy resources in Europe. As such, the electrically islanded Shetland power network will see significant changes in operation as district heating schemes, domestic space and water heating systems, energy storage systems and new wind connections are developed, deployed and integrated under an active network management system. This paper discusses the role of inter-dependent system models in providing essential inputs to active network management (ANM) design and configuration. Early results from model development and testing are presented with specific focus on the stability limits for the connection of additional renewable generation when operating in conjunction with frequency responsive demand.

Synthesis of wind time series for network adequacy assessment

When representing the stochastic characteristics of wind generators within power system simulations, the spatial and temporal correlations of the wind resource must be correctly modelled to ensure that reserve and network capacity requirements are not underestimated. A methodology for capturing these correlations within a vector auto-regressive (VAR) model is presented, and applied to a large-scale reanalysis dataset of historical wind speed data for the British Isles. This is combined with a wind speed-to-power conversion model trained against historically metered data from wind farms on the Great Britain (GB) electricity system in order to derive a lightweight model for simulating injections of wind power across a transmission network. The model is demonstrated to adequately represent ramp rates, both at a site and network level, as well as the individual correlations between sites, while being suitable for network adequacy studies which may require the simulation of many years of operation.

Evaluation of new voltage operating strategies for integration of distributed generation into distribution networks

With the increasing number of distributed generation connections to distribution networks, the need for better understanding of the distribution network constraints becomes crucial. As distribution networks have not been traditionally designed for two-way power flow, the reverse power flows due to the integration of distributed generation changes voltage profiles and can create significant network management issues related to both thermal and voltage limits. Whilst a large body of theory exists on the management of voltage profiles and the integration of distributed generation into voltage-constrained feeders, there has been limited real world application of these methods to date, in part because network operators are reluctant to undertake significant changes that may affect the reliability of their network. This paper provides a case study of three adjustments to existing management of an 11kV feeder that are simple and feasible to implement and evaluates their impact on connection capacity for distributed generation including the importance of location. These adjustments are: increased operational upper-voltage levels, simple demand-management, and non-firm connections to manage local voltage constraints.

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.

Training Tornado: An Intensive, Cross-Curricular Ph.D. Program in Wind Engineering at the University of Strathclyde

Wind energy, like many modern engineering fields, is a collaboration of disciplines. If one were asked which areas of expertise are needed to design a wind turbine, it would be difficult to come up with a definitive list. The team would definitely include electrical, mechanical, and control engineers, and it would likely combine these skills with those of physicists, meteorologists, and materials scientists, to name but a few. In academia, important research in wind energy is undertaken in all these areas and more, and much of the ground breaking research is conducted at the boundaries between disciplines.

Distributed electricity markets and distribution locational marginal prices: A review

As part of the transition from distribution network operator to distribution system operator (DSO), decentralised pricing of energy is an area that needs to be considered. This paper considers different roles for the DSO in facilitating distributed markets including the decentralised and centralised approaches. The latest work in distributed markets has been reviewed including two major pilot projects involving DSO type operation of distribution markets. The use of distribution locational marginal prices (DLMPs) in distributed markets has been studied as a promising means of directing investment and managing constraints in distribution systems. Some simple case studies involving DLMPs in an example distribution network were modelled using Matpower and it was seen that marginal prices could result in reduced losses and congestion if DLMPs are passed on to distributed energy resources. A case was considered of a bus with losses resulting in DLMPs 6% above the grid import cost and it was seen if the DLMP market was used a generator installed at this bus could reduce the cost of losses by up to 14%.

Modelling the potential impacts of locational versus system-wide strike prices in contracts for difference for low carbon generation

This paper describes the use of a cost-minimisation algorithm to explore the potential impact of two options for financial support for low carbon generation in the form of contracts for difference in a system with locational marginal pricing: 1. with a system-wide strike price; 2. with locational strike prices. A two zone system is modelled with the additional financial support for low carbon generation represented as negative variable costs that have the effect of filling in the difference between wholesale market prices and the strike price, the latter intended to cover the long-run costs of low carbon generation. The British case is modelled in which there is a limit to the total top-up expenditure. It is shown that the case of a system-wide strike price can result in less new low carbon generation capacity compared with the case of locational strike prices, due to the increased top-up spend in the lower price zone more rapidly meeting the constraint on the total cost of top-up payments to low carbon generation. However, it is also shown that the imposition of this constraint leads to a failure of the model to settle on one solution due to the non-convex relationship between installed capacity of low carbon generation and wholesale market price.