Assessing Distribution Network Limits to Connecting Renewable Energy Generation
Dr Gareth Harrison, Professor Robin Wallace
Distributed generation gives rise to a range of technical issues of which voltage rise tends to be the most significant. While adverse effects can be mitigated it is often at significant cost to the developer. One way of minimising these problems is for network operators to issue guidance regarding the existence, or otherwise, of spare connection capacity. To do this, DNOs need to ascertain the capacity of new DG that may be connected to their distribution networks. Our approach uses Optimal Power Flow (OPF) to maximise capacity at specified locations while respecting network constraints including fault levels. [More...]
Thipnatee Sansawatt (PhD Study - EPSRC Supergen FlexNet)
Supervisors: Dr Gareth Harrison, Professor Robin Wallace
Previous research projects separately developed 'intelligent' decentralised controllers for generation to minimise voltage impacts and investigated strategies for controlling tap-changing transformers. This project combines these activities to assess a range of adaptive control approaches for distribution networks containing distributed generation. This includes comparisions of the decentralised (local sensing and control) and more centralised (communications-oriented) approaches in terms of improving network operation and security and accommodation of larger volumes of generation.
Application of DG and Demand Response for Management of Transmission Network Operation
Barry Hayes (PhD Study - EPSRC Supergen FlexNet)
Supervisors: Dr Sasa Djokic, Dr Gareth Harrison
Increased penetration of renewable-based distributed generation (DG) and system-wide implementation of demand side management (DSM) are regarded as two important features of future electricity networks. The impact of DG and DSM at the distribution level tends to be direct and easily observed. However, the effects on transmission system performance are difficult to quantify and cannot be characterized by a simple metric. Accordingly, a full assessment of the complex system-load-DG interactions at transmission level (132 kV and above) is possible only if accurate models of DG (including micro-generation) and DSM technologies are incorporated in the representations of aggregate system loads connected to the network. The overall aim of this research is to gain a better understanding of the interactions between various new technologies and their control schemes, and the opportunities provided through active management of distribution networks to relieve congestion in the transmission network and improve the overall performance of the system.
Asset Management and Planning
Our work in this area has been funded primarily through the EPSRC Supergen Asset Management and Performance of Energy Systems (AMPerES) consortium, a £2.8 million collaboration between industrial partners and the Universities of Manchester, Southampton, Edinburgh, Strathclyde, Liverpool and Queens Belfast. The consortium’s aim is to identify the means of maintaining and enhancing the reliability of energy supply at minimum cost despite ageing plant, changing environmental requirements and a reduced skills base. IES is leading the work package on enhanced network performance and planning which will draw together the activities of the consortium.
Optimal Asset Replacement and Network Expansion Methodologies
Dr Gareth Harrison, Dr Chris Dent (Durham), Professor Janusz Bialek (Durham)
When planning network upgrades and replacement strategies, many factors such as the reliability of supply to customers and the ability of the network to support new generation must be taken into account. The latter is becoming increasingly important given the increase in renewable generation within local distribution networks, as opposed to the national transmission network where conventional power stations are connected. This project is developing methods for quantifying generation capacity and system reliability in order to support planning decisions. It provides a critical link to, and integrates the activities of, the consortium.
Optimising Network Security in an Online Mode
Dr Song Zitong, Dr Gareth Harrison, Professor Janusz Bialek (Durham)
The goal of this work is a cost-benefit analysis method for optimal use of network equipment. The cost of component aging from running it harder is balanced against the benefits of increased flexibility which this also brings. It will combine equipment ageing models with on-line monitored data showing loading, network and equipment conditions, and will use equipment ageing research from elsewhere in the AMPerES consortium.
Strategies to Maximise the Absorption of New Generation
Dr Nando Ochoa, Dr Gareth Harrison
While Distributed Generation (DG) still accounts for a small fraction of the energy mix in UK, Distribution Network Operators need to be prepared for future scenarios. This project investigates the strategies that DNOs might use to maximise the connection of new generation capacity, both intermittent and non-intermittent. For this purpose, a more active approach for managing the network is adopted and analysed through the use of mathematical optimisation techniques. Ultimately, in line with the regulator’s policies, the project will identify the locational benefits of DG in order to provide guidelines on the creation of connection incentives. This role is part of a work package led by Queens Belfast on 'New Protection, Control and Management Techniques in Evolving Networks' and will build on Edinburgh’s key research in this area.
Security Analysis of Interdependence between Gas and Electricity Networks
James Whiteford (PhD Study - EPSRC Supergen AMPerES)
Supervisors: Dr Gareth Harrison, Professor Robin Wallace
As the dependence on natural gas for electricity generation in the UK grows, it is becoming increasingly difficult to decouple the security of the gas supply from the security of the electricity supply. As a result, the planning and operation of the transmission network infrastructures can no longer be treated separately and the challenge now faced by industry participants is the necessary harmonisation of the separate networks. This activity will provide an in-depth combined security analysis of the gas and electricity transmission networks in the UK to enhance the limited work that has been done in this area.
Modelling investment in electricity generation capacity as a dynamic control problem
Dan Eager (PhD Study - UK Energy Research Centre Interdisciplinary Studentship)
Supervisors: Dr Gareth Harrison, Professor Janusz Bialek (Durham), Dr Tim Johnson (Heriot-Watt University)
The ability of the UK energy market to trigger investment in the generation capacity required to maintain an acceptable level of security of supply risk has been - and will continue to be - a topic of much debate. Moreover, with a significant volume of wind power expected to come online, does a system based entirely on market prices - with no capacity mechanism - have the ability to induce investment in the type of plant necessary to compliment a variable wind generation profile?
Modelling the dynamics of investment in generation capacity can inform this debate. More precisely, if investment is viewed as a negative feedback control mechanism with energy prices acting as the feedback signal then the system can be viewed as a problem in optimal control. This novel approach of applying engineering tools to economic problem enables analysis of system stability characteristics and, if necessary, an appropriate controller can be designed to minimise the effects of investment uncertainties and ensure the desired level of security of supply risk.
Load Modelling and Demand Side Management
Advanced Load Modelling and Load Aggregation in Power System Studies
Adam Collin
Supervisors: Dr Sasa Djokic, Dr Gareth Harrison
An important requirement for the correct analysis and modelling of both distribution and transmission networks is accurate representation of steady state and dynamic characteristics of the supplied loads. Most of the load models used today are developed several decades ago, and are not adequately updated after the subsequent changes in load structure and load characteristics – last systematic update of load models was performed in the mid 1990s. Majority of power system studies still use typical representation of static loads by the constant power/impedance/current load types, while dynamic loads are represented with the induction motor model. During the work on this Ph. D. research, existing load models will be improved, and detailed models of new load categories will be fully developed (e.g., next generation of high-efficiency electronic loads, plug-in chargers for electric vehicles, LED and high-intensity discharge lighting sources, etc.). All developed models of considered loads will be capable of accurately describing both steady state and dynamic behaviour and responses, with a “generic load model” proposed for each load category. Afterwards, developed generic models of main load categories will be used for accurate representation of the aggregated demand of different load sectors connected at bulk load supply points.
Renewable-based Distributed Generation in Urban Areas
Jorge Luis Acosta Alvarez
Supervisors: Dr Sasa Djokic, Dr Markus Mueller
Besides the well-known general barriers for the application of Distributed Generation (DG) technologies (e.g. interconnection, operation, control and protection issues, as well as poor economics and relatively high costs), there are some additional constraints and limitations for DG applications in urban areas, especially if the DG is renewable-based. These include: high fault levels, space limitations that influence the use of smaller generating units with a lower installed powers, limited choice for selecting an appropriate site/location, and substantially lower energy levels of available primary energy resources. Urban areas, on the other hand, offer probably the biggest potential for demand side management (DSM), because of the high concentration of “demand-manageable loads” in residential, commercial and small business sectors. Both the DG & DSM share several beneficial effects (or potentials) for the system support, what clearly suggests that these two types of distributed resources may naturally complement each other, particularly if their control and operation is carefully correlated and analysed as a part of an integrated, all-inclusive assessment of DG & DSM applications in urban areas. This PhD research will investigate in detail how DG & DSM could be planned, implemented and operated together, in order to maximise all the benefits they may have on the overall system performance. Advantages and disadvantages of various renewable-based DG applications in urban areas will be analysed and modelled, including: wind technologies (no prevailing wind directions, low wind speeds, use of horizontal/vertical axis turbines), solar and PV technologies (presence of obstructions and low level of direct solar irradiance), biomass technologies (transport, storage and burning of biomass fuel), CHP & CCHP technologies (urban environments with/without district heating systems), geothermal technologies (localised resources and land-use concerns), as well as other currently used electricity and thermal generation technologies.
Power Quality and Reliability Assessment
Integrated Assessment of Quality of Supply in Future Electricity Networks
Ignacio Hernando-Gil
Supervisors: Dr Dr Sasa Djokic, Professor Robin Wallace
This project aims to establish a generalised procedure for the successful integration of reliability, power quality, security and other relevant aspects of quality of supply analysis in an all-inclusive methodology for the assessment of system and end-user performance in future electricity networks. The proposed methodology requires formulation of improved modelling and simulation tools, necessary for the correct analysis of future flexible and actively controlled power supply systems. The expected outcome of the proposed research is a set of new indices and performance indicators for a more accurate cost-benefit analysis and economic assessment, benchmarking and validation of the overall system and end-user quality of supply performance.
To answer these challenges, the PhD research within the project will concentrate on the development of improved component models and their use in high-performance parallel computing enabled simulation environment.
