Ignacio Hernando-Gil

Performance Assessment of Micro and Small-Scale Wind Turbines in Urban Areas

This paper addresses some general issues related to the difficulties and uncertainties during the assessment and characterization of micro and small-scale wind-based generation in urban areas. This paper proposes four generic wind turbine models, which could be used for the analysis and selection of optimal wind turbines in target applications, as they accurately represent the range of wind turbines currently available on the market. The analysis in this paper compares results for the expected annual energy outputs and cost-benefit analysis obtained using steady state and dynamic wind turbine models of actual and generic micro/small wind turbines, applying both low-resolution and high-resolution measurements of available wind energy resources. The presented results demonstrate the significance of the accurate assessment of wind resources in urban areas, as well as the importance of the correct modeling of wind turbine characteristics. It is shown that substantial errors, typically overestimating wind turbine performance, are obtained if standard assumptions and current recommendations are used for the analysis of wind turbine performance.

Optimal Power Flow for Maximizing Network Benefits From Demand-Side Management

This paper applies optimal power flow (OPF) to evaluate and maximize network benefits of demand-side management (DSM). The benefits are quantified in terms of the ability of demand-responsive loads to relieve upstream network constraints and provide ancillary services, such as operating reserve. The study incorporates detailed information on the load structure and composition, and allows the potential network benefits, which could be obtained through management of different load types, to be quantified and compared. It is demonstrated that the actual network location of demand-manageable load has an important influence on the effectiveness of the applied DSM scheme, since the characteristics of the loads and their interconnecting networks vary from one location to another. Consequently, some network locations are more favorable for implementation of DSM, and OPF can be applied to determine the optimal allocation of demand-side resources. The effectiveness of the presented approach is assessed using a time-sequential OPF applied to typical radial and meshed U.K. distribution networks. The results of the analysis suggest that network operators could not just participate in, but also encourage and add value to the implementation of specific DSM schemes at the optimum network locations in order to maximize the total benefit from DSM.

An 11 kV steady state residential aggregate load model. Part 1: Aggregation methodology

This paper, which is part one of a two-part series, presents a general methodology for the development of improved aggregate load models for steady state power system analysis. Using the UK residential load sector as an example, the paper shows how component-based low voltage (LV) aggregate load models can be obtained using measurements, statistical and other available data and information on load structure and active/reactive power demands. The presented aggregate LV load models are connected to typical LV and medium voltage (MV) network configurations, in order to obtain correct aggregate load models at higher voltage levels. Part two paper discusses how the presented aggregate load models can be modified to include the analysis the effects of demand side management and microgeneration technologies have on the overall performance of LV/MV networks.

Reliability performance of smart grids with demand-side management and distributed generation/storage technologies

The future “smart grids” will feature significantly higher numbers of various distributed generation and storage (DG&S) systems, as well as a wide-scale implementation of different demand-side management (DSM) functionalities. In existing literature, related analysis mostly concentrates on the operation, control and planning aspects of “smart grids”, while their impact on, and potential for improving system reliability performance is less researched. The work presented in this paper offers a new methodology for assessing reliability performance of power systems with fully employed DSM and DG&S functionalities, allowing to quantify in the most realistic manner standard set of indices reported annually to the Regulators. The methodology extends conventional reliability assessment procedures to include equivalent network models, actual load profiles and empirical fault probability distributions in the analysis, allowing to make a clear distinction between the short and long supply interruptions. Different DSM and DG&S scenarios are considered, in order to validate the proposed methodology and demonstrate its accuracy and applicability.

Reliability performance assessment in smart grids with demand-side management

The paper discusses possible impact of demand-side management (DSM) functionalities on the improvement of reliability performance and formulation of novel reliability assessment procedures of future electricity networks (so called “smart grids”). Firstly, traditionally used continuity of supply metrics and indices are assessed for a given reliability test system without considering any DSM scheme. Differences in the results for reliability indices for test system modelled with bulk loads and system modelled with detailed network configurations supplying connected loads are quantified, emphasising the errors that occur when parts of the system are neglected during the estimations of reliability performance. Afterwards, the effect of DSM on the reliability performance of the same test network are analysed, in order to assess potential benefits of DSM to the network operators, particularly with respect to their annual performance reports. Finally, possible changes in used reliability metrics are discussed, as smart grids will allow to substitute standard lumped representation of system loads at higher voltage levels with a more accurate and detailed information on load demands and load structures, including estimated contribution of demand-manageable portion of system load to the total demand.

An 11 kV steady state residential aggregate load model. Part 2: Microgeneration and demand-side management

This paper is part two of a two-part series on the development of improved aggregate load models for steady state power system analysis. Part one paper presented a general methodology for building component-based low voltage (LV) aggregate load models from statistical information on load structure and measurements of active/reactive power demands. The developed LV aggregate load models are then connected to typical LV and medium voltage (MV) network configurations, in order to obtain correct aggregate load models at higher voltage levels. This paper discusses how the presented LV and MV aggregate load models can be modified in order to include microgeneration technologies and demand-side management (DSM) functionalities in the analysis. Using the UK residential load sector as an example, it is shown that the assessment of microgeneration should be correlated both spatially and temporally with the aggregated load. The effects of DSM generally depend on the applied scenario, but may have a more pronounced effect on the aggregate demands.

Realising the potential of smart grids in LV networks. Part 2: Microgeneration

This paper, which is the second part of a two-part series, considers the influence of microgeneration technologies on the overall network performance and quality of supply of low-voltage residential customers in future “smart grids”. The paper uses the network models and demand-side management (DSM) scenarios developed in the Part 1 paper to further assess changes in active/reactive power flows, system losses, voltage profiles and harmonic emissions due to the combined effects of implementing microgeneration, energy storage and DSM.

Distribution network equivalents for reliability analysis. Part 1: Aggregation methodology

This paper, which is part one of a two-part series, presents a general methodology for reducing system complexity by calculating the electrical and reliability equivalent models of low and medium voltage distribution networks. These equivalent models help to reduce calculation times while preserving the accuracy assessment of power system reliability performance. The analysis is applied to typical UK distribution systems, which supply four generic load sectors with different networks and demand compositions (residential, commercial and industrial). This approach allows for a direct correlation between reliability performance and network characteristics, while assessing the most representative aggregate values of failure rates and repair times of power components at each load sector. These are used in the Part 2 paper for assessing the potential benefits of energy storage and demand-side resources on the reliability performance of different generic distribution networks.

Realising the potential of smart grids in LV networks. Part 1: Demand-side management

This paper, which is part one of a two-part series, analyses the influence of demand-side management (DSM) on the overall performance of distribution networks, particularly with respect to the quality of supply of low-voltage residential customers. The paper uses detailed network configurations and load models to assess changes in active/reactive power flows, system losses, voltage profiles and propagation of harmonics due to changes in the load mix as a result of DSM actions. The Part 2 paper will consider the effect of microgeneration technologies on further improvement/ deterioration of network performance.

Distribution network equivalents for reliability analysis. Part 2: Storage and demand-side resources

This paper, which is the second part of a two-part series, considers the influence of distributed energy resource functionalities on reliability performance of active networks. The reliability and network equivalent models defined in the Part 1 paper are used to assess the potential improvements that different demand-side management and energy storage schemes will have on the frequency and duration of customer interruptions. Particular attention is given to energy-related reliability indices which measure the energy and power not supplied to residential and commercial customers. A new theoretical interruption model is also introduced for a more accurate correlation between the different low-voltage and medium-voltage demand profiles and the time when both long and short interruptions are more likely to occur.