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The capacity of renewable distributed generation (DG) connected in distribution networks is increasing. Use of power electronic interfaces means DG can inject harmonic currents through the point of common coupling into upstream networks. The limits stipulated in harmonic emissions standards may create challenges for accommodating DG. To explore the impact of harmonic regulations on the ability of distribution networks to host DG, this work incorporates harmonic voltage constraints into a network hosting capacity assessment. A novel hosting capacity assessment approach is presented, incorporating percentile-based harmonic compliance levels as chance constraints over multiple periods into AC optimal power flow. The case study shows that network hosting capacity for DG could be evidently lower under rigorous compliance with harmonic distortion limits, but that relaxation of the risk constraints has significant value. Furthermore, the complex inter-connectivity between DG sites means that voltage, thermal and harmonic constraints all influence the locational feasibility for DG capacity.

It is imperative to increase the connectable capacity (i.e., hosting capacity) of distributed generation in order to decarbonise electricity distribution networks. Hybrid generation that exploits complementarity in resource characteristics among different renewable types potentially provides value for minimising technical constraints and increasing the effective use of the network. Tidal, wave and wind energy are prominent offshore renewable energy sources. It is of importance to explore their potential complementarity for increasing network integration. In this work, the novel introduction of these distinct offshore renewable resources into hosting capacity evaluation enables the quantification of the benefits of various resource combinations. A scenario reduction technique is adapted to effectively consider variation of these renewables in an AC optimal power flow-based nonlinear optimisation model. Moreover, the beneficial impact of active network management (ANM) on enhancing the renewable complementarity is also investigated. The combination of complementary hybrid generation and ANM, specifically where the maxima of the generation profiles rarely co-occur with each other and with the demand minimum, is found to make the best use of the network components.

International audience; This paper evaluates deterministic and probabilistic approaches for assessing hosting capacity (HC) of distribution networks for wind-based distributed generation (DG). The presented methodology considers variations of demands and DG power outputs, as well as dynamic thermal ratings (DTR) of network components. Deterministic approaches are based on a limited number of scenarios with minimum and maximum demands and DTR limits, while probabilistic approaches use simultaneous hourly values of all input parameters. The presented methodology has three stages. First, locational HC (LHC) of individual buses is calculated assuming connection of a single DG unit in the considered network. Afterwards, the LHC results are used to calculate network HC (NHC), assuming that DG units are connected at all network buses. Finally, busto-bus LHC-sensitivity factors are used to determine LHC and NHC for any number of DG units connected at arbitrary network buses.

Wave energy has the potential to play an important role in the UK's electricity mix in the coming years and it is important to understand the interactions of wave energy converters with the environment before considering them viable alternatives for other technologies. The aim of this study was to identify the environmental impacts of the deployment of the Oyster wave energy converter to the EMEC test site at Orkney, UK over its lifetime across three general categories: resource use, human health and ecological consequences. A full life cycle assessment was performed on two different models of the Oyster wave energy converter: Oyster 1 and Oyster 800. It was found that the latter is a fitting upgrade for its predecessor as it has lower environmental impacts in all categories; however, the high infrastructural needs of the Oyster technology makes its environmental performance worse than most other wave energy converters. Key sustainability indicators for energy converters include carbon footprint and energy payback period, and these were found to be 79 and 57 gCO2 eq/kWh and 45 and 42 months for the Oyster 1 and Oyster 800, respectively. Although these are significantly higher than most estimates for other types of renewable energy converter, the carbon impacts are still significantly lower than for conventional fossil-fuelled power generation.

There is great interest in data-driven modelling for the forecasting of building energy consumption while using machine learning (ML) modelling. However, little research considers classification-based ML models. This paper compares the regression and classification ML models for daily electricity and thermal load modelling in a large, mixed-use, university building. The independent feature variables of the model include outdoor temperature, historical energy consumption data sets, and several types of ‘agent schedules’ that provide proxy information that is based on broad classes of activity undertaken by the building’s inhabitants. The case study compares four different ML models testing three different feature sets with a genetic algorithm (GA) used to optimize the feature sets for those ML models without an embedded feature selection process. The results show that the regression models perform significantly better than classification models for the prediction of electricity demand and slightly better for the prediction of heat demand. The GA feature selection improves the performance of all models and demonstrates that historical heat demand, temperature, and the ‘agent schedules’, which derive from large occupancy fluctuations in the building, are the main factors influencing the heat demand prediction. For electricity demand prediction, feature selection picks almost all ‘agent schedule’ features that are available and the historical electricity demand. Historical heat demand is not picked as a feature for electricity demand prediction by the GA feature selection and vice versa. However, the exclusion of historical heat/electricity demand from the selected features significantly reduces the performance of the demand prediction.

Purpose To date, very few studies have attempted to quantify the environmental impacts of a wave energy converter, and almost all of these focus solely on the potential climate change impacts and embodied energy. This paper presents a full life cycle assessment (LCA) of the first-generation Pelamis wave energy converter, aiming to contribute to the body of published studies and examine any potential trade-offs or co-benefits across a broad range of environmental impacts. Methods The process-based attributional LCA was carried out on the full cradle-to-grave life cycle of the Pelamis P1 wave energy converter, including the device, its moorings and sub-sea connecting cable up to the point of connection with the grid. The case study was for a typical wave farm located off the north-west coast of Scotland. Foreground data was mostly sourced from the manufacturer. Background inventory data was mostly sourced from the ecoinvent database (v3.3), and the ReCiPe and CED impact assessment methods were applied. Results and discussion The Pelamis was found to have significantly lower environmental impacts than conventional fossil generation in 6 impact categories, but performed worse than most other types of generation in 8 of the remaining 13 categories studied. The greatest impacts were from steel manufacture and sea vessel operations. The device performs quite well in the two most frequently assessed impacts for renewable energy converters: climate change and cumulative energy demand. The carbon payback period is estimated to be around 24 months (depending on the emissions intensity of the displaced generation mix), and the energy return on investment is 7.5. The contrast between this and the poor performance in other impact categories demonstrates the limitations of focussing only on carbon and energy. Conclusions The Pelamis was found to generally have relatively high environmental impacts across many impact categories when compared to other types of power generation; however, these are mostly attributable to the current reliance on fossil fuels in the global economy and the early development stage of the technology. Opportunities to reduce this also lie in reducing requirements for steel in the device structure, and decreasing the requirements for sea vessel operations during installation, maintenance and decommissioning.

Although the integration of meshed multi-terminal direct current (MTDC) grids with the existing AC grid has some added economic advantages, significant challenges are encountered in such system. One of the major challenges is ensuring secure and optimal operation of the combined AC/MTDC grid considering the stability requirements of AC and DC grids at different operating conditions. This paper presents the implementation of hierarchical control for the combined AC/MTDC grid. The hierarchical control is based on the well-established three-layered control of the AC power system, comprising primary,secondary, and tertiary controls. A set of appropriate control methods are proposed for the primary, secondary, and tertiary control layers to accomplish the identified requirements for secure and optimal operation of the combined AC/MTDC grid.

Exploiting the diversity between different renewable resources is regarded as a significant tool to managing their grid integration. Hybrid combinations of resources provide the potential to smooth output and so overcome limits on the export of power, but their network wide impact is not well understood. This paper examines whether combinations of renewable distributed generation can make more effective use of distribution network capacity. A multi-period, multi-resource optimal power flow approach is used to optimally configure wind and solar photovoltaic capacity to maximise energy production whilst complying with network physical limits. The effectiveness of hybrid distributed generation and the optimization method was examined through comparison with cases using single types of renewable distributed generation. This study demonstrates that by capturing the complementarity between renewables through hybrid design, the network can host more renewable generation capacity and increase total energy export. In addition, smart grid techniques, such as active network management, further boosts the value of resource diversity by allowing connection of more generation capacity of all considered renewables through isolating the infrequent co-occurrence of high outputs during periods of low electricity demand.

This work assesses the changes in power capacity expansion decisions regarding power generation and transmission that occur when the effects of Climate Change on wind speed are captured in the decision model. Considering an 85-year period (2016–2101), we use a Mixed-Integer Linear Program (MILP) model to analyze the optimal power capacity expansion in diverse types of power generation technologies, throughout the years and geographical locations. The optimization model minimizes the total (investment and operational) costs of the power system subject to several technical and economic constraints. We implement our model using the main Chilean power system. We compare two scenarios: one assuming that Climate Change affects wind speeds and hence wind farm capacity factors and the other assuming it does not. Our results reveal that, when taking into account the impact of Climate Change on wind speed, the optimal power generation and transmission expansion plan is different than when ignoring this effect. The variation of wind speed affects not only wind power capacity installed, but also other-technology power capacity installed. In particular, power capacity installed in wind and solar generation plants is higher (measured in MW installed) than the power capacity installed when we ignore the effects of Climate Change; and power capacity installed in diesel and natural gas technologies are lower. We perform sensitivity analyses, changing power capacity expansion limits and the discount rate, to check for the robustness of our results.

Static security constraint management, formulated as security constrained optimal power flow (SCOPF), is one of the critical tasks performed during planning and operation. These constraints at any operating point can be divided into noncritical and critical constraints, where former can be managed with preventive controls, while the latter cannot. The violation of at least one critical constraint indicates that network is overstressed and needs a prompt activation of remedial actions to preserve system integrity. Accordingly, critical constraint violations (CCVs) must be identified by solving related SCOPF problem, as information on their types and locations can help to devise and activate optimal remedial actions. However, when dealing with overstressed systems, conventional SCOPF methods may not be able to identify CCVs due to problem infeasibility and there is no commonly accepted method to find related CCVs. Extending previously developed metaheuristic approach, this paper first identifies the CCVs and then proposes a novel methodology to devise the most effective remedial actions to mitigate overstressed system operating conditions. The practical relevance of the remedial actions is demonstrated using IEEE 30-bus, 39-bus, and 57-bus test networks.

This paper presents a method for real-time active network management (ANM) control to maximize network-wide energy yield in constrained networks. Coordinated scheduling of renewable distributed generation (DG) and distribution network control assets can limit DG curtailment and significantly increase energy yield and economic performance of DG. Here an optimal power flow (OPF) approach has been developed for real-time online scheduling of network control settings to better integrate high levels of temporally and spatially variable DG from renewable energy resources. Results show that real-time prescription of ANM control settings provides a feasible alternative to network reinforcement under the existing passive management philosophy.

The generation of renewable energy is strongly related to climate and could be vulnerable as the climate changes in the coming decades. The assessment of the potential risks is a new and evolving area of science. In light of the rapid pace of development and more prominent contribution of renewables to UK electricity generation, this work presents a summary of the current state of knowledge in the field and highlights some of the critical parameters and areas of uncertainty. An assessment of potential changes in the levelised cost of energy is presented, with the caveat that this is entirely based on existing data, which in some cases are highly uncertain. The areas of critical research for both understanding climate and engineering for adaptation are discussed.

Infrastructure is a means to an end: it is built, maintained and expanded in order to enable the functioning of society. Present infrastructure operation is characterised by: governance based on unmanaged growing demand, which is both inefficient and ultimately unsustainable; lack of integration of the end-users, in terms of the variety of their wants, needs and behaviours; separate and parallel delivery of different infrastructure streams prohibiting joint solutions. To achieve long-term sustainability, infrastructure needs to be designed and operated to provide essential service delivery at radically decreased levels of resource use. This new approach will need to: (1) incorporate the end-user, in terms of their wants and behaviours; (2) focus on the service provided; (3) use Information and Communication Technologies more effectively; (4) integrate the operation of different infrastructure systems; (5) be governed in a manner that recognises the complexity and interconnectedness of infrastructure systems; and (6) rethink current infrastructure valuation. Possible configurations incorporating these aspects with the explicit goal of contributing to long-term sustainability could be Multi-Utility Service Companies or “MUSCos”. This article presents new insights and ideas generated by considering the challenge of the transition towards a MUSCo infrastructure.

In this paper, a combinational AC/DC power flow approach is proposed for the solution of the combined AC/DC network. The unified power flow approach is extended to include DC voltage droop control. In the VSC based MTDC grids, DC droop control is regarded as more advantageous in terms of operational flexibility, as more than one VSC station controls the DC link voltage of the MTDC system. This model enables the study of the effects of DC droop control on the power flows of the combined AC/DC system for steady state studies after VSC station outages or transient conditions without needing to use its complete dynamic model. Further, the proposed approach can be extended to include multiple AC and DC grids for combined AC/DC power flow analysis. The algorithm is implemented by modifying the MATPOWER based MATACDC program and the results shows that the algorithm works efficiently.

This paper investigates the operating regimes of CCS power plants in future generation portfolios with large amounts of variable- output wind generation. An advanced electricity system dispatch model is developed and coupled with a Monte Carlo based energy storage optimization model to simulate the least-cost dispatch of an assumed thermal-energy storage generation portfolio with CCS. A historic high-resolution wind speed reanalysis dataset is employed and the proposed locations of future wind farms are used to produce plausible and internally consistent wind capacity deployment scenarios. The fundamental and structural changes that occur to CCS operating profiles and start-up/shut-down schedules are investigated for increasing levels of wind capacity, which creates seasonal and diurnal variations and potential flexibility implications. Non-linear interactions between flexible CCS power plants and other energy vectors are demonstrated for an illustrative case study example in Great Britain. This temporally explicit analysis of the short-term scheduling decisions of thermal plants with CCS highlights the asymmetric displacement of mid-merit thermal plants and the importance of using time-dependent start-up costs in wind-based unit commitment studies.

The total supply capability (TSC) is an important index for assessing the reliability of a distribution power system. In this paper, two models to evaluate the TSC are established. In the first, the TSC is acquired with the conditions that all load outages can be restored via network reconfiguration with transformers' N-1 contingencies, i.e., that all constraints related to branch thermal ratings and bus-voltage limits can be satisfied following restoration for each N-1 contingency. The second model, which is revision of the first, considers the daily load curves for different classes of customers, e.g., residential, commercial and industrial. Both models can be formulated as mixed integer problems with second-order cone programming (MISOCP), which can be solved using commercially available optimization software. Two test systems are used to demonstrate the applicability of the presented models. Numerical results show that the presented model is more accurate than the previously published models. This proposed analytical approach can be applied in a range of network planning studies, e.g., for selecting appropriate ratings of transformers, or for optimal locating of circuit breakers and distributed energy resources.

The paper presents a detailed study of the potential impact on the cost and greenhouse gas emissions (GHG) through low voltage (LV) residential demand-side management (DSM). The proposed optimisation algorithm is used to shift non-critical residential loads, with the wet load category used as a case study, in order to minimise the total daily cost and emissions of GHG due to generation. This study shows that it is possible to reshape the total power demand and reduce the cost and emissions of demand to some extent. It is also shown that further optimisation of the cost leads to an increase in GHG emissions because of their conflicting nature.

This paper presents a secondary control for MTDC systems to update the DC voltage and converter power references of the VSC stations operating under droop control, in order to eliminate the large power deviation from their desired reference power. The rated values of the VSC station used as reference does not take into account the power losses in the converter, DC line and the voltage drops in the DC transmission lines. This creates a constant difference between rated DC voltage reference and actual DC voltage value of the VSC station. This difference is multiplied by the droop gain of the VSC station, hence causing power deviations in the MTDC grid system. In this paper a secondary control is implemented for a four-terminal HVDC system modelled in EMTDC/PSCAD, to demonstrate the reduction in power deviation by the proposed secondary control.

Tidal energy has the potential to play a key role in meeting renewable energy targets set out by the United Kingdom (UK) government and devolved administrations. Attention has been drawn to this resource as a number of locations with high tidal current velocity have recently been leased by the Crown Estate for commercial development. Although tides are periodic and predictable, there are times when the current velocity is too low for any power generation. However, it has been proposed that a portfolio of diverse sites located around the UK will deliver a firm aggregate output due to the relative phasing of the tidal signal around the coast. This paper analyses whether firm tidal power is feasible with 'first generation' tidal current generators suitable for relatively shallow water, high velocity sites. This is achieved through development of realistic scenarios of tidal current energy industry development. These scenarios incorporate constraints relating to assessment of the economically harvestable resource, tidal technology potential and the practical limits to energy extraction dictated by environmental response and spatial availability of resource. The final scenario is capable of generating 17 TWh/year with an effective installed capacity of 7.8 GW, at an average capacity factor of 29.9% from 7 major locations. However, it is concluded that there is insufficient diversity between sites suitable for first generation tidal current energy schemes for a portfolio approach to deliver firm power generation. (C) 2012 Elsevier Ltd. All rights reserved.

It is difficult to estimate how much distributed generation (DG) capacity will be connected to distribution systems in the coming years; however, it is certain that increasing penetration levels require robust tools that help assess the capabilities and requirements of the networks in order to produce the best planning and control strategies. The work of this Task Force is focused on the numerous strategies and methods that have been developed in recent years to address DG integration and planning. This paper contains a critical review of the work in this field. Although there have been numerous publications in this area, widespread implementation of the methods has not taken place. The barriers to implementation of the advanced techniques are outlined, highlighting why network operators have been slow to pick up on the research to date. Furthermore, key challenges ahead which remain to be tackled are also described, many of which have come into clear focus with the current drive towards smarter distribution networks. Science Foundation Ireland Deposited by bulk import

Harmonic emissions from converter-interfaced distributed generation connection can potentially lead to voltage distortion levels that are above applicable standards. The risk increases as greater connection volumes are facilitated by Active Network Management schemes. By incorporating harmonic limits into assessment of the hosting capacity of active networks, this paper demonstrates that by incorporating harmonic levels at the planning stage can prevent inadvertent restrictions on the integration of renewables. Other aspects considered include: the impact of active network controls on harmonic propagation and hosting capacity and the role of active harmonic mitigation methods.

The capacity of distributed generation (DG) connected in distribution networks is increasing as part of the drive to connect renewable energy sources. Due to widespread application of power electronic inverter interfaces, DG can inject harmonic current through the point of common connection into the upstream network. Harmonic current emission may cause voltage distortion problems when harmonic resonance exists in the network. Harmonic distortion is one area of concern for electric utilities in determining whether DG could be connected, although there are differences in utility practices in applying limits. To explore the impact of harmonic regulations on the ability of distribution networks to host DG, this work incorporates harmonic voltage constraints into an established optimal power flow (OPF) planning method. The case study shows that harmonic distortion limits have substantial impacts on the allowable penetration of DG. Furthermore, the complex interconnectivity between DG locations means that voltage, thermal and harmonic constraints have a large influence on the location preference for DG capacity.

The Pelamis wave energy converter is emerging as one of the most promising devices to harness the available power in the waves. This study examines the environmental impacts of the device, presenting the results as a set of impact potentials, and demonstrating that it performs well in comparison to other renewable energy converters and fossil-fuelled generators. (6 pages)

Renewable distributed generation (DG), primarily wind power, will represent the lion’s share of the new generation capacity that will be connected to distribution systems. However, while both firm and variable generation present our traditionally passive distribution networks with well-established technical challenges, the requirements and practices related to the power factor operation of these generation plants might lead to undesirable effects at the transmission level with the reactive power support needed by high penetrations of DG capacity potentially impacting on weak areas of the transmission grid. In this work, this problem is formulated as the minimization of the reactive support for DG and is investigated using two different operational perspectives: adopting passive but enhanced power factor and substation settings, and implementing Smart Grid control schemes. These two approaches are modeled using a tailored multi-period AC optimal power flow technique that caters for the variability of demand and generation, and considers N-1 contingencies. The results demonstrate that the enhanced passive approach is able to achieve a performance almost as good as Smart Grid control without the need for any additional investment.

Background Surgical site infection (SSI) is a common complication following abdominal surgery. It is associated with considerable morbidity and mortality, and its management results in significant cost to health services within both primary and secondary care. Some surgeons believe that the use of a wound-edge protection device may reduce the incidence of SSI. Whilst there is some encouraging evidence showing that such devices may lead to a reduction in SSI, there are no controlled trials of sufficient size or quality to support their routine use. Methods/Design 750 patients will be recruited from around 20 surgical units within the United Kingdom. Patients undergoing laparotomy through any major abdominal incision for any indication, elective or emergency, are eligible. Patients under the age of 18, those undergoing a laparoscopic assisted procedure or who have undergone laparotomy within the previous 3 months, and those who are unable to give informed consent will be excluded. Patients will be randomised (1:1 ratio) to the use of a wound-edge protection device or no wound-edge protection device during surgery. Follow up will consist of blinded clinical wound reviews at 5-7 days and 30-33 days postoperatively with a self-completed questionnaire covering the intervening period. Quality of life questionnaires will be completed prior to surgery and at the subsequent wound review points and information on resource usage will also be captured. The primary outcome measure is SSI within 30 days of surgery. Secondary outcomes include the impact of the degree of wound contamination, patient comorbidity, and operative characteristics on the efficacy of a wound-edge protection device in reducing SSI and whether the use of a wound-edge protection device has an effect on health-related quality of life or length of hospital stay and is cost-effective. Discussion Rossini is the first multicentre observer-blinded randomised controlled trial of sufficient size and quality to establish whether the use of a wound-edge protection device in adult patients undergoing abdominal surgery leads to a lower rate of SSI. The results of this study will be used to inform current surgical practice and may potentially benefit patients undergoing surgery in the future. Trial registration number Current Controlled Trials ISRCTN: ISRCTN40402832

An approach is proposed to solve multistage distribution network expansion planning problems considering future uncertainties, guiding the planner from production of expansion plans, evaluation of the plans under various future uncertain scenarios, to the selection of the best strategy. A new balanced genetic algorithm (BGA) is introduced that improves the intensification of the solution search procedure by trading-off diversification ability. This facilitates searching for the optimal solution, but also the efficient production of suboptimal solutions for the planner to take into consideration. The features of the BGA allow a multistage planning problem to be solved more efficiently; the BGA can consider a set of expansion plans in an early planning stage in a single run and produce planning strategies required to solve network problems in a later stage along the planning horizon. The overall performance of each plan under different uncertain scenarios is evaluated using a modified data envelopment analysis to assist decisions on which solution to adopt. The approach is applied to a multistage greenfield distribution network expansion problem considering scenarios for the location of future loads. The results clearly show the advantages of the approach over more conventional methods. © 2010 IEEE.

The problem of minimizing losses in distribution networks has traditionally been investigated using a single, deterministic demand level. This has proved to be effective since most approaches are generally able to also result in minimum overall energy losses. However, the increasing penetration of (firm and variable) distributed generation (DG) raises concerns on the actual benefits of loss minimization studies that are limited to a single demand/generation scenario. Here, a multiperiod AC optimal power flow (OPF) is used to determine the optimal accommodation of (renewable) DG in a way that minimizes the system energy losses. In addition, control schemes expected to be part of the future Smart Grid, such as coordinated voltage control and dispatchable DG power factor, are embedded in the OPF formulation to explore the extra loss reduction benefits that can be harnessed with such technologies. The trade-off between energy losses and more generation capacity is also investigated. The methodology is applied to a generic U.K. distribution network and results demonstrate the significant impact that considering time-varying characteristics has on the energy loss minimization problem and highlight the gains that the flexibility provided by innovative control strategies can have on both loss minimization and generation capacity. © 2010 IEEE.

The extent to which large volumes of offshore wind can contribute to a secure and reliable electricity supply is a subject of much debate. Key to providing credible answers requires a detailed understanding of the wind resource and its variability in time and space. Here, a mesoscale atmospheric model was employed to create a ten year hindcast of British onshore and offshore wind speeds. This was used to simulate the output of a British offshore wind fleet and combined with demand data to assess reliability during periods of high demand. Further, capacity value calculations using Effective Load Carrying Capability for the combined onshore and offshore GB wind fleet provides an estimate of the long-term reliability of production. (6 pages)

Voltage rise is a significant limitation when connecting large volumes of distributed generation (DG), particularly in rural distribution networks. One means of allowing further capacity penetration is to control voltage regulation devices such as on-load tap changers in a coordinated manner considering the variability of demand and generation. This approach, however, requires the deployment of communication systems, making it a potentially expensive option. To date, most DG technologies feature capabilities such as provision of reactive power or power factor control. Nonetheless, the “fit and forget” approach for the connection of DG units to distribution networks neglects a more active, decentralised management where those and other capabilities could be used without the need of further infrastructure. This work proposes a decentralised control scheme where wind power-based DG units have a dual operation mode (power factor control and voltage control) in order to maintain the voltage at the connection bus within limits. Generators are also able to curtail their power output as a last resort to regulate the local voltage. Time-series analyses demonstrate the effectiveness of the decentralised methodology in adequately integrating DG capacity.

Analysis of lower carbon power systems has tended to focus on the operational carbon dioxide (CO2) emissions from power stations. However, to achieve the large cuts required it is necessary to understand the whole-life contribution of all sectors of the electricity industry. Here, a preliminary assessment of the life cycle carbon emissions of the transmission network in Great Britain is presented. Using a 40-year period and assuming a static generation mix it shows that the carbon equivalent emissions (or global warming potential) of the transmission network are around 11 gCO(2-eq)/kWh of electricity transmitted and that almost 19 times more energy is transmitted by the network than is used in its construction and operation. Operational emissions account for 96% of this with transmission losses alone totalling 85% and sulphur hexafluoride (SF6) emissions featuring significantly. However, the CO2 embodied within the raw materials of the network infrastructure itself represents a modest 3%. Transmission investment decisions informed by whole-life cycle carbon assessments of network design could balance higher financial and carbon 'capital' costs of larger conductors with lower transmission losses and CO2 emissions over the network lifetime. This will, however, necessitate new regulatory approaches to properly incentivise transmission companies. (C) 2010 Elsevier Ltd. All rights reserved.

This paper presents three case studies of risk-based standards from Great Britain: the pre-liberalisation generation planning standard, the present method for setting operational reserve requirements, and the transmission network planning standard. These illustrate a number of key issues in developing planning and operational standards for wind, including: the benefits of risk-based standards in adapting to new circumstances; the importance of considering model assumptions carefully when interpreting risk calculations; the difficulty in calculating the cost of risk; and the need to account for uncertainty in system background. The transmission network planning standard is studied in particular detail, especially how the present combination of deterministic and probabilistic sections might evolve for use in a future power system with a very high renewable penetration.

Distribution networks are increasingly required to host medium to large volumes of distributed (renewable) generation capacity. To facilitate high penetration levels of these new network participants it is crucial to adopt new control strategies in which the distribution systems are operated actively. The wide deployment of schemes such as coordinated voltage control (CVC) or non-firm connections will depend on communication and control infrastructure that is likely to be part of future Smart Grid investments. This infrastructure scenario might also make viable the use of advanced real-time measurement devices required to dynamically assess overhead line ratings. Given the inherent correlation of wind power output, wind speeds and temperature, this work is aimed at demonstrating the benefits that the adoption of dynamic ratings might bring to allow the connection of more wind power capacity. A multi-period AC Optimal Power Flow (OPF)-based technique is used to evaluate the maximum capacity of new generation considering control strategies such as dynamic ratings and CVC. The method caters for the variability of demand, wind resource and temperature. Results from a simple test feeder demonstrate the significant generation capacity gains compared to the passive operation of the network.

With funding from the UK’s Royal Academy of Engineering, the University of Edinburgh has developed a set of three truly interdisciplinary group design exercises aimed at improving penultimate-year undergraduate students’ ability to work across disciplines and improve their preparation for transfer into industry. Three exercises on hydropower system design, potable water supply and a micro-system accelerometer are each designed and led by a Visiting Industrial Professor. The group design exercises are both challenging and popular with students and have achieved several very successful outcomes: experience of real system design; enhanced appreciation of other engineering disciplines; experience of team working where participants have different skills and expertise; demonstration of the links between design and economic viability and introduction to non-technical areas essential to fulfilling the UK Standard for Professional Engineering Competence.

Gas-fired power stations currently generate over a third of the electricity demand of the United Kingdom (UK) and will play an increasing role in the future. At the same time the UK is becoming increasingly reliant on external supplies for gas security. The levels of physical and economic interaction between the gas and electricity systems offer a new set of risks for energy security. This paper traces the development of the UK gas industry, its growing links with the electricity sector and sets out some of the important developments in Europe and within the UK that influence UK energy security.

The potential for distributed generation (DG) to act as an alternative distribution planning option is now well-recognised by academia and industry, and could play a significant role in electricity distribution utility operation and design. However, the unbundling requirements of European Directive 2003/54/EC, coupled with traditional network planning approaches adopted by European Distribution Network Operators (DNOs), appear to be hindering development of DG and its deployment for distribution network ancillary services. The incentives - or otherwise - that arise from alternative models of DG ownership by bundled and unbundled distribution utilities are examined here. The preference for the siting and sizing of DG installations by DNOs is simulated using a multi-year multi-period optimal power flow. Broadly based on the recent UK regulatory framework, the DG ownership issue and its potential to influence DG penetration are explored. © 2009 The Institution of Engineering and Technology.

Wind power is currently the fastest growing renewable technology and will play a significant role in constraining the extent of climate change. However, the very fact that its ‘fuel source’ is driven by the climate may leave it exposed as climate changes over the coming decades. In this preliminary assessment, the potential for changes in climate to affect the significant onshore wind resource in the United Kingdom (UK) is explored using the regional climate change scenarios published by the UK Climate Impacts Programme in 2002. The scenarios indicate seasonal changes in potential wind production with winter production generally increasing while summer decreases.

In the last decade, distributed generation, with its various technologies, has increased its presence in the energy mix presenting distribution networks with challenges in terms of evaluating the technical impacts that require a wide range of network operational effects to be qualified and quantified. The inherent time-varying behavior of demand and distributed generation (particularly when renewable sources are used), need to be taken into account since considering critical scenarios of loading and generation may mask the impacts. One means of dealing with such complexity is through the use of indices that indicate the benefit or otherwise of connections at a given location and for a given horizon. This paper presents a multiobjective performance index for distribution networks with time-varying distributed generation which consider a number of technical issues. The approach has been applied to a medium voltage distribution network considering hourly demand and wind speeds. Results show that this proposal has a better response to the natural behavior of loads and generation than solely considering a single operation scenario. © 2008 IEEE.

While independently conducted polls suggest significant public support for wind energy, there are often objections to particular wind farm developments from the local population which can result in planning permission being declined and a restriction in the ability to meet renewable energy and greenhouse gas reduction targets. The aim of the study was to determine whether the pre-construction opinions held by communities local to a wind farm change after an extended period following commissioning. Residents of St. Newlyn East, Cornwall, England, were asked to recall their opinions of Carland Cross wind farm in 1991 and 2006. Statistically significant changes in opinion were observed for attitudes regarding the wind farm's visual attractiveness and the importance of the energy security it provides. This study continues by exploring potential reasons for this in the context of recent literature on public attitudes towards renewable energy. The findings of this study support the proposals in the 2007 UK White Paper, Planning for a Sustainable Future, for community engagement early in the project process and for the requirement of infrastructure to be debated at the national level.

Many methods have been applied to examine the capacity of existing distribution networks to accept distributed generation (DG). One aspect missing from existing approaches is the capability to efficiently site and size a predefined number of DGs. Here, a hybrid method employing genetic algorithms and optimal power flow aims to overcome this shortcoming. It could be applied by distribution network operators to search a network for the best sites and capacities available to strategically connect a defined number of DGs among a large number of potential combinations. Some applications of the proposed methodology in the UK under current Ofgem financial incentives for DNOs confirmed its effectiveness in siting and sizing an assigned number of DG units.

The world's first commercial‐scale grid‐connected tidal current energy installation will feature the Seagen marine current turbine developed by Marine Current Turbines Ltd. With potential for the manufacture of significant numbers of such devices there is a need to assess their environmental impact and, in particular, their life cycle energy and carbon dioxide (CO2) performance. This paper presents an analysis of the life cycle energy use and CO2 emissions associated with the first generation of Seagen turbines. The detailed assessment covers the embodied energy and CO2 in the materials and manufacturing of components, device installation, and operation along with those for decommissioning. With relatively conservative assumptions, and despite the early stage of development, the study shows that at 214 kJ/kWh and 15 g CO2/kWh, the respective energy and carbon intensities are comparable with large wind turbines and very low relative to the 400 to 1000 g CO2/kWh typical of fossil‐fuelled generation. The energy payback period is approximately 14 months and the CO2 payback is around 8 months. The embodied energy and carbon show limited sensitivity to assumptions with environmental performance remains excellent even under the most adverse scenarios considered. Materials use is identified as the primary contributors to embodied energy and carbon with shipping also significant. Improvements in the environmental impact of the Seagen can be achieved primarily by increased structural efficiency and the use of alternative installation methods to increase recovery of steel at decommissioning.

Regulators are aiming to incentivize developers and Distribution Network Operators to connect distributed generation (DG) to improve network environmental perform-ance and efficiency. A key question is whether these incentives will encourage both parties to connect DG. Here, multi-objective optimal power flow is used to simulate how the par-ties’ incentives affect their choice of DG capacity within the limits of the existing network. Using current UK incentives as a basis, this paper explores the costs, benefits and trade-offs associated with DG in terms of connection, losses and, in a simple fashion, network deferral.

With high levels of variable renewable generation in distribution or transmission systems, the application of demand and generation time series to power flow analysis can be advantageous. Demand data are often available from historic measurements, while renewable generation such as wind turbine output may be recorded or can be derived from resource measurements over the corresponding period of time. Power flow solutions with hourly time steps over a year or more can then be used to produce load duration curves for system components. This paper shows, by example, how utilities can use the method to determine overload conditions or to specify non-firm connection agreements for new generators.

With the rapid increase in distributed generation (DG), the issue of voltage regulation in the distribution network becomes more significant and centralized voltage control (or active network management) is one of the proposed methods.Alternative work on intelligent distributed voltage and reactive power control of DG has also demonstrated benefits in terms of the minimization of voltage variation and violations as well as the ability to connect larger generators to the distribution network. This paper uses optimal power flow to compare the two methods and shows that intelligent distributed voltage and reactive powercontrol of the DG gives similar results to those obtained by centralized management in terms of the potential for connecting increased capacities within existing networks.

Evaluating the technical impacts associated with connecting distributed generation to distribution networks is a complex activity requiring a wide range of network operational and security effects to be qualified and quantified. One means of dealing with such complexity is through the use of indices that indicate the benefit or otherwise of connections at a given location and which could be used to shape the nature of the contract between the utility and distributed generator. This paper presents a multiobjective performance index for distribution networks with distributed generation which considers a wide range of technical issues. Distributed generation is extensively located and sized within the IEEE-34 test feeder, wherein the multiobjective performance index is computed for each configuration. The results are presented and discussed. © 2006 IEEE.

Microgeneration is being promoted as a means of lowering carbon dioxide (CO2) emissions by replacing electricity from the grid with production from small domestic generators. One concern over this drive is that the use of smaller plant could lead to the loss of economies of scale. Partly, this relates to cost but also in terms of energy consumed and CO2 emitted over the life cycle of the microgenerator. Here, an analysis is presented of a life-cycle audit of the energy use and CO2 emissions for the ‘SWIFT’, a 1.5 kW rooftop-mounted, grid-connected wind turbine. The analysis shows that per kilowatt-hour of electricity generated by the turbine, the energy intensity and CO2 emissions are comparable with larger wind turbines and significantly lower than fossil-fuelled generation. With energy and carbon intensities sensitive to assumed levels of production, assessments were carried out for an annual production range of 1000–4000 kWh, representing capacity factors of 8–31 per cent. For the manufacturer's estimated production of 2000 to 3000 kWh and, giving credit for component recycling, the energy payback period was found to be between 17 and 25 months, whereas the CO2 payback was between 13 and 20 months. Across the full production range, the energy and carbon payback periods were 13–50 months and 10–39 months, respectively. A key outcome of the study is to inform the manufacturer of the opportunities for improving the energy and carbon intensities of the turbine. A simple example is presented showing the impact of replacing one of the larger aluminium components with alternative materials.

Electricity networks are called on to accommodate more and more generation capacity in order to supply the increasing demand. Social, planning and environmental reasons hinder the expansion of the existing infrastructure, whereas lack of investment prohibits its reinforcement. Therefore, the efficient utilisation of the existing network is not only suggested for economy, but also imposed by need. Consequently, the realisation of government targets for renewable energy will depend, in part, on the ability of developers and Distribution Network Operators (DNOs) to maximise generator capacities connected to the network whilst minimising negative impacts. One means of ensuring maximum capacity with minimal voltage impact is through the use of intelligent power factor and voltage control of generators and other network components. Previously published work demonstrated the benefits in terms of the minimisation of voltage variations and violations as well as the ability of larger generators to connect to the network. While the capacity benefit could be easily quantified for individual dispersed generators, it was more difficult to explore the benefit of widespread usage. To achieve this it was necessary to draw on earlier work that used Optimal Power Flow (OPF) techniques to evaluate the network capacity available for connecting dispersed generators. The capacity evaluation technique was extended such that it could incorporate the intelligent generator control algorithms and in doing so could find optimal levels of connections. The results of a case study indicate that intelligent power factor and voltage control of generators increases significantly the connecting capacity of existing networks.

Wave energy will have a key role in meeting renewable energy targets en route to a low carbon economy. However, in common with other renewables, it may be sensitive to changes in climate resulting from rising carbon emissions. Changes in wind patterns are widely anticipated, and this will ultimately alter wave regimes. Indeed, evidence indicates that wave heights have been changing over the last 40 years, although there is no proven link to global warming. Changes in the wave climate will affect wave energy conversion. Where the resource is restricted, there may be reductions in energy exports and, consequently, negative economic impacts. On the other hand, increased storm activity will increase installation survival risks. Here a study is presented that, for the first time, indicates the sensitivity of wave energy production and economics to changes in climate.

Climate change is expected to lead to changes in ambient temperature, wind speed, humidity, precipitation and cloud cover. As electricity demand is closely influenced by these climatic variables, there is likely to be an impact on demand patterns. The potential impact of future changes in climate on electricity demand can be seen on a daily and seasonal basis through the fluctuation of weather patterns. The magnitude of the impact will depend on the electricity use patterns in the absence of climate change, as well as long-term socio-economic trends. As developing countries improve their standard of living, their use of air conditioning and other weather-dependent consumption may increase their sensitivity to climate change. This paper reviews existing studies on climate impacts on electricity demand and outlines how this is being assessed for the rapidly growing Thailand electricity sector.

The hydropower industry is looking to take a role in tackling climate change. The technology has no operational carbon emissions, and is seen by many as key to achieving a low carbon future. Doing this in increasingly liberalised markets will be a challenge given the massive up-front costs of dam construction. However, recent initiatives to promote renewable generation twinned with future developments in carbon taxation and emissions trading, look set to improve the competitive position of hydropower. But climate change also brings some bad news for hydropower.