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[en] A Monte Carlo model of the combined GB gas and electricity network was developed to determine the reliability of the energy infrastructure. The model integrates the gas and electricity network into a single sequential Monte Carlo simulation. The model minimises the combined costs of the gas and electricity network, these include gas supplies, gas storage operation and electricity generation. The Monte Carlo model calculates reliability indices such as loss of load probability and expected energy unserved for the combined gas and electricity network. The intention of this tool is to facilitate reliability analysis of integrated energy systems. Applications of this tool are demonstrated through a case study that quantifies the impact on the reliability of the GB gas and electricity network given uncertainties such as wind variability, gas supply availability and outages to energy infrastructure assets. Analysis is performed over a typical midwinter week on a hypothesised GB gas and electricity network in 2020 that meets European renewable energy targets. The efficacy of doubling GB gas storage capacity on the reliability of the energy system is assessed. The results highlight the value of greater gas storage facilities in enhancing the reliability of the GB energy system given various energy uncertainties. -- Highlights: •A Monte Carlo model of the combined GB gas and electricity network was developed. •Reliability indices are calculated for the combined GB gas and electricity system. •The efficacy of doubling GB gas storage capacity on reliability of the energy system is assessed. •Integrated reliability indices could be used to assess the impact of investment in energy assets
[en] Highlights: • CAES and CAES with thermal storage systems were investigated. • The potential for using heat generated during the compression stage was analysed. • CAES-TS has the potential to be used both as energy storage and heat source. • CAES-TS could be a useful tool for balancing overall energy demand and supply. - Abstract: The potential for using heat generated during the compression stage of a Compressed Air Energy Storage system was investigated using exergy and exergoeconomic analysis. Two Compressed Air Energy Storage systems were analysed: Compressed Air Energy Storage (CAES) and Compressed Air Energy Storage combined with Thermal Storage (CAES-TS) connected to a district heating network. The maximum output of the CAES was 100 MWe and the output of the CAES-TS was 100 MWe and 105 MWth. The study shows that 308 GW h/year of electricity and 466 GW h/year of fuel are used to generate 375 GW h/year of electricity. During the compression of air 289 GW h/year of heat is generated, which is wasted in the CAES and used for district heating in the CAES-TS system. Energy efficiency of the CAES system was around 48% and the efficiency of CAES-TS was 86%. Exergoeconomic analysis shows that the exergy cost of electricity generated in the CAES was 13.89 ¢/kW h, and the exergy cost of electricity generated in the CAES-TS was 11.20 ¢/kW h. The exergy cost of heat was 22.24 ¢/kW h in the CAES-TS system. The study shows that CAES-TS has the potential to be used both as energy storage and heat source and could be a useful tool for balancing overall energy demand and supply
[en] Highlights: • Annual domestic demand by category and daily flexible load profiles are shown to 2030. • Valuable flexible demand requires loads to be identifiable, accessible, and useful. • The extent of flexible demand varies significantly on a diurnal and seasonal basis. • Barriers to accessing domestic demand include multiple low value loads and apathy. • Existing market structure a barrier to fully rewarding individual load flexibility. - Abstract: In order to meet greenhouse gas emissions targets the Great Britain (GB) future electricity supply will include a higher fraction of non-dispatchable generation, increasing opportunities for demand side management to maintain a supply/demand balance. This paper examines the extent of flexible domestic demand (FDD) in GB, its usefulness in system balancing and appropriate incentives to encourage consumers to participate. FDD, classified as electric space and water heating (ESWH), and cold and wet appliances, amounts to 59 TW h in 2012 (113 TW h total domestic demand) and is calculated to increase to 67 TW h in 2030. Summer and winter daily load profiles for flexible loads show significant seasonal and diurnal variations in the total flexible load and between load categories. Low levels of reflective consumer engagement with electricity consumption and a resistance to automation present barriers to effective access to FDD. A value of £1.97/household/year has been calculated for cold appliance loads used for frequency response in 2030, using 2013 market rates. The introduction of smart meters in GB by 2020 will allow access to FDD for system balancing. The low commercial value of individual domestic loads increases the attractiveness of non-financial incentives to fully exploit FDD. It was shown that appliance loads have different characteristics which can contribute to an efficient power system in different ways
[en] Highlights: • A sensitivity method was developed to visualize an SOP operating region in a graphical manner. • Time series of SOP set-points were provided considering various load and generation conditions. • A framework was developed to quantify the SOP operational benefit with different objectives. • This framework is able to facilitate the network operators to select SOP control schemes. - Abstract: A soft open point (SOP) is a power electronic device, usually using back-to-back voltage source converters (VSCs), installed at a previously normally open point of a distribution network. Due to its flexible and accurate control of power flows, an SOP is versatile, and increasingly being considered to mitigate voltage and thermal constraints in medium voltage (MV) networks with high penetrations of distributed generation (DG). A Jacobian matrix - based sensitivity method was used to define the operating region of an SOP when the grids/feeders at the two terminals of the SOP have various load and generation conditions, and the SOP operating region was visualized in a graphical manner. The exact operating set-points were determined by adopting a non-linear optimization considering separately different objectives. The methodology was demonstrated on an 11 kV network, considering three optimization objectives with different DG penetrations and different network observabilities. Results showed that the use of an SOP significantly increases the network’s DG hosting capacity. The objective for voltage profile improvement increased the headroom of the voltage limits by the largest margin, at the expense of increased energy losses. In contrast the objectives to achieve line utilization balancing and energy loss minimization showed the most improvement in circuit utilization and in limiting energy losses. The work helps electricity network operators to visualize an SOP’s operation status, and provides high level decision support, e.g. selecting control schemes and restraining SOP operational boundaries.
[en] Heating is arguably one of the most difficult sectors to decarbonise in the UK's energy system. Meeting the 80% greenhouse gas emission reduction target by 2050 is likely to require that heat related emissions of CO_2 from buildings are near zero by 2050, and there is a 70% reduction in emissions from industry (from 1990 levels). Though it is clear that the use of the natural gas network will reduce over time, recent modelling suggests a limited residual role for gas by 2050 to help meet peaks in heat demand. High levels of uncertainty about the way in which heat will be decarbonised present a number of challenges to policy makers. This paper will explore the risks and uncertainties associated with the transition to a low carbon heat system in the UK as outlined by the 4th carbon budget review. The potential impact of key uncertainties on the levelised costs of heat technologies and the development of energy networks are explored using a sensitivity analysis approach. Policy changes required to decarbonise the heat sector are also examined. - Highlights: • We identify the key uncertainties in decarbonising heat in the UK. • A review on the current status of key heat supply technologies is presented. • The significance of key uncertainties on heat technology costs are analysed. • The impact on the development of the energy network infrastructure is assessed. • The policy and incentives required to decarbonise the heat sector are examined.
[en] This study quantifies the effects of aggregating electric load over various combinations (Aggregation Groupings) of the 10 Federal Energy Regulatory Commission (FERC) regions in the contiguous U.S. Generator capacity capital cost savings, load energy shift operating cost savings, reserve requirement cost savings, and transmission costs due to aggregation were calculated for each Aggregation Grouping. Eight scenarios of Aggregation Groupings over the U.S. were formed to estimate overall system cost. Transmission costs outweighed cost savings due to aggregation for all scenarios and nearly all Aggregation Groupings. East–west transmission layouts had the highest overall cost, and interconnecting ERCOT to adjacent FERC Regions resulted in increased costs, both due to limited existing transmission capacity. This study found little economic benefit of aggregating electric load alone (e.g., without aggregating renewable generators simultaneously), except in the West and Northwest U.S. If aggregation of load alone is desired, small, regional consolidations yield the lowest overall cost. This study neither examines nor precludes benefits of interconnecting geographically-dispersed renewable generators with load. It also does not consider effects from sub-hourly load variability, fuel diversity and price uncertainty, energy price differences due to congestion, or uncertainty due to forecasting errors; thus, results are valid only for the assumptions made. - Highlights: ► Effects of aggregating load across various geographic areas of U.S. are quantified. ► Benefits exist for all metrics, but outweighed by additional transmission costs. ► Aggregating electric load alone is not economical, except for West and NW U.S. ► Limited existing transmission capacity yields highest cost for east–west layout. ► Lowest U.S.-wide overall cost when consolidate multiple, small areas.
[en] Highlights: • Availability and cost of gas are crucial factors in power system planning. • CGEN+ was developed to analyse expansion of combined gas and electricity systems. • Performance of various low carbon strategies were assessed. • Electrification of heat and transport requires large investment in power sector. • Despite declining demand for gas, peak gas demand will almost remain unchanged. - Abstract: The reliance of Great Britain power generation on the gas network makes it critical to consider the future availability and cost of gas in planning the expansion of the power system. A combined gas and electricity network planning model was used to investigate impacts of various low carbon strategies on regional expansion of the Great Britain gas network out to the 2050s. A number of long term energy supply and demand strategies covering a range of plausible investment policies for Great Britain gas and electricity systems were explored. Reliance of Great Britain on gas imports was projected to vary from 84%, in an energy system with significant electrification of heat and transport sectors and large capacity of nuclear generation, to 94% in a business as usual case. Extensive investment in Liquefied Natural Gas import facilities at Milford Haven and the Isle of Grain was shown to compensate for reduction of indigenous gas supplies. Exploitation of shale gas in north England was shown to reduce the gas dependency of Great Britain in the business as usual case to 74%. Electrification of the heat and transport sectors combined with exploitation of shale gas in Great Britain could reduce import dependency to below 10% by 2050
[en] Wind power is expected to be the major element of renewable electricity generation in Great Britain (GB) by 2020 with a capacity of around 30 GW. The potential impact of a large amount of wind generation on the GB gas network was investigated using a combined gas and electricity network model. The varying nature of gas and electric power flows, network support facilities such as gas storage and compressors, and the power ramping characteristics of various power plants were considered. Three case studies were modelled, one case uses the existing network and the other two make use of a hypothesised network in 2020 with two distinct levels of wind generation representing low and high wind periods. The simulation results show that a large penetration of wind generation will influence the electricity generation mix as the wind power varies. Gas-fired generation is used to compensate for wind variability. This will cause increased flows and compressor power consumption on the gas network. Linepack depletion during low wind periods was shown to limit the ability of the gas network to fully supply gas-fired generators.
[en] Highlights: • Two control modes were developed for a B2B VSCs based SOP. • The SOP operating principle was investigated under various network conditions. • The performance of the SOP using two control modes was analyzed. - Abstract: Soft Open Points (SOPs) are power electronic devices installed in place of normally-open points in electrical power distribution networks. They are able to provide active power flow control, reactive power compensation and voltage regulation under normal network operating conditions, as well as fast fault isolation and supply restoration under abnormal conditions. Two control modes were developed for the operation of an SOP, using back-to-back voltage-source converters (VSCs). A power flow control mode with current control provides independent control of real and reactive power. A supply restoration mode with a voltage controller enables power supply to isolated loads due to network faults. The operating principle of the back-to-back VSCs based SOP was investigated under both normal and abnormal network operating conditions. Studies on a two-feeder medium-voltage distribution network showed the performance of the SOP under different network-operating conditions: normal, during a fault and post-fault supply restoration. During the change of network operating conditions, a mode switch method based on the phase locked loop controller was used to achieve the transitions between the two control modes. Hard transitions by a direct mode switching were noticed unfavourable, but seamless transitions were obtained by deploying a soft cold load pickup and voltage synchronization process.
[en] Highlights: • An analysis framework was developed to quantify the operational benefits. • The framework considers both network reconfiguration and SOP control. • Benefits were analyzed through both quantitative and sensitivity analysis. - Abstract: Soft Open Points (SOPs) are power electronic devices installed in place of normally-open points in electrical power distribution networks. They are able to provide active power flow control, reactive power compensation and voltage regulation under normal network operating conditions, as well as fast fault isolation and supply restoration under abnormal conditions. A steady state analysis framework was developed to quantify the operational benefits of a distribution network with SOPs under normal network operating conditions. A generic power injection model was developed and used to determine the optimal SOP operation using an improved Powell’s Direct Set method. Physical limits and power losses of the SOP device (based on back to back voltage-source converters) were considered in the model. Distribution network reconfiguration algorithms, with and without SOPs, were developed and used to identify the benefits of using SOPs. Test results on a 33-bus distribution network compared the benefits of using SOPs, traditional network reconfiguration and the combination of both. The results showed that using only one SOP achieved a similar improvement in network operation compared to the case of using network reconfiguration with all branches equipped with remotely controlled switches. A combination of SOP control and network reconfiguration provided the optimal network operation.