The UK has highly ambitious targets for wind development, particularly offshore, where over 30GW of capacity is proposed for development. Integrating such a large amount of variable generation presents enormous challenges. Answering key questions depends on a detailed understanding of the wind resource and its temporal and spatial variability. However, sources of wind speed data, particularly offshore, are relatively sparse: satellite data has low temporal resolution; weather buoys and met stations have low spatial resolution; while the observations from ships and platforms are affected by the structures themselves. This work uses a state-of-the art mesoscale atmospheric model to produce a new high-resolution wind speed dataset over the British Isles and surrounding waters. This covers the whole region at a resolution of 3km for a period of eleven consecutive years, from 2000 to 2010 inclusive, and is thought to be the first high resolution re-analysis to represent a true historic time series, rather than a statistically averaged climatology. The results are validated against observations from met stations, weather buoys, offshore platforms and satellite-derived wind speeds, and model bias is reduced offshore using satellite derived wind speeds. The ability of the dataset to predict power outputs from current wind farms is demonstrated, and the expected patterns of power outputs from future onshore and offshore wind farms are predicted. Patterns of wind production are compared to patterns of electricity demand to provide the first conclusive combined assessment of the ability of future onshore and offshore wind generation meet electricity demand and contribute to secure energy supplies.

Wind power is being added to the supply mix of numerous jurisdictions, and an increasing level of uncertainties will be the new reality for many system operators. Accurately estimating these uncertainties and properly analyzing their effects will be very important to the reliable operation of the grid. A method is proposed to use historical wind speed, power, and forecast data to estimate the potential future forecast errors. The method uses the weather conditions and ramp events to improve the accuracy of the estimation. A bilevel programming technique is proposed to quantify the effects of the estimated uncertainties. It improves upon existing methods by modeling the transmission network and the re-dispatch of the generators by operators. The technique is tested with multiple systems to illustrate the feasibility of using this technique to alert system operators to potential problems during operation.

Wind power is being added to the supply mix of numerous jurisdictions, and an increasing level of uncertainties will be the new reality for many system operators. Accurately estimating these uncertainties and properly analyzing their effects will be very important to the reliable operation of the grid. A method is proposed to use historical wind speed, power, and forecast data to estimate the potential future forecast errors. The method uses the weather conditions and ramp events to improve the accuracy of the estimation. A bilevel programming technique is proposed to quantify the effects of the estimated uncertainties. It improves upon existing methods by modeling the transmission network and the re-dispatch of the generators by operators. The technique is tested with multiple systems to illustrate the feasibility of using this technique to alert system operators to potential problems during operation.

Generation capacity expansion planning has been evolving in rencent decades. First, the long-term planning procedure is taking more detailed considerations of short-term operation impacts. Second, as more renewable resources being integrated into the grid, a new strategy of dealing with the non-dispatchable renewable energy should be developed, with more ancillary services needing to be procured from thermal units. These trends are expected to continue. This thesis describes a methodology in generation capacity expansion planning. The screening curves method can be used to estimate optimal generation mix for a target year. This thesis first introduces three screening curves methods, which are classified based on their ability to deal with detailed shortterm operational issues. It then includes ancillary service and wind integration impacts. Finally, it presents a case study of a projected ERCOT 2030 system. / text

Flexibility describes the system ability to cope with events that may cause imbalance between electricity supply and demand while maintaining the system reliability in a cost-effective manner. Flexibility has always been present in the power system to cater for unplanned generator outages and demand uncertainty and variability. The arrival of wind generation with its variable and hard to predict nature increases the overall needs for system flexibility. This thesis provides a systematic approach for investigating the role of flexibility in different power system activities including generation scheduling, generation planning and market operation, and furthermore proposes two 'offline' indices for flexibility evaluation. Using the tools and metrics presented in this thesis, it is possible to perform the following tasks: • Conduct generation scheduling simulation to evaluate the impacts of wind on the flexibility requirement of power systems; • Use the unit construction and commitment algorithm to 1) estimate the maximum allowable wind capacity for an existing system; 2) find the optimal investment of new flexible units for accommodating more wind generation; and 3) decide an optimal generation mix for integrating a given wind penetration; • Use the market model to reveal the value and profitability of flexibility and evaluate the corresponding effects of alternative market design; • Use the two proposed flexibility indices to quantitatively assess the flexibility of individual generators and power systems without undertaking complex and time consuming simulations.

No description available.

New European energy policies have set a goal of a high share of renewable energy in electricity markets. In the presence of high levels of renewable generation, and especially wind, there is more uncertainty in the supply. It is natural, that volatility in energy production induces the volatility in energy prices. This can create incentives for the generators to exercise market power by traditional means: withholding the output by conventional generators, bidding not the true marginal costs, or using locational market power. In addition, a new type of market power has been recently observed: exercise of market power on ramp rate. This dissertation focuses on modeling the exercise of market power in power systems with high penetration of wind power. The models consider a single, or multiple profit-maximizing generators. Flexibility is identified as one of the major issues in wind-integrated power systems. Therefore, part of the research studies the behavior of strategic hydropower producers as main providers of flexibility in systems, where hydropower is available.Developed models are formulated as mathematical and equilibrium problems with equilibrium constraints (MPECs and EPECs). The models are recast as mixed-integer linear programs (MILPs) using discretization. Resulting MILPs can be solved directly by commercially-available MILP solvers, or by applying decomposition. Proposed Modified Benders Decomposition Algorithm (MBDA) significantly improves the computational efficiency. / <p>QC 20170516</p>

Sweden has goals to reach net-zero emissions by 2045. Although electricity sector is almost fossil free, industry &amp; transport still rely on fossil fuels. Ambitious initiatives such as HYBRIT, growth of EV market &amp; expansion of wind power aim to expedite emission reduction. Decarbonization of transport, industry and large-scale wind &amp; solar PV integration in the future necessitates studying energy system of Sweden at national scale in the context of sector coupling, external transmission &amp; storage technologies. Therefore, this study aims to evaluate the impact of thermal energy storage, hydrogen storage and batteries via Power-to-heat &amp; Power-to-hydrogen strategies in the future Swedish energy system (2045) with high proportions of wind power. Two scenarios SWE_2045 &amp; NFF_2045 were formulated to represent two distinct energy systems of the future. The SWE_2045 energy system still relies on fossil fuels, but to a lower extent compared to 2019 level and has increased levels of electrification and biofuels in the transport and industrial sectors. In comparison, the fossil fuels are completely removed in NFF_2045 and the industrial sector has significant demand for electrolytic hydrogen. Both the scenarios were simulated using EnergyPLAN, a deterministic energy system model, under each storage technology. The results indicate that HPs coupled with TES has the potential to increase wind integration from 29.12% to 31.8% in SWE_2045 and 26.78% to 29.17% in NFF_2045. HP &amp; TES also reduces heat production from boilers by 67% to 72% depending on the scenario, leading to overall reduction in total fuel and annual costs by at least 2.5% and 0.5% respectively. However, for wind integration of 31.1% in SWE_2045 the annual cost increases by 5.1% with hydrogen storage compared to TES. However, hydrogen storage shows better performance in NFF_2045, wherein the wind integration increases from 26.78% to 29.3%. Furthermore, increasing hydrogen storage for a lower wind capacity (60 GW) in NFF_2045 reduces both electricity import and export while simultaneously increasing the contribution of storage in fulfilling the hydrogen demand from 1.62% to 6.2%. Compared to TES and HS, the contribution of battery storage is minimal in sector integration. For increase in wind integration of 28% to 29%, the annual cost of a system with battery storage is 1.3% to 2% higher than that of the system with TES and hydrogen storage respectively. Therefore, HPs coupled with TES can improve flexibility in both scenarios. Hydrogen storage is not a promising option if the end goal is only to store excess electricity, as shown by the results in SWE_2045. However, it demonstrates better utilization in terms of wind integration, reduction in electricity import and export when there is a considerable demand for hydrogen, as in the case of NFF_2045. / Sverige ligger i framkant när det gäller avkarbonisering och har mål att nå nettonollutsläpp till 2045. Även om elsektorn är nästan fossilfri, är industri och transport fortfarande beroende av fossila bränslen. Ambitiösa initiativ som Hydrogen Breakthrough Ironmaking Technology (HYBRIT), tillväxt av elbilsmarknaden och expansion av vindkraft syftar till att påskynda utsläppsminskningar. Dekarbonisering av transport, industri och storskalig vind- och solcellsintegrering i framtiden kräver att man studerar Sveriges energisystem i nationell skala i samband med sektorskoppling, extern transmissions- och lagringsteknik.  Därför syftar denna studie till att bestämma effekten av termisk energilagring, vätelagring och batterier via Power-to-heat &amp; Power-to-hydrogen-strategier i det framtida svenska energisystemet (2045) med höga andelar vindkraft. Två scenarier SWE_2045 &amp; NFF_2045 formulerades för att representera två distinkta framtidens energisystem. Energisystemet SWE_2045 är fortfarande beroende av fossila bränslen, men i lägre utsträckning jämfört med 2019 års nivå och har ökat nivåerna av elektrifiering och biobränslen inom transport- och industrisektorn. Som jämförelse är de fossila bränslena helt borttagna i NFF_2045-scenariot där transportsektorn endast är beroende av el och biobränslen, medan industrisektorn har en betydande efterfrågan på elektrolytiskt väte. Båda energisystemen simuleras med EnergyPLAN, en deterministisk energisystemmodell, för olika testfall under varje lagringsteknik. Resultatet av simuleringen bedömdes i termer av kritisk överskottselproduktion, potential för ytterligare vindintegration, total bränslebalans i systemet och årliga kostnader.  Resultatet indikerar att värmepumpar i kombination med termisk energilagring kan förbättra flexibiliteten i båda scenarierna genom att minska den kritiska överskottselproduktionen och bränsleförbrukningen samtidigt som vindintegrationen förbättras. Vätgaslagring är inget lovande alternativ om målet är att endast lagra överskottsel, vilket framgår av vindintegrationsnivåerna i SWE_2045. Det förbättrar dock vindintegration och tillförlitlighet avsevärt när det finns en betydande efterfrågan på vätgas i NFF_2045. Som jämförelse är batteriernas bidrag till vindintegration minimalt i båda scenarierna i samband med sektorintegration på grund av utnyttjandet av överskottsel av värmepumpar och extern överföring av restel. Valet av lagringsteknik i framtiden beror dock på dess tekniska ekonomiska utveckling och energipolitik.