Increasing Wind Capacity Research Articles

Reasons for the Recent Onshore Wind Capacity Factor Increase

Increasing wind capacity and capacity factors (CF) are essential for achieving the goals set by the Paris Climate Agreement. From 2010–2012 to 2018–2020, the 3-year mean CF of the global onshore wind turbine fleet rose from 0.22 to 0.25. Wind turbine siting, wind turbine technology, hub height, and curtailed wind energy are well-known CF drivers. However, the extent of these drivers for CF is unknown. Thus, the goal is to quantify the shares of the four drivers in CF development in Germany as a case. Newly developed national power curves from high-resolution wind speed models and hourly energy market data are the basis for the study. We created four scenarios, each with one driver kept constant at the 2010–2012 level, in order to quantify the share of a driver for CF change between 2010–2012 and 2019–2021. The results indicated that rising hub heights increased CF by 10.4%. Improved wind turbine technology caused 7.3% higher CF. However, the absolute CF increase amounted to only 11.9%. It is because less favorable wind turbine sites and curtailment in the later period moderated the CF increase by 2.1% and 3.6%, respectively. The drivers are mainly responsible for perennial CF development. In contrast, variations in wind resource availability drive the enormous CF inter-annual variability. No multi-year wind resource change was detected.

Profitability Assessment of Windfarm Overplanting in Spain

The efforts made by European institutions to decarbonise the electricity system over the last decade have led Spain to become the fifth country in the world in terms of wind power plant capacity in 2021. This major achievement is still far from being able to contain and limit CO2 emissions. By 2030, it is expected that, together with photovoltaic energy, Spain will reach 74 % of renewable generation in its electricity system. Wind technology is currently very mature in onshore wind farms and its relatively low cost makes this technology attractive to investors. However, the best wind sites were the first places to be occupied by the first turbine generations. On the other hand, newer wind farms occupy sites with less wind resource but have more efficient turbines. To improve the profitability of the wind farm and increase its production, the feasibility of other alternatives such as overplanting or storage is beginning to be investigated. Overplanting aims to optimise the use of the transmission system by increasing wind capacity above the transmission capacity limit. In this work, we measure the profitability of an overplanting strategy by quantifying the parameters that make profitable the investment. The developed model optimised the production of energy taking into account technical and financial parameters in order to cover a wide range of situations. We analysed the case of a specific site with 25 2 MW turbines with the Python tool PyWake. The results obtained show that for each new turbine the annual energy produced (AEP) grows by around 3.87 GWh per turbine added (a cut of 1.69 GWh due to congestion of the transmission system). The study shows improvements in profitability when the electricity price exceeds 70 €/MWh.

Structural Optimisation of Offshore Direct-Drive Wind Turbine Generators Including Static and Dynamic Analyses

One way to achieve increased wind capacity is by installing larger and more efficient wind turbines, which results in larger/heavier generators. Direct-drive, permanent magnet generators are favoured due to their increased efficiency, but the added weight is an issue, as this drives up the cost of the nacelle and turbine support structure, along with increasing the manufacturing and installation costs. Therefore, minimizing the mass, particularly the structural mass, of these low speed generators is becoming much more important. A vast amount of research has been done on trying to reduce the electromagnetically ‘active’ materials, but it is the supporting structure or ‘inactive’ materials, that makes up the biggest percentage of the generator’s mass. Therefore, this paper studies the statics and dynamics of a large offshore direct-drive generator’s supporting structure and the opportunities for light-weighting, as well as improvements to the generator’s rotor structure through structural optimisation. The indicator for optimised design is system weight under each predefined scenario. These scenarios will cover different design considerations of the generator’s rotor structure.

Zonotope‐based method for optimal allocation of wind capacity in microgrids considering generation uncertainty

The increasing wind capacity integration brings new challenges to power system planning and operation, due to the intermittency and uncertainty of its power generation. This study determines the optimal allocation of wind capacity in microgrids, with considerations of the impact of generation uncertainty on both static and dynamic performance of the system, for reducing the possible violations of operation limits caused by wind power fluctuations. The system performance under uncertainty is evaluated using a zonotope-based set-theoretic method. The uncertain variations of wind power are modelled by a zonotope, then the uncertainty sets of static and dynamic state variables, which capture all possible values of the system states, are further calculated by set operations and are embedded in the optimisation model as constraints for system performance. The proposed method is applied to a 33-bus microgrid; the results prove the validity of the method and show that the system can be guaranteed to operate within acceptable security regions in all possible situations when subjected to certain level of uncertainty.

Optimal allocation of wind capacity considering the impact of generation uncertainty based on zonotope limited security regions

The increasing wind capacity integration brings new challenges to power system planning and operation, due to the intermittency and uncertainty of its power generations. This paper determines the optimal allocation of wind capacity with considerations of the impact of uncertainty in wind generation using the zonotope-based method, for the sack of reducing the possible violations of operation limits caused by wind power fluctuations. The uncertain variations of wind power are bounded by a zonotope and then propagated through a linearised power flow to get another zonotope, which captures all possible values of the system state variables. The state-bounding zonotope is then added to the optimal model to quantify and assess the impact of generation uncertainty on system static performance. The proposed method is applied to IEEE 33-bus system, the results prove the validity of the method and show that the zonotope based set-theoretic method is more efficient than probabilistic methods when focusing on the operation limits with considerations of the uncertainty of multiple renewable energy sources.

The economic impacts of high wind penetration scenarios in the United States

The U.S. electric sector is experiencing rapid increases in renewable generation with an expectation of continued growth. We examine the impacts of increased wind electricity on the U.S. economy using a hybrid model that links a detailed electric sector model (the National Renewable Energy Laboratory's Regional Energy Deployment System [ReEDS]) with a computable general equilibrium model of the U.S. economy (the Massachusetts Institute of Technology's U.S. Regional Energy Policy [USREP] model). Increasing wind capacity displaces fossil fuels for electricity generation, which depresses fossil fuel prices and reduces economy-wide CO2 emissions. Competitive wind deployment in the reference scenario achieves these outcomes with lower electricity prices than a scenario with wind capacity fixed at 2016 levels. Lower fossil fuel and electricity prices benefit low-income households, but the dominant economic impacts are driven by increased electric sector investment and capital returns, which primarily benefit those with higher incomes. Overall, cost-competitive wind provides benefits to the U.S. economy that are initially low but rise beyond 2030 to achieve cumulative welfare and GDP improvements of $110 and $111 billion through 2050.Prescribing additional wind deployment (meeting 35% of demand by 2050) increases post-2030 electricity prices but not more so than keeping wind capacity fixed at 2016 levels. The negative effect of higher prices on welfare, however, is outweighed by higher returns from the additional wind investment. While these changes favor higher income classes, we find economy-wide benefits through 2040. These benefits diminish by 2050, but the cumulative additional gains through 2050, beyond the reference case, are $192 billion in welfare and $150 billion in GDP.

The direct interconnection of the UK and Nordic power market – Impact on social welfare and renewable energy integration

United Kingdom and the Nordic power market have plans to interlink directly through a sub-sea power transmission line in The North Sea. Such power market couplings have complicated implications for the interconnected energy systems and for different agents in the common power market. We analyse this case by modelling the hourly operation of the Nordic-UK power market coupling, considering the local district heating (DH) system in each country as well. According to the results, after the operation of the new interconnection between Norway and the UK (North Sea Link), the overall socio-economic benefits (social welfare) in the region will likely improve by 220–230 million euro per year, without considering the cost of the interconnector itself. The UK-Nordic market coupling enhances the flexibility of the UK power system in wind integration, irrespective of the share of wind in the Nordic countries. However, increasing wind capacity in the UK will diminish the expected economic benefits of the link. The merit order effect of wind integration in the UK will reduce the price gap between UK and Norway, and so the congestion income of the link in many hours a year when the link is congested from Norway towards the UK.

Environmental assessment of wind turbine systems based on thermo-ecological cost

An increased wind capacity penetration reduces loading on conventional thermal units causing higher fuel requirements due to the off-design operation. Regarding the environmental analysis, such an adverse effect should be allocated to the operational phase of wind turbines. In the present work, we apply Thermo-ecological Cost (TEC) to evaluate the environmental performance of wind power systems operating in Poland and Italy. The analysis focuses on the quantitative assessment of the effect of additional chemical energy consumption due to part-load operation of the conventional power units in both analyzed electricity systems. We present the results for two different dispatch strategies. The results confirm high environmental effectiveness of wind power systems. However, the TEC resulting from the compensation for wind generation variations has a significant contribution to the overall LC-TEC index. In particular, without considering the effect of compensation, the TEC for wind turbines are from 47 to 65 times lower than for coal-fired power plants and 35 to 48 times lower than for NGCC plants. Concerning the real load conditions, and considering the effects resulting from the compensation for wind generation variations, the TEC index for this phase contributes between 36% and 75% to the total TEC value.

How do Price Caps in China’s Electricity Sector Impact the Economics of Coal, Power and Wind? Potential Gains from Reforms

China imposes maximum prices by plant type and region on the electricity that generators sell to utilities. We show that these price caps create a need for subsidies and cross-subsidies, and affect the economics of wind power. We model the price caps using a mixed complementarity formulation, calibrated to 2012 data. We find that the caps impose an annual cost of 45 billion RMB, alter the generation and fuel mixes, require subsidies for the market to clear, and do not incentivize adding capacity for a reserve margin. They incentivize market concentration so that generators can cross-subsidize power plants. Depending on the regulatory response, increasing wind capacity can alleviate the distortions due to the price caps. The added wind capacity, however, does not have a significant impact on the amount of coal consumed. We also find that the feed-in tariff was priced slightly higher than necessary.

The impact of wind power growth and hydrological uncertainty on financial losses from oversupply events in hydropower-dominated systems

The rapid expansion of variable renewable energy (e.g., wind and solar) can make it more difficult to balance electricity supply and demand at a grid-scale. While much attention has focused on the risk of unexpected generation shortfalls, periods of oversupply (when supply is greater than demand) also present challenges that can lead to financial losses for utilities and/or consumers when renewable energy is “curtailed”. A unique form of oversupply occurs in hydro-dominated systems. Although hydropower is thought to offer a highly flexible resource that can complement variable renewable energy, seasonal variability in streamflows and the presence of environmental regulations can create complex oversupply conditions if renewable energy is plentiful. In this study, an integrated hydro-economic model is developed to assess the frequency and severity of financial losses arising from oversupply in the U.S. Pacific Northwest, a hydro-dominated system with rapidly growing wind power generation. Present value losses over 25years (2016–2040) are evaluated under several future scenarios including increased wind capacity, electricity price uncertainty, and expanded transmission capacity for moving excess electricity to export markets. Results indicate that oversupply losses will increase as a function of installed wind capacity, with the extent of this increase sensitive to future electricity prices. In the case of adding transmission capacity to alleviate oversupply losses, the cost of this infrastructure is substantially more than the associated reduction in losses and is therefore difficult to justify.

Energy storage and wind power: sensitivity of revenue to future market uncertainties

Grid connected electrical energy storage is expected to enable the integration of variable renewable generation in the future. As the electricity sector develops wholesale electricity prices will change, which will change the way in which storage technologies are operated. This study investigates the sensitivity of storage revenue to uncertain market variables. Results indicate that higher gas prices, carbon prices and average demand would increase peak electricity prices, leading to larger daily price spreads and increased storage revenue. Increased wind generation, however, would reduce opportunities for price arbitrage and lessen storage revenue. Wind power also affects the way in which devices are operated and changes the characteristics which are rewarded by the market. With increased wind capacity, storage devices cycle less regularly as operation is driven by substantial changes in wind power output, rather than daily demand patterns. As a result, slower discharge times are more favourable and revenue is more sensitive to rates of self-discharge. Furthermore, there is less variation in wholesale electricity price and consequently conversion efficiency is more critical to performance.

Allocation of Wind Capacity Subject to Long Term Voltage Stability Constraints

Increasing wind capacity integration results in displacement of active power from conventional generators and a reduction in reactive power sources available. As such, voltage stability may become a concern in certain periods for power system operation particularly in weaker areas of the network. Thus, it is of importance to consider the AC constraints for optimal wind generation planning (long term) in order to decrease the possibility of a wind capacity allocation that requires costly remedies from the power system operation perspective (short term). In this work, a procedure is proposed for wind capacity allocation with the aim of benefiting from the potential of an optimal wind capacity allocation for enhancing the voltage stability margin. The procedure is based on a multi operating conditions voltage stability constrained optimal power flow. The wind capacity target is set and the loadability margin is tracked. The results will show the applicability of the proposed procedure and will emphasize the effects of the pattern of wind capacity allocation on the loadability margin. This will result in a wind capacity allocation that enhances the minimum loadability margin among the possible future operating conditions considered for planning. The procedure uses the Maximin concept for this purpose.

Operational Flexibility of Future Generation Portfolios Using High Spatial- and Temporal-Resolution Wind Data

Increasing amounts of variable renewable energy sources will cause fundamental and structural changes to thermal power plant operating regimes. Maintaining key reserve requirements will lead to an increase in power plant start-ups and cycling operations for some units. An enhanced unit commitment model with energy storage and flexible ${\text C}{{\text O}_2}$ capture is formulated. High-resolution on-/offshore wind data for the U.K., and probabilistic wind power forecast, model wind imbalances at operational timescales. The strategic use of flexible ${\text C}{{\text O}_2}$ capture and energy storage helps maintain reserve levels, decreasing power plant cycling operations and wind curtailment. A temporally explicit variability assessment of net demand illustrates the generation flexibility requirements and the nonlinear impacts of increasing wind capacity on power plant operating regimes.

Is There Still Merit in the Merit Order Stack? The Impact of Dynamic Constraints on Optimal Plant Mix

The merit order stack is used to tackle a wide variety of problems involving electricity dispatch. The simplification it relies on is to neglect dynamic issues such as the cost of starting stations. This leads the merit order stack to give a poor representation of the hourly pattern of prices and under-estimate the optimal level of investment in both peaking and inflexible baseload generators, and thus their run-times by up to 30%. We describe a simple method for incorporating start-up costs using a single equation derived from the load curve and station costs. The technique is demonstrated on the British electricity system in 2010 to test its performance against actual outturn, and in a 2020 scenario with increased wind capacity where it is compared to a dynamic unit-commitment scheduler. Our modification yields a better representation of electricity prices and reduces the errors in capacity investment by a factor of two.

The effects of wind generation capacity on electricity prices and generation costs: a Monte Carlo analysis

ABSTRACTWe use Monte Carlo analysis to examine the potential of increased renewable generation to provide a hedge against variability in energy prices and costs. Fuel costs, electricity demand and wind generation are allowed to vary and a unit commitment and economic dispatch algorithm is employed to produce cost-minimizing generation schedules under different levels of installed wind capacity. Increased wind capacity reduces the mean and the variance of production costs but only the variance of electricity prices. Wind generators see their market revenues increase while consumer payments and fossil generator profits do not considerably vary as wind capacity increases. Risk aversion is captured by considering the conditional value-at-risk for both consumers and producers. The optimal level of wind generation increases as risk aversion increases due to the potential of wind to act as a hedge against very high electricity prices in high fuel price scenarios.

Emissions and Cost Implications of Controlled Electric Vehicle Charging in the U.S. PJM Interconnection.

We develop a unit commitment and economic dispatch model to estimate the operation costs and the air emissions externality costs attributable to new electric vehicle electricity demand under controlled vs uncontrolled charging schemes. We focus our analysis on the PJM Interconnection and use scenarios that characterize (1) the most recent power plant fleet for which sufficient data are available, (2) a hypothetical 2018 power plant fleet that reflects upcoming plant retirements, and (3) the 2018 fleet with increased wind capacity. We find that controlled electric vehicle charging can reduce associated generation costs by 23%-34% in part by shifting loads to lower-cost, higher-emitting coal plants. This shift results in increased externality costs of health and environmental damages from increased air pollution. On balance, we find that controlled charging of electric vehicles produces negative net social benefits in the recent PJM grid but could have positive net social benefits in a future grid with sufficient coal retirements and wind penetration.

Optimal investment timing and capacity choice for pumped hydropower storage

Pumped hydropower storage can smooth output from intermittent renewable electricity generators and facilitate their large-scale use in energy systems. Germany has aggressive plans for wind power expansion, and pumped storage ramps quickly enough to smooth wind power and could profit from arbitrage on the short-term price fluctuations wind power strengthens. We consider five capacity alternatives for a pumped storage facility in Norway that practices arbitrage in the German spot market. Price forecasts given increased wind capacity are used to calculate profit-maximizing production schedules and annual revenue streams. Real options theory is used to value the investment opportunity, since unlike net present value, it accounts for uncertainty and intertemporal choice. Results show that the optimal investment strategy under the base scenario is to invest in the largest available plant approximately eight years into the option lifetime.

The effect of long-distance interconnection on wind power variability

We use time- and frequency-domain techniques to quantify the extent to which long-distance interconnection of wind plants in the United States would reduce the variability of wind power output. Previous work has shown that interconnection of just a few wind plants across moderate distances could greatly reduce the ratio of fast- to slow-ramping generators in the balancing portfolio. We find that interconnection of aggregate regional wind plants would not reduce this ratio further but would reduce variability at all frequencies examined. Further, interconnection of just a few wind plants reduces the average hourly change in power output, but interconnection across regions provides little further reduction. Interconnection also reduces the magnitude of low-probability step changes and doubles firm power output (capacity available at least 92% of the time) compared with a single region. First-order analysis indicates that balancing wind and providing firm power with local natural gas turbines would be more cost-effective than with transmission interconnection. For net load, increased wind capacity would require more balancing resources but in the same proportions by frequency as currently, justifying the practice of treating wind as negative load.

Analysis of impacts of wind integration in the Tamil Nadu grid

As the share of wind in power systems increases, it is important to assess the impact on the grid. This paper combines analysis of load and generation characteristics, generation adequacy and base and peak load variations to assess the future role of wind generation. A simulation of Tamil Nadu in India, with a high penetration of wind power (27% by installed capacity), shows a capacity credit of 22% of the installed wind capacity. For seasonal wind regimes like India, neither the capacity factor, nor the capacity credit reflects the monthly variation in the wind generation. A new approach based on the annual load duration curve has been proposed for generation expansion planning with higher penetration of wind. The potential savings in base and peak capacity required with increasing wind power have been quantified. A future scenario for Tamil Nadu for 2021 has been illustrated. It was found that 5500 MW of wind power can save 3200 MU of peak energy required or an average peak capacity of 2400 and 1100 MW of base capacity. This analysis would be useful to assess the future impacts of increasing wind capacity in grids.

System operation with high wind penetration

The European Union has committed to reduce the equivalent carbon dioxide emissions by 8% of the 1990 level by the end of 2012. To meet the objective, the member states have financially encouraged the development of renewable energy especially wind power. Locally, this results in some of the highest wind power penetration levels in the world. This paper discusses the transmission challenges of Denmark, Spain, Germany and Ireland. With increasing wind capacity, the transmission system operators (TSOs) became concerned about the impact of high levels of wind generation on system stability. The integration of wind power has been hampered by the lack of suitable dynamic models for use in transient stability programs. The number of different turbine technologies used increased the complexity of the modeling problems.