The challenge of wind integration is to make best use of the variable and uncertain power source while maintaining the continuous balance between consumption and generation and high level of reliability in the power system. There is already experience of operating power systems with large amounts of wind power and integration studies give estimates on wind power impacts. Power systems are equipped to handle variability and uncertainty that comes from the electricity consumption, the load. Short‐term wind forecasting is required to manage large amounts of wind power. The main impacts of wind integration are investments in grid infrastructure and efficiency losses in power plants when following the increased variations and uncertainty in the power system. Wind power will lower emissions while replacing energy produced by fossil fuels and can also replace some power plant capacity. However, wind's lower capacity value compared to conventional power plants is one integration impact of wind power, meaning higher total installed capacity in power systems with high wind penetration. Managing options for wind integration impacts includes proper wind power plant grid‐connection rules, increasing transmission capacity and increasing flexibility that is available from generation plants and demand side. Further development of models and tools is required to study how entire power systems can be operated during the hours and days of very high penetration levels covering 60–80% of load.

INTRODUCTION

Wind power is a strongly growing renewable electricity technology that has high technical potential worldwide and high targets of deployment in many countries. Integrating variable and uncertain wind power production to the electricity system is one limiting factor in using the high technical potential. The concerns that wind power brings for system operation are how to maintain power system reliability and the balance between load and generation.

Integration challenge depends on the penetration level of wind power in the power systems. The penetration of wind power can be expressed by various measures. Usually, either energy or capacity metrics are used: yearly wind power production as a percentage of yearly electricity consumption (energy) and installed wind power capacity as a percentage of peak load (capacity). In this chapter, the energy penetration level is used.

There is already experience in operating power systems with 10–20% penetration levels and a lot of studies on the impacts of wind power to power systems. This chapter is about integrating wind power in larger power systems and is mainly based on three summary publications on the issue^[1–3]. For smaller autonomous systems where wind provides a large part of the energy for wind–diesel systems, or in small island systems see, e.g. Refs.^{[4, 5]}.

THE CHALLENGE OF WIND POWER TO POWER SYSTEMS

The goal of power system operations is to maintain the continuous balance between load and generation with high reliability. Possible impacts are presented in Figure 20.1 in two dimensions – impacts in different area size (locally and systemwise) and impacts in different timescales. Impacts can been seen during operation (in seconds to days) and need to be taken into account when planning the adequacy of future generation capacity and transmission grid years ahead.

The integration cost is the additional cost of the design and operation of the nonwind part of the power system when wind power is added to the generation mix. Often, integration costs are associated only with wind power; however, actually other generation can also cause integration costs as increased transmission and increase in contingency reserve to accommodate a large unit, for example. Integration cost can sometimes also be defined as difference in cost compared to some alternative power production that could be added to a system. Cost allocation is another point – often, system costs are allocated to all users in tariffs. Part of the integration costs may be covered by the wind power producers as connection costs and network and imbalance tariffs.

The impacts of wind power can be different for different power systems because power system characteristics are not the same. Adding large amounts of wind power plants will make the power systems more complex and requires new tools and operational practices. Variability and uncertainty in wind generation is managed mainly by using flexible resources in the power systems^{[6, 7]}. Flexibility refers to the ability to change power output level or consumption according to the system needs when keeping the continuous balance of consumption and generation. In general, systems where the balance needs to be kept in smaller areas with power plants operating with fixed schedules have more challenges than larger, well‐interconnected power systems that can use all flexibility options in power plants and have a strong grid to start with.

WIND IMPACTS ON BALANCING AND RESERVES

Power systems have controllable generation to handle significant variability and uncertainty in loads over timescales from seconds to days. The generation is scheduled first based on forecasted demand, then re‐dispatched closer to delivery with updated information on forecasts, and, finally, systems carry operating reserves that will respond either automatically or manually on 5–15 minutes notice to keep the balance of demand and generation at all times. System operators follow the change in total demand, not the variation from a single generator or customer load.

The variations of wind power do not correlate with how the load varies from one time step to another. Adding this new component of variability to a power system will not result in just adding up the total and extreme variability of both, because the extreme variations are not likely to coincide. Power systems carry reserves to handle rare events occurring, for example, once a year. Carrying reserve for even more improbable events such as the extreme of wind and load and a large outage occurring all at the same instant would mean extra costs for reserve that would not be used in practice. “Backup” generating plants dedicated to wind plants, or to any other generation plant or load, are not required, and would be quite costly use of power‐generation resources^{[2, 3]}. Example of the variability of load and the net load, the load minus the wind power produced, is shown from real data from western Denmark that has 24% wind penetration level in a yearly basis (Figure 20.3).

The Variability and Uncertainty of Wind Power

The relative variability of wind will decrease with the aggregation of more wind power plants (Figure 20.4). Aggregating wind generation over larger geographic areas decreases the number of hours of zero output. One wind power plant can have zero output for more than 1000 hours in a year, whereas the output of aggregated wind power in a very large area is always greater than zero. Aggregation also means that the full total installed capacity will not be reached at any instant, as the wind will not blow hard enough over large areas of several hundred kilometers simultaneously. Also, as the technical availability of single turbines is of the order of 95% of time, there will always be some turbines standing still when a fleet of hundreds or thousands of turbines is considered.

The variability also decreases as the timescale decreases. The second and minute variability of large‐scale wind power is generally small. Over several hours, however, there can be great variability even for distributed wind power: low wind and high wind days can still clearly be seen (Figure 20.4).

Storm events can result in extreme variation from wind power: when wind speeds are high enough, wind turbines must shut down from full power to protect them. These events are quite rare: usually one or two times in 1–3 years, depending on location. Large storm fronts take 4–6 hours to pass over several hundred kilometers, so aggregation of wind capacity turns the sudden interruption of power into a multihour downward ramp^[2]. Short‐term forecasts of wind power are critical in managing these situations. Large wind power plants can be required to operate at partial loads during storm events to prevent large ramps. The impact can also be reduced by changing the controls of wind turbines, preventing all turbines from shutting down during the same minute, and reducing the output more slowly as winds increase over cutout wind speeds.

Wind energy forecasting can be used to predict wind energy variability in advance through a variety of methods based on numerical weather‐prediction models and statistical approaches. Wind forecasting has been developed since the 1990s and is still developing^[28]. The overall shape of wind generation can be predicted most of the time, but significant errors can occur in both the level and in the timing of wind generation. Wind forecast accuracy improves for shorter time horizons (Figure 20.5). There is a strong aggregation benefit for wind forecasting, as shown in Figure 20.6. Aggregation over a 750 km region reduces forecasting error by about 50%. In Germany, typical wind forecast errors for representative wind power forecasts for a single wind project are 10–15% of installed wind capacity but drop to 6–8% for day‐ahead wind forecasts for a single control area and to 5–7% for day‐ahead wind forecasts (measured as a root‐mean‐square error [RMSE]). Combining different wind forecasting models into an ensemble wind forecast can also improve wind‐forecasting accuracy by up to 20%^{[1, 28, 29]}.

Both accuracy and uncertainty of short‐term forecasts are important information for system operators, when allocating the reserves needed to manage the real‐time operation.

Frequency Control and Reserves

The reserve requirement addresses the more short‐term flexibility for power plants that can follow unpredicted net load variations. Wind power will also increase the need for flexibility for power plants that can follow the scheduled net load. Operational practices, such as markets scheduling on hourly level or scheduling at 5–15 minutes, will also have an impact on how much reserves are needed during the operating hour. Experience shows that when reaching penetration levels of 5–10%, an increase in the use of short‐term reserves is observed, especially for reserves activated on a 10–15 minutes timescale. So far, no new reserve capacity has been built specifically for wind power^{[8, 30]}.

In Portugal and Spain, new pumped hydro is planned to increase the flexibility of the power system, and this is mainly driven by wind power to enable more than 15% penetration levels^[11]. In the highest wind penetration countries – Denmark, Spain, and Portugal – no significant frequency impacts have been observed that are the result of wind power variation^[31].

In wind integration studies, the increase in short‐term reserve requirements is mostly estimated by comparing the reliability of the system before and after the addition of wind. A basic approach is to combine the variability or forecast errors of wind power with that of load and in some cases also power plant outages, and to investigate the increase in the largest variations seen by the system. The range of results for reserve requirement increase due to wind power is wide (Figure 20.7): Increased reserve capacity should be 1–15% of installed wind power capacity at 10% penetration and 4–18% of installed wind power capacity at 20% penetration^[1]. Timescales used in the estimation explain much of the differences in results, as can be seen from German results from 2010 that calculate the reserve requirement based on either day‐ahead, four hours ahead, or hour‐ahead uncertainties^[32]. German Dena estimates only show the average day‐ahead uncertainty (for up and down reserves separately)^[18]. In Minnesota^[33] and California^[34], day‐ahead uncertainty has been included in the estimate. UK study^[35] combines the four‐hours‐ahead variability of wind to load uncertainty–using wind forecasting would give lower results^[1]. For others, the effect of variations during the operating hour is considered^[36], with Ireland^[37] and Sweden^[38] including the four‐hours‐ahead uncertainty separately. All studies show an increasing trend of reserve requirements as wind penetration increases. Even if the aggregation benefits of wind power can decrease the reserve requirements, in the studies it is often assumed that the smoothing effect reaches its maximum already at lower penetration levels, and adding wind in the same area will no longer decrease the variability nor forecast error levels.

With high wind penetration, it will be beneficial to allocate reserve requirements dynamically. If allocation is estimated once a day for the next day instead of using the same reserve requirement for all days, the low wind days will induce less requirements for the system, and thus the reserve allocation can be increased only for days when wind variability and uncertainty are at highest^{[15, 30]}.

Increasing reserve requirements is usually calculated for the extreme cases. Even if there is an increase in reserve requirements, this does not necessarily mean new investments for reserve capacity; rather, generators that were formerly used to provide energy could now be used to provide reserves^[1].

BALANCING COSTS OF WIND POWER

Balancing costs reflect increased use of reserves and less‐efficient scheduling of conventional power plants. Impact on efficiency of conventional power plants needs simulations of power system scheduling and dispatch and they are mostly based on comparing costs of system operation without wind and adding different amounts of wind. The studies show a significant reduction of operational costs (fuel usage and costs) due to wind power even at higher penetration levels so the integration effort will not offset the emission savings of wind power^[44]. To capture the integration cost means capturing the difference of full credit for operating cost reduction compared with cost for system operation, with efficiency penalties due to increased variability and uncertainty. One way of capturing cost of variability is by comparing simulations with flat wind energy to varying wind energy^{[33, 45]}. However, the two simulated cases can also result in other cost differences than just the variability cost^[46].

Increase in balancing costs at wind penetrations of up to 20% amounted to roughly 1–4 € MWh⁻¹ of wind power produced^{[1, 33, 35–37, 45, 47–51]}. If interconnection capacity is allowed to be used for balancing purposes as well, the balancing costs are lower compared to the case where balancing is made only in the area – increasing area size will have aggregation benefits of wind power and also add more balancing power. The two points for Greennet Germany and Denmark^[45] at the same wind penetration level reflect that balancing costs increase when neighboring countries get more wind^[52] (Figure 20.8).

Not all case studies presented results quantified as MW of increase in reserve requirements or monetary values for increase in balancing costs. The Ireland All Island Grid Study shows that the net benefit for the power systems, going from 2 to 6 GW wind, will be €13 MWh⁻¹, as the operational costs of the electricity system fall compared to the base case^[22].

CURTAILMENTS OF WIND POWER GENERATION

Challenging situations seen in system operation so far are from high wind‐power generation during low‐load situations, when wind power penetration levels exceed 50%^[11]. Wind is usually last to be curtailed. However, when all other units are already at a minimum (and some shut down), system operators sometimes need to curtail wind power to control frequency^[8]. Denmark has solved part of the curtailments by increasing flexible operation of combined heat and power plants and by lowering the minimum generation levels used in the thermal plants^[1].

In Ireland, some curtailments have been due to concerns of low inertia^[53], and consequently, susceptibility to instability in the system because of high instantaneous wind penetration and low system load. Currently, the issue of low inertia is unique to small systems such as those in Ireland and Crete in Greece^[3]. In Ireland, they are working on solutions to go up to 75% penetration levels^[21].

WIND IMPACTS ON THE TRANSMISSION GRID

Grid planning for future wind energy targets brings needs to reinforce the grid as well as building new lines, both inside the country/region as well as interconnection to neighboring countries/regions. Transmission is important both for enabling transfer of the generated electricity to loads and also for gaining aggregation benefits in variability and uncertainty of wind power. Assessing the impacts of wind power to the transmission grid involves steady‐state load flow and transient stability simulations of the network for specific snapshots situations. Network contingency situations are studied to meet the criteria of power system operation and safety established by the system operator.

Wind power is normally not the only driving force for grid investments, but it is a major factor (Ireland^[59], Germany^[60], Europe^[61], and the United States^[62])^[16]. The cost of grid reinforcements due to wind power depends on where the wind power plants are located relative to load and grid infrastructure. Portugal reported €145 million (70 € kW⁻¹) increase in grid infrastructure investments in the period 2004–2009 for increasing wind penetration from 3% (1400 MW) to 13% wind energy penetration (3500 MW)^[16]. In several studies, grid reinforcement costs roughly vary from 0 to 270 € kW⁻¹ reflecting different systems, countries, grid infrastructure, and calculation methodologies^[1].

A challenge for transmission planning is to resolve the scheduling conflict where wind plants can be permitted and constructed in 2–3 years and it may take 5–10 years to plan, permit, and construct a transmission line. Some transitional solutions can allow wind power plants to connect to the existing grid, even if there will be times when the grid is not strong enough to transmit all generation produced^[3]. Dynamic line ratings, taking into account the cooling effect of the wind together with ambient temperature in determining the transmission constraints, can increase transmission capacity and delay the need for network expansion. By curtailing the generation in critical situations, grid equipment such as overhead lines or transformers can be protected from overloads. As wind power will produce most of the time at part load, the critical situations often result in only small production losses, and in these cases it can be cost‐effective to curtail and thus lower the connection costs^[63]. However, these transitional solutions are insufficient for large amounts of wind power and can result in high curtailments, such as in Texas, with 17% of all potential wind energy generation curtailed in 2009^[64].

CAPACITY VALUE OF WIND POWER

Power system planning includes determining generation capacity needs for the future. Wind power is often considered as an energy source, but it can also provide some capacity to be relied on during peak loads. Ensuring power adequacy is typically done using reliability analysis, which is based on loss of load probability (LOLP) or loss of load expectation (LOLE). The use of these approaches allows the system planner to determine the power adequacy level and also the contribution that each generating plant makes toward resource adequacy, called capacity credit or capacity value^{[2, 65]}. The availability of high‐quality chronological synchronized data that captures the correlation with load data is of paramount importance, and the robustness of the calculations is highly dependent on the volume of this data.

So far, wind power has been built as additional generation to power systems, and thus no problems with having adequate power capacity to cover peak loads have been reported^[8].

The results from studies estimating the capacity value for wind power range from 5% to 40% of wind‐rated capacity (Figure 20.9). The wide range of capacity credit assigned to wind reflects the differences in the timing of wind energy delivery (when the wind blows) relative to system peak loads^[66]. Aggregating larger areas benefits the capacity credit of wind power^{[1, 67]}.

In some reports, the term capacity cost is used. The meaning of this is the cost for the difference between lower‐capacity credit for wind power and higher‐capacity credit for a conventional power plant. It is not straightforward to calculate how a “reduced value” transforms to a cost for wind power. It is important to use the lowest investment cost‐generating capacity as backup so as not to overestimate this cost^[68].

CONCLUSION AND OUTLOOK

The natural variability of wind power makes it different from other generating technologies. This raises questions about how wind power can be successfully integrated into the grid. Power systems are equipped to handle variability and uncertainty that comes from the load. There is already a lot of experience of operating power systems with large amounts of wind power, and integration studies have also offered valuable insights into how high wind penetrations can be successfully achieved. Model and tool development is still required to study how entire power systems can be operated with occasionally high penetration levels at 60–80% of load.

Wind integration means investments in grid infrastructure and increased use of balancing power that can lead to efficiency losses in power plants. There will be significant reduction of operational costs (fuel usage and costs) due to wind power, even at higher penetration levels, so integration effort will not offset the emission savings of wind power. The capacity value of wind power is less than for conventional power plants and will reduce at higher penetration levels.

Reaching high wind penetration levels challenges generation owners and transmission operators to better utilize technology and existing assets to provide flexibility. More flexibility from the nonwind generation fleet would include reduced minimum generation levels, greater ramp rates, quicker start times, and designs that allow frequent cycling without increasing material fatigue or reducing component lifetimes. This will require incentives or requirements, and markets and tariffs also need to be designed to reward increased flexibility. Integrating wind power generation into power systems can be aided by enlarging balancing areas and moving to subhourly scheduling, which enable grid operators to access a deeper stack of generating resources and to take advantage of the smoothing of wind power output due to geographic diversity. The ongoing developments of smart grids demand response, and plug‐in hybrids as well as continued improvements in new conventional generation technologies will give new opportunities for wind integration.

ACKNOWLEDGMENTS

This work is part of International Energy Agency Implementing Agreement for Wind Energy (IEAWIND) research collaboration Task 25 Design and Operation of Power Systems with Large Amounts of Wind Power http://www.ieawind.org/AnnexXXV.html. All participating members are greatly acknowledged for providing information on wind integration studies and experience. Juha Kiviluoma is acknowledged for his comments on the text.

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