In the context of the recent COP21 climate agreement, the United States have finally announced a real desire to reduce their greenhouse gas significantly over the coming years. According to President Obama’s Clean Power Plan (CPP), the US plans to reduce greenhouse gas emissions from the electric sector by 32% below 2005 levels by 2030. Substitution of electric power generation by zero-emitting sources such as wind and solar power is one of the three building blocks proposed by the administration to achieve the CPP goals. According to the International Renewable Energy Agency’s (IRENA) REmap 2030 for the US, the CPP goal could be reached through a strong development of renewable energy uptake in the US power sector, accounting for 70% of the emissions reduction. In this scenario around 27% of the US’ electricity generation would come from wind and solar resources in 2030, two intermittent sources of energy. Right now these two sources of energy only account for about 5,6% of total electricity generation in the US, but the potential for these resources is huge. However, high integration of intermittent sources of energy such as wind and solar power puts a burden on power grids and electricity markets that are not properly adapted to such power generation technologies. If these technologies are to expand significantly in the coming years, power grids will have to be expanded and modernized, key practices in electricity markets will have to be adapted and production forecast’s accuracy will be of critical importance.
The US territory is divided in 10 different electricity markets, out of which 3 are still traditional bilateral markets. (source: http://www.ferc.gov/)
The US power sector is divided in 10 different markets, each with its specific regulatory regime and system operators. Since 1996, previously vertically integrated electricity markets started to organize in the form of Independent System Operator’s (ISO). An ISO facilitates open-access to and operates the transmission system, while at the same time operating the energy and ancillary markets through economic dispatching. While today large parts of the country still operate under traditional market structures (NorthWest, SouthWest and SouthEast), two thirds of the electric load is now met under an ISO. Because they provide open-access to the transmission system and the wholesale market, ISO’s are better suited for independent wind and solar power producers to participate in the power system.
The Southwest Power Pool (SPP), which covers a region that has some of the highest wind resources in the country also has the highest integration of wind power in its generation mix (12% in 2014). The California ISO (CAISO) however has the highest integration of solar power in its generation mix, deriving more than 5% of its power generation from the sun. Solar power in California has been growing at a tremendous rate over the last years, with over 4.4 GW of newly installed capacity in 2014. When it comes to wind power however, it is Texas that leads the country, with an installed capacity of 17.7 GW at the end of 2015, providing 9% of all electricity generated in ERCOT, the Texas ISO.
California derives more than thirty percent of its electricity from renewable energy sources and has been leading the country in developing photovoltaïc energy. (source: ACORE)
Wind and solar power are called variable renewable energy (VRE) resources because they are non-dispatchable. This means that their output is dependent on meteorological conditions. Moreover, VRE output is uncertain until realization and it is location specific, since the power has to be produced where the resource is found. Because of this, these sources of energy imply integration costs for the power system that traditional power plants do not have. These integration costs can be divided in three different costs according to their effects.
These costs are the marginal costs of deviating from announced generation schedules due to forecasting errors. They are reflected in the difference between real-time price and the day-ahead price. The determining factor of these costs is first and foremost the size of the forecasting errors. A study on the feasibility of 30% integration of wind and 5% of solar power in the Western part of the US found that uncertainty caused by imperfect forecasts would have the greatest impact on system operation. Other factors include also the capacity mix of the residual system, hydropower balancing being generally cheaper than using thermal plants, and the design and liquidity of the market. By scheduling generation in smaller intervals, they allow short-time forecasts to be more accurate and VRE generators to adjust their scheduled output more frequently to changing wind conditions. CAISO an MISO now operate 5 minute interval real-time markets for this purpose.
Because of the highly variable nature of wind resources, hourly dispatches result in a lot of imbalance charges for wind energy producers. (source: CAISO)
Grid-related costs are the marginal costs of transmission constraints and losses, reflected in the price spreads between locations. Variable renewable energy (VRE) generators tend to produce disproportionately more power in regions of low electricity demand. The highest grid-related costs are related to offshore wind, which is usually installed the farthest from the consumer. Strong transmission networks in many regions in Europe feature lower grid-related costs than large countries with weak grids, such as in the midwest regions of the US where wind resources are very high. SPP has successfully increased its transmission capacities over the last year in order to reliably dispatch record levels of 33% of real-time wind penetration in 2014. CAISO on the other hand implemented its Energy Imbalance Market in 2014, allowing balancing authorities outside the ISO’s balancing area to participate in CAISO’s real-time market. This increases the geographical diversity of the resources that have to be balanced.
Midwestern states where onshore wind resources are the highest also suffer from the poorest grid transmission connections. (source: NREL)
Profile costs are the marginal costs of the temporal variability of VRE output which results in a new profile of net load to be met by the residual capacity (total capacity excluding VREs). Even if we assume that VRE generation could be perfectly forecasted and the entire market has unrestricted transmission capacity, eliminating the previously explained costs, VRE variability would have economic consequences. A first part of these profile costs is the cost of adjusting the output of thermal plant to the changing net load profile, which has higher ramps and a higher need of cycling reserves, this is called the ‘flexibility effect’. The second and most important profile cost is called the ‘utilization effect’ and comes from a reduced utilization of thermal plants, despite a need to maintain a high capacity for reduced amounts of operation time. This is the most important integration cost and is estimated to contribute to two thirds of integration costs at high penetration levels.
The so-called ‘duck-curve’ shows the impact of growing PV capacity on the load profile of CAISO and the increased need for high ramp-up during the evenings. (source: CAISO)
If the United States is serious about their recently unveiled plans to significantly cut carbon emissions in the electricity sector, a massive transition towards renewable energy technologies will have to be made. Recent developments in key states such as California and Texas have been going in the right direction, but to allow further integration of variable renewable energy sources such as wind and solar power, the operation of the power systems will have to be adapted. Apart from an important increase in transmission capacities, an increase in flexibility and liquidity of the markets, the widespread use of accurate VRE forecasting technologies such as Nnergix’ by transmission system operators, market participants and independent power producers will be critical for an efficient power system.
For more detailed information, acces to full article here. (By Cyrille Dubois, Cuong Ngo and Le Chen)