The variability of solar energy resources affects the technical performance of solar power systems on all time scales. In addition, this variability affects the financial and commercial performance of the system, which is a major consideration for solar project investors. Typically, solar power systems connected to the utility grid are signed with a long-term power purchase agreement (PPA), which sets out the sale of the power generation, and an interconnection agreement (lA), which specifies how the solar power system can be approved for integration into the utility grid. and interact with it. The revenue of the system is often specified in these long-term agreements to ensure that the project is financed. These terms have important implications when assessing the impact of solar resource variability on project performance.
1. price volatility
Many power purchase agreements (PPAs) have different prices based on different times of the day and year. For example, solar electricity prices in southern California are much higher (3 times higher) in summer afternoons than in winter evenings. Fluctuations in such pricing reflect the regulating function of wholesale electricity markets, where electricity prices are higher during periods of peak demand. In the desolate American Southwest, air conditioning loads in the summer afternoons often lead to peak electricity usage. Other electricity markets have different times of peak electricity consumption, and wholesale electricity prices fluctuate accordingly. In contrast, PPAs require a relatively fixed price for electricity coming online at all times. These terms directly affect the calculation process of project revenue and ultimately the risk assessment to support financing.
Variable-priced PPAs depend on the timing of electricity delivery, which requires a detailed review of not only trends in solar resources and generation throughout the year, but also price movements during periods of significant change. Since summer months have both higher electricity prices and abundant solar energy resources, the revenue of solar projects in summer is significantly higher than that in winter. Seasonal fluctuations in revenue must be assessed in payment obligations (debt repayment, operating costs), since seasonal fluctuations in payment obligations are not possible.
In addition, an uncommon approach can be used to establish a project scenario without a PPA. The resource and resource risk analysis in this case is much the same as the usual way. However, possible future changes in market pricing and regulations (e.g. cuts) make this situation even more risky.
A large amount of thermal energy can be stored in the CSP system, which can be converted into electrical energy for delivery and dispatch at any time through solar energy facilities. Although battery storage is not economically attractive and its application deployment is very limited, battery storage in relation to photovoltaic system projects is still a possible solution. Storing electricity adds complexity to resource and revenue analysis because such systems have the ability (or part of the ability) to choose when to deliver the electricity they collect to the utility grid. Depending on the terms of the contract, this flexibility allows targeted projects to achieve optimal revenue through scheduling during periods when prices are at their highest. Analyzing such situations requires a better understanding of the seasonal and daily fluctuations of resources in specific locations.
2. Delivery requirements and capacity tariffs
In a solar project contract, upper and lower limits on the amount of electricity delivered and output power (capacity) can be specified for a specific period. These requirements may further change seasonally. If the energy company fails to meet the above requirements, the buyer can reduce the payment or claim other financial compensation. Therefore, the ability of the project to effectively meet such requirements must be assessed in the solar resource and project performance assessment.
While most current solar projects only receive a fee for outputting electricity, future projects may also be outfitted with large amounts of electricity storage materials. At that time, in the power supply contract with the public grid system, in addition to specifying the amount of power supply, it is also necessary to specify the storage capacity.
The capacity of a utility grid system refers to the amount of power the system can provide during peak electricity consumption. There is an inevitable connection between solar energy resources and peak electricity consumption in most regions. Considering that the peak electricity consumption period often extends into the evening, it is difficult to guarantee the power generation capacity of solar energy projects during this period. However, when equipped with sufficient power storage equipment, solar energy projects can also be regarded as a capacity resource, thereby overcoming the reliability problem of power supply.
When evaluating a solar project with a large number of storage devices, the variability of the solar resource needs to be assessed in terms of both revenue assumptions and whether the project can meet the contracted capacity requirements.
3. Forecast Requirements
Some PPAs may require the project to forecast the amount of electricity delivered on different time scales (eg, daily, weekly, monthly, quarterly). Different protocols may have significant differences in prediction accuracy and penalties for prediction errors (if any). To understand the risks a project faces, the above requirements of the protocol must be understood in the context of solar resource data and its variability.
For example, a project requires quarterly output forecasts one quarter in advance, so quarterly historical variability must be assessed in the solar resource analysis and compared with the contractual allowable limits to understand the probability of penalties. Such requirements could make some lenders more cautious. They generally don’t want a project’s debt repayment ability to be affected by weather risks.
In addition to assessing historical variability, forecasting techniques can be used to increase the confidence of forecasts. However, lenders often don’t provide funding quickly until the technology, including predictions, is proven and applied in the market. Therefore, until the forecasting technology becomes more mature and commercial performance is achieved, investors may be conservative in the assessment of forecast risk, which will be detrimental to the financing terms.
