As the penetration of variable renewable generation increases in power systems worldwide, planning for the effects of variability will become more important. Traditional capacity adequacy planning techniques have been supplemented with integration studies, which have been carried out in power systems with high targets for renewable generation. These have highlighted the increased variability that a system may experience in the future. As system generation planning techniques evolve with the challenge of integrating variable generation, the flexibility of a system to manage periods of high variability needs to be assessed. The insufficient ramping resource expectation (IRRE) metric is proposed to measure power system flexibility for use in long-term planning, and is derived from traditional generation adequacy metrics. Compared to existing generation adequacy metrics, flexibility assessment is more data intensive. A flexibility metric can identify the time intervals over which a system is most likely to face a shortage of flexible resources, and can measure the relative impact of changing operational policies and the addition of flexible resources. The flexibility of a test system with increasing penetrations of variable generation is assessed. The results highlight the time horizons of increased and decreased risk associated with the integration of VG.

/pdf/evaluation-of-power-system-flexibility-3j85po2z7z.pdf

Evaluation of Power System Flexibility

Power systems are planned such that they have adequate generation capacity to meet the load, according to a defined reliability target. The increase in the penetration of wind generation in recent years has led to a number of challenges for the planning and operation of power systems. A key metric for generation system adequacy is the capacity value of generation. The capacity value of a generator is the contribution that a given generator makes to generation system adequacy. The variable and stochastic nature of wind sets it apart from conventional energy sources. As a result, the modeling of wind generation in the same manner as conventional generation for capacity value calculations is inappropriate. In this paper a preferred method for calculation of the capacity value of wind is described and a discussion of the pertinent issues surrounding it is given. Approximate methods for the calculation are also described with their limitations highlighted. The outcome of recent wind capacity value analyses in Europe and North America, along with some new analysis, are highlighted with a discussion of relevant issues also given.

/pdf/capacity-value-of-wind-power-31d5ppozx9.pdf

Capacity Value of Wind Power

The value of energy storage in decarbonizing the electricity sector

The electricity sector in OECD countries is on the brink of a large shift towards low-carbon electricity generation. Power systems after 2030 may consist largely of two low-carbon generator types: Intermittent Renewable Energy Sources (IRES) such as wind and solar PV and thermal generators such as power plants with carbon capture. Combining these two types could lead to conflicts, because IRES require more flexibility from the power system, whereas thermal generators may be relatively inflexible. In this study, we quantify the impacts of large-scale IRES on the power system and its thermal generators, and we discuss how to accurately model IRES impacts on a low-carbon power system. Wind integration studies show that the impacts of wind power on present-day power systems are sizable at penetration rates of around 20% of annual power generation: the combined reserve size increases by 8.6% (6.3–10.8%) of installed wind capacity, and wind power provides 16% (5–27%) of its capacity as firm capacity. Thermal generators are affected by a reduction in their efficiency of 4% (0–9%), and displacement of (mainly natural gas-fired) generators with the highest marginal costs. Of these impacts, only the increase in reserves incurs direct costs of 1–6€/MWhwind. These results are also indicative of the impacts of solar PV and wave power. A comprehensive power system model will be required to model the impacts of IRES in a low-carbon power system, which accounts for: a time step of

/pdf/impacts-of-large-scale-intermittent-renewable-energy-sources-44gm7z6kpr.pdf

Impacts of large-scale Intermittent Renewable Energy Sources on electricity systems, and how these can be modeled

Challenges and barriers to demand response deployment and evaluation

The effective load carrying capability (ELCC) is considered the preferred metric to evaluate the capacity value of added wind generation. However, the classical method of computing this metric requires substantial reliability modeling and an iterative process that is quite computationally intensive. Consequently, a noniterative method of estimating a wind plant's ELCC is proposed in this paper. Inspired by Garver's approximation and derived based on well-known reliability concepts, the proposed method provides an excellent approximation while requiring only minimal reliability modeling and no computationally-intensive iterative process. It computes ELCC estimates from a single function using only the wind plant's multistate probabilistic representation and a graphically determined parameter that characterizes the existing power system. After presenting the complete mathematical derivation of this function, the method is applied to compute the ELCC estimates of various wind plants at different penetration levels. It is shown that the resultant ELCC estimates only slightly overestimate the classically computed values by relative errors of 2.5% or less. Furthermore, the proposed method yields more accurate ELCC estimates than the capacity factor approximation, which is commonly used to approximate the ELCC of a wind plant.

Noniterative Method to Approximate the Effective Load Carrying Capability of a Wind Plant

As intermittent renewable generation becomes more significant in the portfolio of power generation, it becomes increasingly important to assess its impact on the generation reliability of power systems. Therefore, it is the objective of this paper to evaluate the reliability impact of wind power penetration using the basic loss of load probability and expectation concepts. To this end, reliability impacts of various levels of wind power penetration are investigated and compared with conventional fossil-based units. The results of this comparison shows that, at wind penetration levels of less than 5%, the reliability impact of the wind farm is comparable to the impact of an energy equivalent conventional unit. However, for penetration levels greater than 5%, the wind farm is less efficient in reducing the LOLE than its energy equivalent unit.

Wind power generation reliability analysis and modeling

The effective load carrying capability (ELCC) is considered the preferred metric to evaluate the capacity value of a wind farm when performing generation expansion studies. Unfortunately, the classical implementation of the ELCC concept requires substantial reliability modeling and a computationally-intensive iterative process. The non-iterative method developed as part of our previous work addresses these issues. In this work, a detailed application of the non-iterative method is presented to compute the ELCC of a wind farm in two case studies. From these case studies, we establish that the non-iterative method can be applied successfully whether or not wind generation is a part of the existing generation portfolio. Foremost, we demonstrate that the non-iterative method can be utilized effectively to compute ELCC estimates for various evaluation periods such as a particular month or peak hours period. Results from both case studies and all evaluation periods show that the non-iterative method provides excellent ELCC estimates with an average relative error of only 2.2% for the first case study and 1.4% for the second. Furthermore, the ELCC estimates are compared to the capacity factor approximation which is often used to estimate a wind farmpsilas ELCC. In these case studies, the capacity factor approach is shown to offer inaccurate ELCC estimates with average relative errors of 20.2% for the first case study and 14.1% for the second.

Analysis of a wind farm’s capacity value using a non-iterative method

Along with many other Independent System Operators, the ERCOT ISO has been charged with the task of integrating renewable resources into the electric power system. A significant amount of this effort has been centered on wind energy. Wind power forecasting has been a key factor in being able to incorporate large Wind-powered Generation Resources (WGRs) into normal operations. Consequently, this paper will present the wind power forecasting tools used by the ERCOT ISO and describe how they are being integrated in System Operations. As part of this discussion, the challenges that have surfaced in implementing these wind power forecasting tools will be explored. Finally, there will be a brief look into anticipated future work and goals for the ERCOT ISO.

C. D'Annunzio

Papers

Capacity Value of Wind Power

Noniterative Method to Approximate the Effective Load Carrying Capability of a Wind Plant

Wind power generation reliability analysis and modeling

Analysis of a wind farm’s capacity value using a non-iterative method

Utilization of forecasts for Wind-powered Generation Resources in ERCOT operations