Clarifying the Interpretation and Use of the LOLE Resource Adequacy Metric

The loss-of-load expectation (LOLE) risk metric has been used in probabilistic power system resource adequacy assessment for over 70 years, and today is one of the most recognizable and widely-used measures of system shortfall risk. However, this wide adoption has been accompanied by ambiguities and inconsistencies in its definition and application. This paper provides a unifying reference for defining the metric as it relates to modern analyses, while clarifying a number of common points of confusion in its application. In particular, the paper clarifies that LOLE is not a measure of expected total shortfall duration, a 2.4 hours per year LOLE target implies a less reliable system than a 1 day in 10 years (0.1 days per year) LOLE target, and exact conversions between hourly and daily LOLE targets are not generally possible. Illustrative examples are provided to help explain each of these points.

Clarifying the Interpretation and Use of the LOLE Resource Adequacy Metric

The loss-of-load expectation (LOLE) risk metric has been used in probabilistic power system resource adequacy assessment for over 70 years, and today is one of the most recognizable and widely-used measures of system shortfall risk. However, this wide adoption has been accompanied by ambiguities and inconsistencies in its definition and application. This paper provides a unifying reference for defining the metric as it relates to modern analyses, while clarifying a number of common points of confusion in its application. In particular, the paper clarifies that LOLE is not a measure of expected total shortfall duration, a 2.4 hours per year LOLE target implies a less reliable system than a 1 day in 10 years (0.1 days per year) LOLE target, and exact conversions between hourly and daily LOLE targets are not generally possible. Illustrative examples are provided to help explain each of these points.

Power System Market Planning

The loss of load expectation (LOLE) considered an acceptable security standard across most of the national electricity systems. In the present study, the LOLE is calculated. This means that the LOLE needs developing a model. The developed model serving to assesses the security of supply risks associated with the different electricity capacity margin levels, where the capacity margin is the level by which available electricity generation capacity exceeds the maximum expected level of demand. Then, the developed model updated on an annual basis. The annual update is helping to fulfill the Electricity Authority for planning, operation and control. The developed model will assess the system by calculating the capacity margin probability by combining both the generation and load models. The calculation of LOLE is an internationally accepted criterion in capacity adequacy. The results for the model of each region vary due to several factors, such as generation resource, load forecast, and forced outage rates (FOR). The estimation of the risk is economically optimal reserve margin to a number of case studies assumptions considered in the present study. The results help in future planning for the electric system operation and control. Furthermore, the study is helping to evaluate the implications of the obtained results for the electricity policy market to determine the best model for market design in the future.

Importance of Reliability Criterion in Power System Expansion Planning

The self-sufficiency of a power system is no longer a relevant issue at the electricity market, since day-to-day optimization and security of supply are realized at the regional or the internal electricity market. Research connected to security of supply, i.e., having reliable power capacities to meet demand, has been conducted by transmission system operators. Some of the common parameters of security of supply are loss of load probability (LOLP) and/or loss of load expectation (LOLE), which are calculated by a special algorithm. These parameters are specific for each power system. This work presents the way of calculating LOLP as well as the optimization algorithm of LOLP, which takes into consideration the particularities of the power system. It also presents a difference in the treatment of LOLP regarding the observed power system and the necessary installed power capacity if applied to the calculated LOLP in relation to the optimized LOLP. As a conclusion, the study analyzed the parameters impact the regional electricity market—where the participants are countries with different development levels and various particularities of power systems—i.e., what it means when the same LOLP criterion is applied to them and the optimized LOLP.