Incorporating reliability index distributions in small isolated generating system reliability performance assessment

This work deals with assessing the reliability of wind energy sources incorporated into a microgrid system to increase grid stability. As the share of power generated from wind energy continues to increase due to environmental concerns and to reduce carbon footprints, the case study proposed is designing an effective wind energy system for a smart building environment to reduce the burden on the grid. Incorporating wind energy systems into grid-connected buildings increases the reliability of the microgrid system for smart building environments. Applying smart techniques with integrated automation in the built environment can play a key role in decreasing peak demand for load development in smart cities. This can also enhance the overall efficiency of power grids, reduce waste, and enable the effective use of energy resources. Furthermore, researchers are finding new ways to collect energy from renewable sources and power-built environments due to dwindling fossil fuel resources and increased environmental awareness. The analysis of wind-connected power systems has been initiated to satisfy the increasing demand for reliable supply systems by consumers. This has prompted the use of wind energy systems with controlled techniques to enhance the reliability of power systems and reduce carbon footprints generated by fossil fuel-based power systems. Therefore, the main purpose of this work is to understand the economic prospects of wind energy sources for smart building environments, reliability analysis of wind energy sources-based power systems, reduce carbon footprints, and balance power demand through wind energy systems. The Progressive Wind Model Taylor-Sequence Proliferation (PWMTSP) and Innovative Six Parameters Based Progressive Beta Creative Model (ISPBPBCM) approaches are proposed to understand the reliability of wind energy-based power systems in smart building environments. The work also provides an economic analysis of the proposed low-cost wind power system with different capacities for residential consumers in selected geographic location. Eight cases are considered for the proposed effective wind energy system for smart building environments ranging from 2 MW to 32 MW. Hence, the economic analysis of the proposed systems is discussed for residential users. All eight cases are eco-friendly and reduce carbon emissions as these generated units from wind energy sources need not be purchased from fossil fuel-based plants, which increases the reliability of the proposed system. The expected energy not supplied (EENS) in the planned work increases as wind power capacity increases. Loss of load expectation (LOLE), loss of load probability (LOLP), and failure rate all decrease with the installation of more wind power systems. Moreover, it can be seen that mean time to repair (MTTR) improves when wind energy capacity rises incrementally from 2 MW to 32 MW. The proposed method is anticipated to be adaptable to various types of wind energy systems where dependability is a crucial component of system design and scalable to large wind integrated power systems.

Guest Editorial

Reliability assessment techniques and programs handling is an important issue for both power systems planning and testing in existing power system configurations. The Assessment techniques are suitable for detecting weak points in the reliability assessment. The reliability study of bulk power systems indicates the ability of the composite generation and transmission system to satisfy the load demand at major load points. The major burden of the developed methods used is the computation time required to solve a large number of credible contingencies or outage states. This paper presents a novel approach capable of the reliability evaluation for real large-size networks using normal size computers. It calculates the reliability indices at individual load buses and reliability of the whole system. The effect of the loading factor between loads on reliability is also investigated. The proposed approach is expanded to calculate the reliability of composite generation and transmission system taking the following constraints into consideration: amount of reliability of system generation, amount of reliability of transmission lines, maximum system generation capacity, maximum transmission lines capacity and maximum connected load at each bus. The approach is based on the minimal path set and dual fault tree techniques. A new concept of constant reliability region, which is utilized in the field of optimum operation of power networks, is introduced. A special program is developed for the proposed technique. The comparison between the proposed and the previous techniques confirms that the proposed method is more accurate and precise.

Wind power has the characteristics of randomness and intermittent, with the increasing unit capacity of wind turbines and wind farm scale, it is urgent to study the impact on generation and transmission system reliability. In addition, there are different degrees of correlation among regional multiple wind farms because of their geographic proximity. When it comes to research on the influence on the power system reliability, the analysis result will be larger error without considering the correlation, which is optimistic for reliability assessment. Therefore, it is meaningful to take the correlation into account in wind power system reliability assessment. In this paper, IEEE-RTS 79 generation and transmission reliability test system is adopted to verify the reliability assessment of power systems with wind farms considering correlations. The experimental results show that adding wind turbines in the original power system, system reliability has been greatly improved; and the system has higher reliability with given the considering the correlation between wind farms.

In the last two decades, the wind power generation has been rapidly and widely developed in many regions and countries for tackling the problems of environmental pollution and sustainability of energy supply. However, the high share of intermittent and fluctuating wind power production has also increased the burden of system operator for securing power system reliability during the operational phase. Moreover, the power system restructuring and deregulation have not only introduced the competition for reducing cost but also changed the strategy of reliability evaluation and management of power systems. The conventional long-term reliability evaluation techniques have been well developed, which have been more focused on planning and expansion rather than operation of power systems. This paper proposes a new technique for evaluating operational reliabilities of restructured power systems with high wind power penetration. The proposed technique is based on the combination of the reliability network equivalent and time-sequential simulation approaches. The operational reliability network equivalents are developed to represent reliability models of wind farms, conventional generation and reserve provides, fast reserve providers and transmission network in restructured power systems. A contingency management schema for real time operation considering its coupling with the day-ahead market is proposed. The time-sequential Monte Carlo simulation is used to model the chronological characteristics of corresponding reliability network equivalents. A simplified method is also developed in the simulation procedures for improving the computational efficiency. The proposed technique can be used to evaluate customers’ reliabilities considering high penetration of wind power during the power system operation in the deregulated environment.

This paper reviews some of the analytical methods developed in our laboratory for reliability evaluation of large scale power systems including renewable energy sources like photovoltaic units and wind farms. The methods presented here successfully reflect the correlations existing between the hourly load and the fluctuating energy outputs of unconventional generating units. Three different approaches, each an improvement over its predecessor, are presented for computing reliability indices like Loss of Load Expectation (LOLE) and Expected Unserved Energy (EUE). In the first approach, all the generation system models are combined hourly by means of an efficient algorithm for calculating the relevant reliability indices. The second approach uses a clustering algorithm for identifying a set of system states, such that the reliability indices are calculated for each state and then aggregated to yield overall values. The third approach introduces the concept of mean capacity outage tables for efficiently calculating EUE,

Dynamic regulation reliability of a pumped-storage power generating system: Effects of wind power injection

Risk index of loss-of-load expectation is traditionally used to determine generation adequacy. However, be-cause responsibility of generation installation and demand increases with different entities, both generation and load need to be examined to evaluate the resource adequacy of today’s deregulated power systems. An electric utility’s main concern is to plan, design, operate and maintain its power supply to provide an acceptable level of reliability to its users. This clearly requires that standards of reliability be specified and used in all three sectors of the power system, i.e., generation, transmission and distribution. Reliability indices have been defined for the three sectors separately as well as for the bulk power system. Reliability criteria may be determined at the selected load points in the system for different combination of generators and transmission line failures. This paper presents an effective simulation method for the reliability assessment of reliability index, loss-of-load expectation (LOLE). This method is applied to Bangladesh Power System (BPS). BPS has a total installed capacity of around 6550 MW. The maximum demand of BPS is about 5700 MW. The relevant data of the generators and hourly load profiles are collected from the National Load Dispatch Center (NLDC) of Bangladesh and reliability index ‘LOLE’ is assessed for the last six years.

In this paper, a probabilistic analytical approach for reliability evaluation of power systems with high penetration of wind and solar photovoltaic (PV) renewable power generation is presented. Due to intermittent nature of wind and solar power, the traditional deterministic method cannot properly address such uncertainties, probabilistic methods need to be utilized. In this paper, the loss of load method, one of the most effective probabilistic analytical methods, is adopted. The generation model is represented by the capacity outage probability table (COPT). The load model is presented by the load duration curve (LDC). Both generation and load models are used to obtain the system reliability considering wind and PV sources with certain forced outage rate (FOR). Simulation results are obtained using MATLAB. It is found that renewable energy sources can significantly improve the system reliability, but not as good as conventional power generators with the same rated capacity due to the actual reduced capacity value of renewable energy sources caused by intermittency. This analytical analysis is useful for the power system planner to quantify reliability improvements by installing grid-connected hybrid renewable power generation.

Generation planning utilizes reliability indices as criteria to ensure adequacy in terms of total installed capacity. Reserve Margin and Loss of Load Expectation (LOLE) are the most widely-used indices in generation adequacy evaluation. Reserve Margin is a measure of available capacity over and above the capacity needed to meet normal peak demand levels. In Peninsular Malaysia, the amount of Reserve Margin has been perceived to be high. Generally, high Reserve Margin can provide high reliability. However, it acquires more generation plant, for which some of them may not be necessary. This may indicate over investment which will be reflected in the tariff structure. LOLE is a probabilistic measure which indicates the risk at which the generation capacity fails to meet the demand and its evaluation involves specific parameters such as the plant capacity and outage rate of each generating unit. Therefore, in order to have optimum generation planning and investment efficiency, it is necessary to perform a study on the practical Reserve Margin level with respect to the current LOLE requirement without endangering the overall power system reliability. This research studies the factors affecting LOLE and evaluates the relationship between Reserve Margin and LOLE under various conditions. A modified Peninsular Malaysia system is simulated using Wien Automatic System Planning (WASP -IV) to determine LOLE focusing on thermal power plants. This study concludes that peak load and forced outage rate give significant impacts to the LOLE and thus, the reliability of the system. Effort to ensure availability especially during peak load may need to be intensified. The study also establishes an inverse exponential curve for the relationship between Reserve Margin and LOLE. It is found that the outcome of the study is to enhance generation planning decision making in obtaining the optimum Reserve Margin considering the LOLE under various conditions.

This study evaluated a potential transition of India’s power sector to 100% wind and solar energy sources. Applying a macro-energy IDEEA (Indian Zero Carbon Energy Pathways) model to 32 regions and 114 locations of potential installation of wind energy and 60 locations of solar energy, we evaluated a 100% renewable power system in India as a concept. We considered 153 scenarios with varying sets of generating and balancing technologies to evaluate each intermittent energy source separately and their complementarity. Our analysis confirms the potential technical feasibility and long-term reliability of a 100% renewable system for India, even with solar and wind energy only. Such a dual energy source system can potentially deliver fivefold the annual demand of 2019. The robust, reliable supply can be achieved in the long term, as verified by 41 years of weather data. The required expansion of energy storage and the grid will depend on the wind and solar energy structure and the types of generating technologies. Solar energy mostly requires intraday balancing that can be achieved through storage or demand-side flexibility. Wind energy is more seasonal and spatially scattered, and benefits from the long-distance grid expansion for balancing. The complementarity of the two resources on a spatial scale reduces requirements for energy storage. The demand-side flexibility is the key in developing low-cost supply with minimum curtailments. This can be potentially achieved with the proposed two-level electricity market where electricity prices reflect variability of the supply. A modelled experiment with price signals demonstrates how balancing capacity depends on the price levels of guaranteed and flexible types of loads, and therefore, can be defined by the market.

Wind power is an intermittent energy source that behaves quite differently from conventional energy sources. The reliability impact of this highly variable energy source is an important aspect that needs to be assessed as wind power penetration becomes increasingly significant. Generation adequacy assessment including wind energy conversion systems (WECS) at multiple locations is described in this paper. Effective load-carrying capabilities (ELCC) obtained using the loss of load expectation (LOLE) and the loss of load frequency (LOLF) for a power system containing WECS are illustrated and compared. The results show that ELCC obtained using the LOLF and obtained using the LOLE for WECS can be considerably different, while they are similar for a conventional generating unit. The impact on the system reliability indices of wind speed correlation between two wind farms is also examined. The studies show that the degree of wind speed correlation between two wind farms has a considerable impact on the resulting reliability indices. The sequential Monte Carlo simulation approach is used as this methodology can facilitate a time series modeling of wind speeds, and also provides accurate frequency and duration assessments. An autoregressive moving average time series model is used in this study to simulate hourly wind speeds

The imminent exhaustion of fossil energy resources and the increasing demand for energy were the motives for those reasonable in world to put into practice an energy policy based on rational use of energy; and on exploitation of new and renewable energy sources. After 1980, as the supply of conventional energy has not been able to follow the tremendous increase of the production demand in rural areas of the world, a renewed interest for the application of solar and wind energy has shown in many places. Therefore, the researchers and engineers began to pay more attention to wind and solar energy utilisation in rural areas. Because the wind energy resource in many rural areas is sufficient for attractive application of wind pumps, and as fuel is insufficient, the wind pumps will be spread on a rather large-scale in the near future. Wind is a form of renewable energy, which is always in a non-steady state due to the wide temporal and spatial variations of wind velocity. The need for the provision of new data stations in order to enable a complete and reliable assessment of the overall wind power potential of the country is to be identified and specific locations suggested. This article presents the background and ideas of the development of the concept as well as the main results and experience gained during ongoing projects up to now. In the world, various designs of wind machines for water pumping have been developed and some designs are presently manufactured commercially. Results suggest that wind power would be more profitably used for local and small-scale applications especially for remote rural areas. It is concluded that many parts of the world is enjoyed with abundant wind and solar energy resources.

Finding the reliability expression of different substation configurations can help design a distribution system with the best overall reliability. This paper presents a computerized a nd implemented algorithm, based on Disjoint Sum of Product (DSOP) algorithm. The algorithm was synthesized and applied for the first time to the determination of reliability expression of a substation to determine reliability indices and costs of different substation arrangements. It deals with the implementation and synthesis of a new designed algorithm for DSOP implemented using C/C++, incorporating parallel problem solving capability and overcoming the disadvantage of Monte Carlo simulation which is the lengthy computational time to achieve satisfactory statistical convergence of reliability index values. The major highlight of this research being that the time consuming procedures of the DSOP solution generated for different substation arrangements using the proposed method is found to be significantly lower in comparison with the time consuming procedures of Monte Carlo-simulation solution or any other method used for the reliability evaluation of substations in the existing literature such as meta-heuristic and soft computing algorithms. This implementation gives the possibility of RBD simulation for different substation configurations in C/C++ using their path-set Boolean expressions mapped to probabilistic domain and result in simplest Sum of Disjoint Product which is on a one-to-one correspondence with reliability expression. This software tool is capable of handling and modeling a large, repairable system. Additionally, through its intuitive interface it can be easily used for industrial and commercial power systems. With simple Boolean expression for a configuration’s RBD inputted, users can define a power system utilizing a RBD and, through a fast and efficient built-in simulation engine, the required reliability expressions and indices can be obtained. Two case studies will be analyzed in this paper. The effects of different substation configurations on the reliability are analyzed and compared. Then, the reliability of a radial distribution system will be evaluated using DSOP solution. The failure results will be combined with a load flow scenario, and indices such as SAIDI, SAIFI will be determined.

Integration of renewable energy sources, such as wind power and solar power, into the generation system can enhance country's energy security. These alternative energy help diversify sources of primary energy used to produce electricity. However, the biggest disadvantage of using these types of renewable energy power plants is that it might reduce power system reliability because these intermittent renewable energy sources have low dependable capacity. This paper aims to evaluate the dependable capacity of wind power and solar power generation systems. It considers uncertainties due to intermittent wind speed, solar irradiance, ambient temperature, and unavailability of their corresponding generators. Additionally, load uncertainty is also taken into account. The dependable capacity of the wind power and solar power generation systems are determined from the principle of generation system reliability evaluation. The reliability index such as Loss of Load Probability (LOLP) will be used as a key indicator to define the dependable capacity.