Advanced synchronizing systems improve reliability and flexibility of offshore power systems

Power system is one of the most complex systems ever designed. Determining its reliability is therefore a demanding process, which is mostly dealt with in a way that partial problems are stated and solved. A reliability method of loss of load expectation is selected and improved and the model of conventional power system is considered as a standpoint. Reliability of the initial conventional power system is evaluated. Then, the conventional power system is changed, where one conventional power plant is abandoned and new wind power plants stand to its place. The reliability of the initial and the changed power system is calculated and compared. Discussion shows the problems of decreased reliability of the power system with increasing the percentage of wind power plants within the power system replacing conventional plants, if not enough reserve is added to the power system at the same time. The other related problems are discussed in addition, to show that the problem is very complex and one cannot only consider a limited number of influencing parameters when deciding on power system configurations.

In the power system of the future, reliability will play an important role. This reliability is influenced by different developments like the increase in electricity consumption and the use of renewable and distributed generation. It is important to have a good insight into the reliability performance of the system. With probabilistic methods, the reliability of the power system can be analyzed and decisions can be made to maintain the high reliability level that we demand. This paper gives an overview of the different developments in power systems and describes how these developments influence the reliability of the future power system. The possibilities to implement these developments into the probabilistic reliability analysis in network planning and operational planning are discussed. By use of an example, the possibilities and challenges of probabilistic methods in operational planning are illustrated.

The reliability of power system will obviously be influenced by wind farms connected because of the volatility of wind power. With the increase of wind power penetration, it's necessary to research the influence of wind power integration on the reliability level of system and how much reserve capacity should we increase in order to stabilize the influence of wind power on power system reliability. In this paper a reliability evaluation model is built by Monte Carlo method and also a reserve optimization model, which can be used to analyze changes of system reliability in conditions of different grid-connected wind farms, and to find out the optimum of system reserve to achieve unifying the maximum utilization of new energy and meanwhile high reliability of power system.

Uncertainty parameters of battery energy storage integrated grid and their modeling approaches: A review and future research directions

Review of real-time electricity markets for integrating Distributed Energy Resources and Demand Response

Operational flexibility is an important property of electric power systems. The term flexibility is widely used in the context of power systems although at times without a proper definition. The role of operational flexibility for the transition of existing power systems, many of them based on fossil fuels, towards power systems effectively accommodating high shares of variable Renewable Energy Sources (RES) has been widely recognized. Availability of sufficient operational flexibility is a necessary precondition for the grid integration of large shares of power in-feed from variable RES, for example wind power and photovoltaics (PV). The paper analyzes the role of operational flexibility in power systems. Necessary flexibility metrics for categorizing different types of operational flexibility are discussed. A new methodology for assessing the technically available operational flexibility is presented. Qualitative insights are derived, notably regarding the limits of RES integration for a given power system with its specific flexibility properties. An extensive simulation study is performed, assessing the role that operational flexibility has for the mitigation of challenges, namely curtailment, arising from high shares of variable RES in-feed.

Under the new power system, a high proportion of new energy is widely connected to the power grid, and it is necessary to increase investment in centralized and distributed energy storage, flexible resource regulation, and transmission and distribution grids, resulting in an increase in power system costs. The current electricity capacity price does not reflect the economic value of the added system adequately, and flexible capacity is needed to ensure the safety of the power grid under the new power system. In the context of the transformation of the new power system and investment function, it is increasingly difficult to recover the costs according to the traditional electricity price. It is necessary to establish a coordinated development mechanism for the electricity capacity price and the electricity price that recovers the fixed costs according to the investment function to ensure a reasonable return on investment in flexible resources and to provide effective investment signals. Therefore, this work first studied and proposed a mechanism for the formation of capacity and electricity prices based on the proportion of allowed income and fixed costs at different voltage levels and calculates the level of electricity capacity (demand) prices and electricity consumption prices. Then, using the BARY curve, genetic algorithm, and clustering of user load rates, a collaborative mechanism between the electricity capacity price and the electricity price was designed. With the goal of optimizing the electricity capacity price and considering constraints such as the flexibility and reliability of the new power system, the ratio of the capacity cost allocated to the electricity capacity price by voltage level users to the capacity cost allocated to the electricity price was calculated, and the optimal combination of electricity capacity price and electricity price for different load‐rate intervals was determined. Finally, the effectiveness of the model was verified through numerical simulations. On the basis of the investment characteristics of the new power system, suggestions for a capacity pricing mechanism under the new power system were proposed from the perspectives of transfer capacity function, transfer electricity function, grid reliability, and environmental and social benefits.

Reliability and economic evaluation of power system with renewables: A review

Power system control is an important issue with regard to power system safety, flexibility, and reliability. Over the years, various new power system control strategies have been explored, but the main disadvantage of these control strategies is their complexity in structures with respect to industrially applied PID controller. The present paper introduces a novel control strategy based on modified disturbance rejection control, which is a modification of the PID controller that not only preserves the simplicity of control design but also offers an effective control based on state observer-based control law. The proposed control strategy addresses some basic limitations of a PID controller and implements modified control law to remove these limitations. In order to prove the effective control of the proposed control strategy, a standard IEEE-39 bus power system integrated with renewable energy generations is developed, and a comparative analysis of the proposed controller is performed with respect to its ancestor controllers. The comparison is validated based on the system dynamic responses like frequency and tie-line power deviations when the power system is subjected to different disturbances. Furthermore, the power system is integrated with electric vehices (EVs) in vehicle-to-grid (V2G) mode in order to ascertain the effect of EVs when used in V2G mode. A novel study is carried out in which the optimal location of EVs in the power system is determined based on the enhancement in stability of the power system by EVs. The analyses are carried out in MATLAB Simulink software. Simulation reports reflect the optimal control action of the proposed controller with respect to already established strategies projected in the literature. Moreover, the results illustrate that EVs when connected in Area 1 and Area 3 of the power system, the system deviations and steady-state errors are much less as compared to the other cases.

Pumped storage is the main regulating power supply of power system. It is more urgent to build a new power system with new energy as the main body. In order to accelerate the development of pumped storage projects, it is urgent to improve the economic evaluation method of pumped storage projects under the background of new power system construction. Firstly, the value of pumped storage in ensuring the safety and reliability of the new power system, improving the utilization level of renewable energy, and improving the performance of power generation, distribution and consumption of the new power system is analyzed. Then, the economic evaluation model of pumped storage project is optimized, and an index system covering value contribution to the new power system, financial profitability and anti risk ability is constructed. Finally, through the comparative analysis of pumped storage and coal-fired power generation projects, the scientificity and rationality of the model are verified.

In electric power systems, the generated power should be equal with the demand and power of network is mainly controlled through generation system. In such operation, the demand is satisfied through changing the generated power and afterward, the safe operation of power system is reached. But during recent years, a new concept has been developed in electric power systems namely demand side management (DSM). DSM is the modification of consumer demand for energy through various methods such as financial incentives and education. Usually, the goal of demand side management is to encourage the consumer to use less energy during peak hours, or to move the time of energy use to off-peak times such as nighttime and weekends. One of the important models of DSM is interruptible loads. Interruptible loads are the right for an electricity utility to interrupt supply to a customer, typically during a system emergency, to relieve short term network constraints up to a couple of hours. Interruptible loads can be deployed in one of two ways. The network operator gives notice of an interruptible load event to the customer, then relies on the customer to reduce their electricity usage; or unilaterally interrupts supply to the customer. In this paper, the effect of interruptible loads on the power system reliability is investigated. A multi machine power system is considered as cases study. Simulation results show the great effects of interruptible loads on the power system reliability.

Despite the many advantages of renewable energy sources, the stochastic nature of their generation creates a mismatch between the timing of electricity production and demand. Without appropriate storage solutions, surplus energy may remain unused. Therefore, the development of energy complexes based on solar power plants with the integration of battery energy storage systems, as well as the development of corresponding computational models for them, becomes critical for ensuring the stability, flexibility, reliability, and efficiency of power systems. Battery energy storage systems have become widely used due to their availability, high response speed, significant energy density, and sufficient power capacity. However, their cost remains relatively high. This paper proposes a methodology and a calculation model for determining the optimal forecasted capacity and the rational storage requirements of an energy complex consisting of a solar power plant and a battery energy storage system operating in parallel with the grid at constant power under short-term forecasting conditions (day-ahead or longer). The proposed approach makes it possible to minimise the costs of energy companies associated with the short-term lease of part of a battery energy storage system when they do not own one, or, if such a system is available, to lease out its unused capacity and obtain corresponding profits. The validation of the computational model was carried out using a dataset of hourly daily power outputs of solar power plants in the Integrated Power System of Ukraine for 2018. Statistical analysis of the obtained results showed that the probability of occurrence of maximum deviations for the optimal capacity of the energy complex (5.4%), as well as for the power and capacity of the battery energy storage system (13% and 18%, respectively), does not exceed 0.05 during the year. Although the proposed methodology was applied using solar power plant generation data for the national power system as a whole, it can also be used for individual solar power plants located in different regions and countries with different climatic conditions. Certainly, the calculated coefficients will differ, but the methodology itself and the sequence of its application will remain the same.

The proliferation of distributed energy resources (DERs) and the increasing frequency of high-impact events have introduced challenges for the reliability, resilience, and operational flexibility of modern electric power systems. Microgrids have emerged as a promising solution, enabling localized control, seamless transition between grid-connected and islanded modes, and enhanced integration of DERs. This article presents the design, implementation, and operational validation of the Bronzeville Community Microgrid (BCM), a pioneering utility-scale microgrid commissioned by Commonwealth Edison (ComEd) in Chicago, Illinois. The BCM integrates a diverse mix of customer loads and DERs, advanced automation, and a microgrid master controller (MMC) to manage dynamic operating modes and adaptive protection. The article details the technical architecture, control strategies, and functionality validation through hardware-in-the-loop simulations and field tests, demonstrating the BCM’s capabilities for planned islanding, grid reconnection, and clustering with the Illinois Institute of Technology campus microgrid. Lessons learned and strategic opportunities for future microgrid deployments are discussed, highlighting the role of microgrids in advancing resilient, distributed, and intelligent power systems.

MILP formulation for generation and storage asset sizing and sitting for reliability constrained system planning

Guest Editorial: Situational awareness of integrated energy systems