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This article proposes a DR program characterized by a novel compensation scheme. The proposed scheme recognizes the different characteristics of curtailment, such as the total length of curtailments within a window of time, or the number of separate curtailment events (i.e., curtailment startup), and compensates the end-user accordingly. The proposed compensation scheme features a piece-wise reward function comprised of two intervals. DR participants receive a onetime reward upfront when they enroll in the DR program and accept a set of predefined curtailment aspects. Curtailment aspects in excess of the agreed quantities are rewarded at a linear rate. This design is tailored to appeal to residential DR participants, and aims to secure sufficient flexibility at minimum cost. The parameters of the smart contract are optimized such that the system’s social welfare is maximized. The optimization problem is modeled as a mixed-integer linear program. Consequently, this article updates the unit-commitment (UC) formulation with the commitment aspects of DR units. The proposed extension to the UC problem considers the critical aspects of DR participation, such as: the total length of interruptions within a window, the frequency of interruptions within a time-window irrespective of their length, and the net energy deviation from the original load profile. Deployment of the smart DR contract in the unit dispatch problem requires translating DR participants’ characteristics to their equivalent aspects in conventional thermal generators, such as minimum up time, minimum down-time, start-up and shutdown costs. The obtained results demonstrate significant improvement in social welfare, notable reduction of curtailed renewable energy and reduction in extreme ramping events of conventional generators. [ABSTRACT FROM AUTHOR]

Deferrable power-driven demands such as water and thermal ones possess a capability of energy storage which can be exploited to further optimize electric systems. This paper proposes a new optimized scheduling framework for electric grids by simultaneously exploiting the high-inertia thermal dynamics and lossless water storage. Unlike previous ideas in the literature, both water and thermal demands are managed to realize the long-term and short-term load-shifting strategies, respectively. First, distributed water/thermal loads are aggregated where the virtual storage can be represented by battery models. Then, a further optimized scheduling framework is proposed with a mixed-integer nonlinear programing problem. Comparative studies show that the water storage offers outstanding flexibility for electric system via pumps scheduling, especially for the electric load-shifting strategy in a long time-horizon thanks to the lossless water-storage process. Meanwhile, the thermal storage can directly support short-term electric load-shifting to avoid price spikes of electricity. Numerical results show that the proposed method can reduce the total cost of micro-grids by maximizing the usage of renewable energy sources, avoiding price spikes, and reducing dependence on high-cost centralized energy-storage facilities provided that the critical water-energy demands are preserved. [ABSTRACT FROM AUTHOR]

The standard alternative-arm converters (AAC) with the sweet spot or short overlap operation have faced a challenge of balancing submodule (SM) capacitor voltages, where this issue has not been paid much attention so far. In this paper, a new control strategy for the SM-capacitor voltage balancing of the AAC applied in high-voltage dc transmission systems is proposed. The suggested control technique is composed of three regulators, where a control for the average voltage of all SM capacitors, the voltage balancing among the converter arms, and the voltage balancing of the individual SM capacitor are performed. Based on the operation principle of the standard AAC, which activates only three of six converter arms simultaneously, the energy balancing of the three activated arms is performed every one sixth of the fundamental cycle by the converter common offset voltage. Band-stop filters with the central frequencies at the fundamental, second-, and third-order components of the line frequency are applied to obtain the average values of the SM capacitor voltages for the feedback controllers. The simple proportional and integral controllers are employed for this scheme and the voltages of SM capacitors are mostly balanced during the steady states and kept closely to the rating with overshoot of less than 7% under the transient conditions. The proposed control method is verified by simulation results for a 33-level AAC under both normal and fault conditions. [ABSTRACT FROM AUTHOR]

The article focuses on the HVDC technology (high voltage direct current) is used to transmit electricity over long distances by overhead transmission lines or submarine cables. It mentions HVDC allows power transmission between unsynchronized AC transmission systems; and most HVDC links use voltages between 100 kV and 800 kV. A 1,100 kV link in China was completed in 2019 over a distance of 3,300 km with a power of 12 GW.

Power generation from renewable energy resources is on the increase in most countries, and this trend is expected to continue in the foreseeable future. In an effort to enhance the integration of renewable power generation from solar and wind into the traditional power network, there is need to address the vulnerabilities posed to the grid as a result of the intermittent nature of these resources. Variability and ramp events in power output are the key challenges to the system operators due to their impact on system balancing, reserves management, scheduling and commitment of generating units. This has drawn the interest of utilities and researchers towards developing state of the art forecasting techniques for forecasting wind speeds and solar irradiance over a wide range of temporal and spatial horizons. The main forecasting approaches employ physical, statistical, artificial intelligence and hybrid methodologies. This study provides the rationale for forecasting in power systems, a succinct review of forecasting techniques as well as an assessment of their performance as applied in the literature. Also, techniques for improving the accuracy of forecasts have been presented together with key forecasting issues and developing trends. [ABSTRACT FROM AUTHOR]

Hybrid micro‐grids are one of the most viable solutions to the present day problem of integration of renewable energy into existing power systems. With various options available for implementation of hybrid micro‐grids, the stability of such systems has to be ensured before they can be implemented. Further, conventional micro‐grid operational studies do not take into consideration the constraints set by the grid codes. This study analyses three types of interconnections, possible for implementation of hybrid micro‐grids, taking into consideration the transient stability and grid code constraints. The hybrid micro‐grid considered comprises a synchronous diesel generator and an inverter‐based distributed generation. The results and analysis are conducted by time‐domain simulations using MATLAB/Simulink software. The results provide the actual operational limits of possible micro‐grid interconnections under the set of given constraints. [ABSTRACT FROM AUTHOR]

Fossil fuel power plants continue to contribute significantly to carbon emissions, necessitating a transition towards cleaner energy sources. Despite the growing presence of renewables within the power systems, the incorporation of carbon capture technologies into the traditional thermal power plants holds great potential in emissions reduction. In this paper, the integration of renewable energy sources (RES) and coal-fired power generation units outfitted with carbon capture schemes is addressed. Multiple demand response (DR) programs and hydropower plants are strategically utilized to increase the power system flexibility. To effectively plan the day-ahead (DA) operation of the power system, a presumed market-clearing framework is adopted and modelled as a risk-constrained two-objective stochastic mixed-integer linear programming problem. The proposed framework helps to tackle the uncertainties related to RES and demand variations by employing a hidden Markovian process (HMP) technique. To simultaneously minimize the system's operational costs and CO 2 emissions, an enhanced version of the augmented ɛ -constraint method is employed. To prove its value, the proposed framework is devoted to the 24-bus IEEE reliability test system (IEEE-RTS). The system features substantial penetration of RES (exceeding 87% of peak load) and standard DR options capacities (less than 25% of peak load). The results show a 24% reduction in load peaks, an over 63% decrease in emissions, and a 17% reduction in the overall operation costs. • Proposing a comprehensive linearized mathematical framework accelerating the energy transition. • Coordinating the responsive power systems with carbon capture and hybrid ESS (BESS, PHS, HES). • Enhancing an effective augmented ɛ -constraint technique to simultaneously optimize cost and CO 2. • Presenting robust decision-making with two-stage SP, hidden Markovian process, and CVaR strategy. • Integrated approach: 87% of RES, cost & CO 2 reductions, fewer load peaks, enhanced flexibility. [ABSTRACT FROM AUTHOR]

Integrating renewable energy resources (RES) is a challenge for power system operators due to their fluctuations and unpredictability. At the same time, the water shortage problem and the needs to desalinate more freshwater increase the prominence of sufficient energy resources for sustainable operation. Therefore, this paper presents a market-clearing mechanism in a co-optimization model that coordinates the operation of grid-connected reverse osmosis water desalination plants (RO-WDPs) and the operation of renewable-rich power systems. It is assumed that electric demands can participate in the provision of demand response (DR) to the market via multiple DR options. The DR options related to the general loads are demand shifting, load curtailment, distributed generation, and hybrid energy storage systems (HESS). These HESS includes battery storage and hydrogen storage systems. Pertaining to their special characteristics, a new DR option is proposed as a customized option for RO-WDPs. The market clearing mechanism is assumed to be based on the security-constrained unit commitment (SCUC) and formulated as a stochastic mixed-integer linear programming problem (MILP) to optimally schedule the day-ahead operation of the power system. The presented model is applied on 6-bus and IEEE 24-bus reliability test system (RTS) test power systems with significant penetration of RES to demonstrate its merits. The simulation results show that the system efficiency is enhanced by adding the energy flexibility of RO-WDP without endangering the water demand-supply when using the proposed coordinated model. Hence, the total operation cost is minimized, the RES integration is facilitated, and the hourly electricity prices are smoothened. • We propose coordination model of grid-connected RO desalination and responsive power system. • The power system in our model considers five DR options including hybrid ESS. • We avoid the generic DR model to reschedule the RO desalination flexibility. • The day-ahead operation of our energy–water nexus incorporates system uncertainties. • The incorporated approach minimizes cost and CO2 and enhances the system flexibility. [ABSTRACT FROM AUTHOR]

The increased penetration levels of renewable energy resources (RESs) transform the power generation schema into one that is more susceptible to changes due to weather conditions, complicated load profiles, and reduced inertia levels. One of the main challenges that power grids can encounter under varying and low system inertia (SI) is poor frequency response (FR). Therefore, this paper proposes a novel online tool for assessing, predicting, and enhancing the frequency stability (FS) of power systems with renewable power generation and energy storage systems (ESS). Firstly, the tool provides accurate tracking of the SI in real-time settings using recursive least square identification and Kalman filtering to provide accurate and computationally efficient results. Secondly, the tool estimates the FR of the whole system in a virtual environment for different contingencies and inertia levels. The accuracy of the FR is improved by classifying the frequency response models (FRMs) based on the SI levels. Lastly, the proposed tool computes the optimal additional estimated reserve power (ERP) required from PV and battery energy storage systems (BESS) to provide inertial and primary frequency support to the power grid at the onset of a contingency. In addition, a reserve power allocation and load-shedding strategies are proposed and implemented to dynamically adjust the reserve power of PV power plants. This dynamic control of the PV power plant reserve capacity guarantees the availability of adequate reserves for addressing unforeseen systems contingencies. Moreover, dedicated FR controllers for PV and BESS are employed to emulate the synchronous machine's inertial response (IR) and primary frequency control (PFC). The performance of the proposed tool and the FR controllers are tested and validated on a generic power grid and the IEEE 39 bus system using MATLAB Simulink and the OPAL-RT real-time simulation software. • Power system inertia estimation in a real-time environment with minimum data. • Frequency nadir estimation using multi-regressed models based on the system inertia. • Estimation of optimal reserve power for PV and BESS for frequency stability. • Dynamic adjustment of PV sub-optimal operation. • Frequency response controllers for PV and BESS, and optimal load shedding strategy. [ABSTRACT FROM AUTHOR]