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A microgrid (MG) is always prone to the uncertainties of its demand variation and the generation of its non-dispatchable renewable sources when operating in islanded mode. Such variation events can lead to the voltage or frequency (VF) violation in the MG. However, there are some techniques available in the literature that can predict these events a few minutes ahead. Using such techniques, the VF violation can also be predicted and prevented with the introduction of a suitable preventive controller. Hence, this paper proposes a look-ahead controller that uses the short-horizon prediction data of demand and renewable generation to determine any prospective VF violation. If a violation is predicted, the proposed technique will aim to define the most optimal generation level of dispatchable sources, the MG's best network configuration and the engagement level of the supportive actions, such as exchanging power with neighboring microgrids, utilizing energy storages, a demand response and renewable energy curtailment (if and when available). The technical, reliability and environmental aspects of the MG are considered within the proposed technique along with the operational cost. The determined optimal control variables are then sent to the local controllers to apply the proper arrangements in the system to retain the VF within the desired range. The performance of the developed technique is validated through extensive numerical analyses in MATLAB. [ABSTRACT FROM AUTHOR]

To address the challenges of integrating ever-increasing renewable energy generation such as wind power and photovoltaic (PV) to the power system concerned, the wind-PV-thermal-bundled (WPTB) transmission mode could be employed to mitigate the intermittent power output from wind and PV units. In this work, based on the mathematical models of thermal generation units, wind turbines and PV units, the WPTB transmission system model is developed. Each load demand is modeled as a random variable under various operating conditions of the concerned power system. The Lyapunov linearization method is used to obtain the system matrix of each operation mode, and then all eigenvalues of the system can be attained. According to the generator participation factor, the oscillation modes of the power system are classified. The eigenvalue and damping ratio of each oscillation mode are employed to formulate the objective function of the optimal strategy for enhancing probabilistic small-signal stability, and the particle swarm optimization algorithm is used for global optimization. The secure operation of the power system can be ensured in a wider range by the designed optimization strategy in this work. The effectiveness of the method is demonstrated by simulation results of a sample power system which can operate stably under some uncertain operation conditions. [ABSTRACT FROM AUTHOR]

With the target of carbon peaking and carbon neutrality, renewable energy generation (REG) develops rapidly. The increasing penetration of REG brings along the problems of fluctuation in power flow and the possible abandonment of wind and photovoltaics (PV) generation. In this context, the so-called integrated energy system (IES) becomes a promising solution to the accommodation of REG thanks to energy storage systems and coupling devices inside. In this paper, the optimal operation model of an IES is first presented, with the schemes of green certificate trading and carbon emission right trading included to provide economic incentives for accommodating REG. Next, in order to address the problem of uncertainty in REG, the devices in the IES are divided into three types based on regulation flexibility, and a multi-time period optimal dispatching scheme is proposed, including day-ahead optimal scheduling, rolling optimal dispatching, and real-time control strategy. Finally, it is demonstrated by simulation results of a numerical example that the proposed method not only promotes the accommodation capability for REG but can also cope well with contingencies. [ABSTRACT FROM AUTHOR]

Bidirectional power flow is becoming increasingly commonplace in modern distribution systems with the integration Renewable Energy Sources (RESs) and Energy Storage Systems (ESSs). This has facilitated in bringing generation closer to end‐consumers, thus leading to the emergence and rapid growth of microgrids. Additionally, due to the technological revolution in Information and Communications Technology (ICT), innovative business models have developed where willing and able participants of the power system can participate in the electricity market. In line with this evolution of both the electric power system and its participants, Energy‐as‐a‐Service (EaaS) is emerging as an increasingly prominent business model to address electrical grid challenges economically. EaaS encourages electricity grid customers to play a more active role and participate in different electricity markets. This paper introduces and simulates a variant of a Transactive Energy (TE) trading algorithm for microgrids. The paper describes the model in brief how multiple microgrids assets can trade electricity to ensure more efficient and economical local resource utilization. The main motivations of this research paper is to validate and test the suitability of the TE trading algorithm for a variety of conditions. The coordinated TE trading model can optimize expansion and investment planning especially at the distribution level. [ABSTRACT FROM AUTHOR]

The global resurgence of hydrogen as a clean energy source, particularly green hydrogen derived from renewable energy, is pivotal for achieving a carbon-neutral future. However, scalability poses a significant challenge. This research proposes innovative business models leveraging the low-emission property of green hydrogen to reduce its financial costs, thereby fostering its widespread adoption. Key components of the business workflow are elaborated, mathematical formulations of market parameters are derived, and case studies are presented to demonstrate the feasibility and efficiency of these models. Results demonstrate that the substantial costs associated with the current hydrogen industry can be effectively subsidized via the implementation of proposed business models. When the carbon emission price falls within the range of approximately 86–105 USD/ton, free access to hydrogen becomes a viable option for end-users. This highlights the significance and promising potential of the proposed business models within the green hydrogen credit framework. • Business models for trading green hydrogen credits are designed the first time. • It provides innovative financial solutions to decrease the cost of green hydrogen. • Incentives of utilizing green hydrogen are created using proposed business models. • The adoption of proposed trading framework can stimulate global hydrogen economy. • This work accelerates the progress towards a carbon-neutral future. [ABSTRACT FROM AUTHOR]