• Energy Research

Voltage dip immunity of converter-connected distributed generation units will become increasingly important. This paper focusses on the relation between the voltage-dip ride-through capability of converters and their current-control strategy. A comparison is made between a recently proposed control strategy with programmable damping resistance and the classical sinewave control algorithm. The first-mentioned control structure will prove to yield an improved voltage dip immunity. Experimental tests on a single-phase full-bridge bidirectional converter are carried out and validate the aforementioned postulations.

Integrating offshore renewable energy (ORE) into power systems is vital for sustainable energy transitions. This paper examines the challenges and opportunities in integrating ORE, focusing on offshore wind and floating solar, into grid systems. A simulation was conducted using a 5 MW offshore wind turbine and a 2 MW floating PV (FPV) system, complemented by a 10 MWh battery energy storage system (BESS). The simulation utilized the typical load profile of Belgium and actual 2023 electricity price data, along with realistic wind and solar generation patterns for a location at the sea border of Belgium and the Netherlands. The use of real operational and market data ensures the practical relevance of the results. This study highlights the importance of BESS, targeting a significant revenue by participating in system imbalance and providing ancillary services (aFRR and mFRR). Key findings emphasize the need for grid infrastructure transformation to support ORE’s growing investments and deployment. This research underscores the essential role of technological innovation and strategic planning in optimizing the potential of ORE sources.

The current energy transition and the underlying growth in variable and uncertain renewable-based energy generation challenge the proper operation of power systems. Classical probabilistic uncertainty models, e.g., stochastic programming or robust optimisation, have been used widely to solve problems such as the day-ahead energy and reserve dispatch problem to enhance the day-ahead decisions with a probabilistic insight of renewable energy generation in real-time. By doing so, the scheduling of the power system becomes, production and consumption of electric power, more reliable (i.e., more robust because of potential deviations) while minimising the social costs given potential balancing actions. Nevertheless, these classical models are not valid when the uncertainty is imprecise, meaning that the system operator may not rely on a unique distribution function to describe the uncertainty. Given the Distributionally Robust Optimisation method, our approach can be implemented for any non-probabilistic, e.g., interval models rather than only sets of distribution functions (ambiguity set of probability distributions). In this paper, the aim is to apply two advanced non-probabilistic uncertainty models: Interval and ϵ-contamination, where the imprecision and in-determinism in the uncertainty (uncertain parameters) are considered. We propose two kinds of theoretical solutions under two decision criteria—Maximinity and Maximality. For an illustration of our solutions, we apply our proposed approach to a case study inspired by the 24-node IEEE reliability test system.

The objective of this study is minimizing the frequency deviation due to the load variations and fluctuations of renewable energy resources. In this paper, a new type-2 fuzzy control (T2FLC) approach is presented for load frequency control (LFC) in power systems with multi-areas, demand response (DR), battery energy storage system (BESS), and wind farms. BESS is used to reduce the frequency deviations caused by wind energy, and DR is utilized to increase network stability due to fast load changes. The suggested T2FLC is online tuned based on the extended Kalman filter to improve the LFC accuracy in coordination of DR, BESS, and wind farms. The system dynamics are unknown, and the system Jacobian is extracted by online modeling with a simple multilayer perceptron neural network (MLP-NN). The designed LFC is evaluated through simulating on 10-machine New England 39-bus test system (NETS-39b) in four scenarios. Simulation results verifies the desired performance, indicating its superiority compared to a classical PI controllers, and type-1 fuzzy logic controllers (FLCs). The mean of improvement percentage is about 20%.

In this research, the performance of vanadium redox flow batteries (VRFBs) in grid-connected energy storage systems centering on frequency and power sharing using voltage source inverters was evaluated. VRFBs are increasingly promising due to their scalability and long lifespan. We explore the impact of voltage source inverters on the frequency of the power supply when there is a change in load and power sharing between the grid and VRFB through MATLAB simulations. The test system demonstrates a storage system at an 11-kV substation and considers a load profile commencing from residential and commercial consumers. The outcome of this study reveals that VRFBs provide the required power to maintain load demand. Due to fast response time, VRFBs also regulate the frequency efficiently during the change in load demand and maintaining current total harmonic distortions (THDs). This research confirms the design and operation of VRFB-based energy storage systems, contributing to resilient grid infrastructure and reliable power distribution systems.

This article provides an agent-based model of a hypothetical standalone electricity network to identify how the feed-in tariffs and the installed capacity of wind power, calculated in percentage of total system demand, affect the electricity consumption from renewables. It includes the mechanism of electricity pricing on the Day Ahead Market (DAM) and the Imbalance Market (IM). The extra production volumes of Electricity from Renewable Energy Sources (RES-E) and the flexibility of electrical consumption of industries is provided as reserves on the IM. Five thousand simulations were run by using the agent-based model to gather data that were then fit in linear regression models. This helped to quantify the effect of feed-in tariffs and installed capacity of wind power on the consumption from renewable energy and market prices. The consumption from renewable sources, expressed as percentage of total system consumption, increased by 8.17% for every 10% increase in installed capacity of wind power. The sharpest increase in renewable energy consumption is observed when a feed-in tariff of 0.04 €/kWh is provided to the wind farm owners, resulting in an average increase of 9.1% and 5.1% in the consumption from renewable sources while the maximum installed capacity of wind power is 35% and 100%, respectively. The regression model for the annualized DAM prices showed an increase by 0.01 €cents/kWh in the DAM prices for every 10% increase in the installed wind power capacity. With every increase of 0.01 €/kWh in the value of feed-in tariffs, the mean DAM price is lowered as compared to the previous value of the feed-in tariff. DAM prices only decrease with increasing installed wind capacity when a feed-in tariff of 0.04 €/kWh is provided. This is observed because all wind power being traded on DAM at a very cheap price. Hence, no volume of electricity is being stored for availability on IM. The regression models for predicting IM prices show that, with every 10% increase in installed capacity of wind power, the annualized IM price decreases by 0.031 and 0.34 €cents/kWh, when installed capacity of wind power is between 0 and 25%, and between 25 and 100%, respectively. The models also showed that, until the maximum installed capacity of wind power is less than 25%, the IM prices increase when the value of feed-in tariff is 0.01 and 0.04 €/kWh, but decrease for a feed-in tariff of 0.02 and 0.03 €/kWh. When installed capacity of wind power is between 25 and 100%, increasing feed-in tariffs to the value of 0.03 €/kWh result in lowering the mean IM price. However, at 0.04 €/kWh, the mean IM price is higher, showing the effect of no storage reserves being available on IM and more expensive reserves being engaged on the IM. The study concludes that the effect of increasing installed capacity of wind power is more significant on increasing consumption of renewable energy and decreasing the DAM and IM prices than the effect of feed-in tariffs. However, the effect of increasing values of both factors on the profit of RES-E producers with storage facilities is not positive, pointing to the need for customized rules and incentives to encourage their market participation and investment in storage facilities.

The global wind power capacity is on a constant rise. Many countries are moving towards renewable energy sources. Wind energy accounts for the biggest renewable energy resource in Europe. Despite all the benefits, wind energy tends to weaken the grid stability. One reason for this is the fact that most wind turbine generators are not directly coupled to the grid and do not provide ancillary services, such as primary frequency control, due to the lack of rotating inertia. This paper presents detailed models of a wind turbine with a permanent magnet synchronous generator (PMSG). This model is used to test the feasibility of providing ancillary services by performing the pre-qualification test for primary frequency control, as established by the Belgian Transmission System Operator (TSO). These tests are conducted under 4 different wind profiles, each having a different level of turbulence.