The increasing amount of photovoltaic (PV) systems leads to a voltage rise in the distribution grid. By providing reactive power, PV and battery inverters can reduce the voltage. For this purpose, most inverters have implemented a voltage-dependent reactive power curve, which is often parameterised once during the installation of the system. In most cases, the parameterisation does not take into account the position of the system in the grid. As a result, inverters closer to the distribution transformer provide less or no reactive power as the voltage at the beginning of a feeder is much smaller. This study presents a regulation tool, which parameterises the reactive power curve in dependence on the position in the grid. This leads to a coordinated behaviour of all inverters in a distribution grid and ensures that all inverters provide a similar amount of reactive power. Moreover, the regulation tool notices if the grid topology has changed and adapts the reactive power control to this change.

In future power systems with little system inertia, grid operators will require the provision of synthetic inertia (SI) from renewable energy sources. Unlike today, grid operators may require continuous provision of SI. This can lead to an unwanted disconnection of wind turbine generators (WTGs) from the grid, and has the potential to cause a significant decrease of the energy yield and financial losses for the turbine operator. In order to avoid such situations a controller is proposed, which interprets the grid codes to the benefit of all parties involved. This can be achieved by a variable inertia constant, which changes with the operating point of the WTG. In this study, the behaviour of the variable inertia constant controller is described, assessed and verified with time domain simulations.

This study presents and assesses the outcomes of inertial response tests performed on a transmission system-connected wind power plant in the Canadian province of Quebec. Frequency signals representing a response to a typical loss of generation event were injected into the wind turbines’ control systems to artificially trigger an active power increase. The measurement campaign aimed to fulfil two main objectives. First, to validate the performance of a wind turbine control algorithm designed to optimise the active power behaviour after inertial response activation. Second, to study the correlation between individual wind turbine and wind power plant behaviours during, and immediately after, an inertial response event. This publication offers an update on the capabilities and limitations of type 4 wind turbines for providing inertial response functionalities. Furthermore, it underlines the importance of understanding the various parameters that have an impact on the aggregate inertial response of a wind power plant in reality as well as in dynamic simulations. This publication also addresses how simulations can be used to predict the behaviour of inertial response from wind power plants. Final results suggest that current approaches for integrating and evaluating inertial response from wind power plants in system planning studies should be revisited.

The recent development of a number of advanced wind farm (WF) operation strategies, using designed verification studies, has resulted in various operational and economic improvements. These applications focused on stabilised conditions to confirm the improved effect derived from a maximum power extraction condition. In the case of large-scale WFs, however, a physical area with realistic environmental variations should be considered in order to conduct applicable case studies. In this study, the authors propose a modified reactive power allocation strategy, based on proportional techniques, with the system components of a WF structure for utilisation under a variety of practical situations. The proposed method introduces a modified loss prediction model, which takes the resistive components of the wind turbine into consideration. Each analysis is conducted to confirm the feasibility of active reference assignment in terms of loss reduction and flexibility. The simulations are based on electromagnetic transients using DC software tools to perform electrical loss estimation, in order to verify the effectiveness of this strategy.

A good understanding of forecast errors is imperative for greater penetration of wind power, as it can facilitate planning and operation tasks. Oftentimes, public data is used for system studies without questioning or verifying its origin. In this study, the authors propose a methodology to verify public data with the example of wind power prognosis published by Nord Pool. They focus on Swedish data and identify a significant bias that increases over the forecast horizon. In order to explore the origin of this bias, they first compare against Danish forecast and then describe the underlying structure behind the submission processes of this data. Based on the balance settlement structure, they reveal that Swedish ‘wind power prognoses’ on Nord Pool are in fact rather wind production plans than technical forecasts. They conclude with the recommendation for improved communication and transparency with respect to the terminology of public data on Nord Pool. They stress the importance for the research community to check publicly available input data before further use. Furthermore, the root-mean-square error and the spatio-temporal correlation between the errors in the bidding areas at different horizons are presented. Even with this compromised data, a stronger correlation is identified in neighbouring areas.

The solar power installed capacity all over the world is growing and this renewable energy technology is playing an important role to build a clean energy future. The solar forecast is a necessary tool for the transmission system operator in order to maintain the electricity network safety and reliability. This study aims to report the experience of R&D Nester in the solar forecast at national level in Portugal, forecasting for all solar plants connected to the very high voltage (400, 220 and 150 kV) and high voltage (60 kV) networks, providing this information to the Portuguese transmission system operator, REN. A novel approach to calculate cloud index from images from a sky camera is presented.

Renewable distributed generation and electric vehicles (EVs) are two important components in the transition to a more sustainable society. However, both pose new challenges to the power system due to the intermittent generation and EV charging load. In this case study, a power system consisting of a low- and medium-voltage rural and urban distribution grid with 5174 customers, high penetration of photovoltaic (PV) electricity and a fully electrified car fleet were assumed, and their impact on the grid was assessed. The two extreme cases of two summer weeks and two winter weeks with and without EV charging and a PV penetration varying between 0 and 100% of the annual electricity consumption were examined. Active power curtailment of the PV systems was used to avoid overvoltage. The results show an increased electricity consumption of 9.3% in the winter weeks and 17.1% in the summer weeks, a lowering of the minimum voltage by 1% at the most, and a marginal contribution by the EV charging to lower the need of PV power curtailment. This shows the minor impact of EV charging on the distribution grid, both in terms of allowing more PV power generation and in terms of lower voltage levels.

This study presents the impact of wind power plant components modelling on harmonics propagation and harmonic small-signal stability studies. Different types of cable and transformer modelling techniques are taken into consideration, e.g. state-of-the-art standard models and latest academic developments. The models are compared based on system-level studies in a real-life large offshore wind power plant. It is shown that the use of detailed cable and transformer models increases the overall damping estimation in the system, and therefore improves the resonance characteristics and small-signal stability margins of the investigated wind power plant.

This study endeavours an effective frequency control of renewable-based isolated two-area interconnected microgrid (ICμG) without battery, incorporating wind power generation in area-1, dish-Stirling solar power generation system in area-2 and other common distributed generation systems such as diesel engine driven generator, plug-in hybrid electric vehicle, heat pump and freezer in both the areas. A recently developed heuristic optimisation technique called water cycle algorithm (WCA) is applied to optimally tune the parameters of the non-integer fractional-order proportional-integral-derivative (FOPID) controllers employed with ICμG. Application of WCA-based FOPID controllers in frequency control two-area ICμG without battery is a novel work. The comparative performance analysis of proportional-integral-derivative (PID), PID with filter and non-integer order-based FOPID controller with their gains tuned by particle swarm optimisation (PSO), improved PSO, firefly algorithm and WCA algorithms indicates the superiority of WCA-based FOPID controller's under different case studies (considering different load disturbances, wind speed variation with real data, and solar irradiance) in terms of frequency deviation, tie-line power, and objective function. Furthermore, the sensitivity analysis contemplates that WCA-optimised FOPID controller can withstand ±25% change in synchronising coefficient, +20% change in loading condition and ±25% change in frequency bias constant without resetting the gain values.

In Brazil, specify in isolated areas, the connection to the conventional electric energy distribution grid becomes restrictied due to financial and geographical factors. Then the main option for supplying the energy demand is fossil fuel driven thermal systems. With the purpose of providing an alternative option for power generation, this study presents an analysis of biomass-based energy systems for isolated communities, in special Bonfim city, in Roraima state. The technologies applied were conventional Rankine cycle, organic Rankine cycle (ORC) and gasification system with an internal combustion engine. All systems are operated with agricultural wastes (rice straw and rice husk). The modelled systems produced electricity with a conversion efficiency of 10.78, 17.78 and 14% for ORC, conventional Rankine cycle and gasification systems, respectively. With these results and with a production of 35,667 tons of waste per year, the systems can supply the energetic demand of Bonfim city (536.40 kW). With relation to costs, currently the generation costs in isolated communities of Bonfim city are in a range of 390.31–475.85 US$/MWh. The proposed cases have a generation costs of 197.11 US$/MWh (conventional Rankine cycle), 324.77 US$/MWh (ORC) and 336.49 US$/MWh (gasification system).

The effects of blockage ratio and boundary proximity on tidal turbine performance are quantified in this study using computational fluid dynamics (CFD). Reynold averaged Navier–Stokes (RANS) equations are solved using the commercial CFD code ANSYS CFX. Steady-state analyses are performed using a rotating frame of reference technique, and a shear stress transport turbulence model is used. Results from the numerical model are validated with experimental data. RANS CFD simulations are performed over tip speed ratios (TSRs) from 1 to 9. The simulation-based performance curve approximately match the experimental performance curve, with errors ranging from 4 to 9%. Blockage ratios from 0.02 to 0.19 are evaluated for a constant depth of two rotor diameters to study the effect of blockage on turbine performance. Results show that shaft power increased by 13 and 47% for TSRs of 5.11 and 9.05, respectively, when the blockage ratio increased from 0.02 to 0.19. Additionally, for these TSRs and blockage ratios the turbine thrust increased by 7 and 10%. The presence of a boundary layer resulted in a calculated thrust increases between 1.6 and 2.3% and power between 2.7 and 3.5% for the entire range of evaluated blockage ratios.

Despite higher winds, the investment and operation and maintenance costs of offshore wind farms are still high as compared to onshore solutions. This highlights the importance of an increased reliability, because the occurrence of a failure can result in long downtimes due to inaccessibility of the site during harsh weather conditions. This study performs a reliability analysis of the internal grid of an offshore wind farm, comparing different topologies and their economic outcome. The research addresses both a redundancy between each pair of two strings (classical redundancy design) and a redundancy between already redundantly paired sets of strings (newly proposed redundancy design). The results show that the use of a redundancy scheme leads to a positive Net Present Value (NPV) and an interesting Internal Rate of Return (IRR), which can be an appealing investment. Moreover, it is more profitable to simply rate the cables to support normal operation conditions at rated power rather than increasing the cable ratings to support all failure scenarios. Overall, the topology that shows the best economic results combined with a good reliability is the topology with cable ratings based on regular conditions with a redundancy in the middle of the string between each pair of two strings.

Extension of renewable energies in power system planning and operation especially distribution networks is not limited to power sustainability. It also encompasses many significant contributions such as eliminating electricity shortages by diversifying energy supply, improving reliability with power quality, reducing greenhouse gas emissions, and providing energy independence, which is the most crucial aspect for both developed and developing countries power sector. The extraction of such benefits in the best manner can be achieved by considering storage and control devices, aiding well-configured electricity networks through competitive optimisation techniques. By taking such points into consideration, optimal multi-configuration and allocation of step-voltage regulators (SVRs), capacitor banks, and energy storage system along with centralised wind-power generation integrating to distribution network are investigated and applied, using a novel and Pareto based epsilon multi-objective genetic algorithm. The proposed methodology is applied to an extensive and real 162-bus distribution network in Kabul city to validate its sturdiness. The simulations are performed in MATLAB^® environment with six configuration scenarios to compare the effect of multiple arrangements in the distribution network, and to discover the best configuration fulfilling the optimisation criteria with the objective functions being as power loss, voltage deviation, and violation cost.

Renewable power generation combined with energy storage (ES) is expected to bring enormous economical and environmental benefits to the future smart grid. However, the ES management in smart grid is facing significant technical challenges due to the volatile nature of renewable energy sources and the buffering effect of ES units. The challenges are further complicated by the increasing size and complexity of the system, as well as the consideration of random usage patterns of electrical appliances by customers. To address these challenges, this study proposes a parallel decomposition method for large-scale stochastic programming in a distribution system with renewable energy sources and ES units. By leveraging nested decomposition, the problem can be converted into independent sub-problems with a series of time periods. In addition, the reformulated problem is fully parallel for speed up in execution. The performance of the proposed method is evaluated based on the IEEE 4-bus and 33-bus test distribution systems with real photovoltaic generation and electrical appliance usage data. The case study demonstrates that the proposed scheme can substantially reduce the system operation cost, with low computational complexity.

Operation of microgrids in islanded mode either by intention or by involuntary action is of increasing concern nowadays. Optimal operation and control of such islanded microgrids considering various objectives are crucial for effective planning problem. This work proposes a new methodology for optimal operation of islanded microgrids considering economic and emission objectives together with loadability in droop-regulated islanded microgrid. Loadability being one of dominant aspects to be considered for effective microgrid planning and operation to ensure increased voltage-stability margin in the entire due course of operation. In conjunction with that islanded microgrid operational constraints and uncertainty in various system parameters need to be considered to interpret real-time operation of the microgrid. In the light of above, a multi-objective optimisation problem in droop-regulated islanded microgrid is formulated with economic–emission–loadability objectives by considering uncertainties in load demand and renewable generation along with system constraints. The formulated problem is solved using multi-objective antlion optimiser algorithm and validated on the test system. The performance of the proposed approach is compared with other optimisation algorithms to show its effectiveness. The importance of considering loadability along with economic–emission objectives to achieve compromised solution resulted in ensuring better operational planning of droop-regulated islanded microgrids.