Remote Wind Farms Research Articles

A Semi-Markov Stochastic Model for Operational Reliability Assessment of Hybrid AC and LCC-VSC-Based DC System With Remote Wind Farms

A Semi-Markov Stochastic Model for Operational Reliability Assessment of Hybrid AC and LCC-VSC-Based DC System With Remote Wind Farms

Dynamic stability reinforcement in remote wind farm connections: POD-SSSC coordination with fuzzy logic control using RTDS

Dynamic stability reinforcement in remote wind farm connections: POD-SSSC coordination with fuzzy logic control using RTDS

Remote Wind Farm Path Planning for Patrol Robot Based on the Hybrid Optimization Algorithm

Globally, wind power plays a leading role in the renewable energy industry. In order to ensure the normal operation of a wind farm, the staff will regularly check the equipment of the wind farm. However, manual inspection has some disadvantages, such as heavy workload, low efficiency and easy misjudgment. In order to realize automation, intelligence and high efficiency of inspection work, inspection robots are introduced into wind farms to replace manual inspections. Path planning is the prerequisite for an intelligent inspection robot to complete inspection tasks. In order to ensure that the robot can take the shortest path in the inspection process and avoid the detected obstacles at the same time, a new path-planning algorithm is proposed. The path-planning algorithm is based on the chaotic neural network and genetic algorithm. First, the chaotic neural network is used for the first step of path planning. The planning results are encoded into chromosomes to replace the individuals with the worst fitness in the genetic algorithm population. Then, according to the principle of survival of the fittest, the population is selected, hybridized, varied and guided to cyclic evolution to obtain the new path. The shortest path obtained by the algorithm can be used for the robot inspection of the wind farms in remote areas. The results show that the proposed new algorithm can generate a shorter inspection path than other algorithms.

Optimal joint maintenance and orienteering strategy for complex mission-oriented systems: A case study in offshore wind energy

This paper introduces and solves the joint maintenance and orienteering problem with an application to offshore wind farms. The quest for sustainable energy production is fueling the growth of offshore wind electricity generation. Energy producing offshore wind turbines are typically dispersed across several remote wind farms and must be maintained and operated with high reliability levels for long time-periods separated by scheduled maintenance rotations. Due to resource constraints such as travel time, cost, and availability of repair crews, only a subset of turbines and their components can be selected for maintenance operations during maintenance trips. This paper proposes a novel joint maintenance and orienteering framework to address the selection of turbines to visit, the components to maintain, the maintenance levels to be performed, the assignment of repair crews, and their routing with the goal of minimizing total cost while satisfying a minimum required reliability threshold during the next operating mission until the next maintenance rotation. A mixed-integer linear programming optimization model is developed and fully discussed. To solve the problem for large-scale instances, a column generation method based on Dantzig–Wolfe decomposition and labeling algorithm is proposed. Several numerical experiments demonstrate the validity of the proposed model and the benefit of jointly optimizing maintenance and orienteering decisions. The results show that inclusion of detailed reliability and multiple maintenance levels allows better maintenance and routing decisions. Numerical results also show trade-offs between reliability requirement, shift duration and total cost.

Automated Scheduling Approach under Smart Contract for Remote Wind Farms with Power-to-Gas Systems in Multiple Energy Markets

The promising power-to-gas (P2G) technology makes it possible for wind farms to absorb carbon and trade in multiple energy markets. Considering the remoteness of wind farms equipped with P2G systems and the isolation of different energy markets, the scheduling process may suffer from inefficient coordination and unstable information. An automated scheduling approach is thus proposed. Firstly, an automated scheduling framework enabled by smart contract is established for reliable coordination between wind farms and multiple energy markets. Considering the limited logic complexity and insufficient calculation of smart contracts, an off-chain procedure as a workaround is proposed to avoid complex on-chain solutions. Next, a non-linear model of the P2G system is developed to enhance the accuracy of scheduling results. The scheduling strategy takes into account not only the revenues from multiple energy trades, but also the penalties for violating contract items in smart contracts. Then, the implementation of smart contracts under a blockchain environment is presented with multiple participants, including voting in an agreed scheduling result as the plan. Finally, the case study is conducted in a typical two-stage scheduling process—i.e., day-ahead and real-time scheduling—and the results verify the efficiency of the proposed approach.

Convolutional Neural Network for Wind Turbine Failure Classification Based on SCADA Data

As a renewable energy source and an alternative to fossil fuels, the wind power industry is growing rapidly. However, due to harsh weather conditions, wind turbines (WT) still face many failures that raise the price of energy produced and reduce the reliability of wind energy. Hence, the use of reliable monitoring and diagnostic systems of WTs is of great importance. Operation and maintenance expenses represent 30% of the total cost of large wind farms. The installation of offshore and remote wind farms has increased the need for efficient fault detection and condition monitoring systems. In this work, without using specific custom devices for monitoring conditions, but only increasing the sampling frequency in the sensors already available (in all commercial WT) of the supervisory control and data acquisition system (SCADA), datadriven multiple fault detection is performed, and a classification strategy is developed. The data is processed, and subsequently, using a convolutional neural network (CNN), six faults are classified and evaluated with different metrics. Finally, it should be noted that the classification speed allows the implementation of this strategy to monitor conditions online in real under-production WTs.

Enhancing wind power transfer and protection of actual Egyptian 220 kV HVAC transmission system with multi-terminal VSC-HVDC system

Transmitting power using high-voltage direct current (HVDC) systems instead of high-voltage alternating current (HVAC) ones becomes desirable for integrating remote wind farms. Nowadays, Egypt planned to increase the wind power generation in the Red Sea zone from 1400 to 4000 MW by 2022. Unfortunately, the full capacity of the existing 220 kV HVAC transmission line connecting the current wind farms with the main grid is 1500 MW only. This paper aims first to pinpoint the challenges and drawbacks of the existing AC system, including limited capacity, and service quality. Then, it provides a comprehensive, technical and economic evaluation study of upgrading the existing 220 kV HVAC transmission system to a ± 160 kV HVDC system as compared with expanding the existed system to a conventional 500 kV HVAC transmission line. Finally, a thorough investigation study is presented for the proposed multi-terminal HVDC line in conjunction with its modified protection scheme based on a detailed simulation in MATLAB. Based on a variety of fault cases, an assessment of the performance and suitability of the proposed solutions is visualized. The results ensure the ability of the proposed HVDC system to be a suitable solution for integrating the wind farms in Egypt.

Analyzing and Quantifying the Intrinsic Distributional Robustness of CVaR Reformulation for Chance-Constrained Stochastic Programs

Chance-constrained program (CCP) is a popular stochastic optimization method in power system planning, and operation problems. Conditional Value-at-Risk (CVaR) provides a convex approximation for chance constraints which are nonconvex. Although CCP assumes an exact empirical distribution, and the optimum of a stochastic programming model is thought to be sensitive in the designated probability distribution, this letter discloses that CVaR reformulation of a chance constraint is intrinsically robust. A pair of indices are proposed to quantify the maximum tolerable perturbation of the probability distribution, and can be computed from a computationally-cheap dichotomy search. An example on the coordinated capacity optimization of energy storage, and transmission line for a remote wind farm validates the main claims. The above results demonstrate that stochastic optimization methods are not necessarily vulnerable to distributional uncertainty, and justify the positive effect of the conservatism brought by the CVaR reformulation.

Offshore Transmission Network Planning for Wind Integration Considering AC and DC Transmission Options

Along with development of remote wind farms, offshore transmission networks become an integral part of wider transmission system. In this paper, an offshore transmission network planning (TNP) model is proposed for large-scale wind integration. The proposed approach allows system planners to evaluate the economic and technical feasibility of a range of potential network and non-network options considering a variety of uncertainties. The framework can be divided into one high-level planning problem determining a suitable type of power transmission technology and network routine over given planning horizon, and several low-level problems that examine the feasibility and optimality of the solution from the high-level problem considering different remedial action schemes, which is expected to reduce the need for adding new lines considering a broad range of uncertainty during system operation. Numerical examples on an IEEE 14-bus test system and an Australian regional transmission grid illustrate the performance of the proposed TNP model.

Grid integration of wind generation considering remote wind farms: hybrid markovian and interval unit commitment

Grid integration of wind power is essential to reduce fossil fuel usage but challenging in view of the intermittent nature of wind. Recently, we developed a hybrid Markovian and interval approach for the unit commitment and economic dispatch problem where power generation of conventional units is linked to local wind states to dampen the effects of wind uncertainties. Also, to reduce complexity, extreme and expected states are considered as interval modeling. Although this approach is effective, the fact that major wind farms are often located in remote locations and not accompanied by conventional units leads to conservative results. Furthermore, weights of extreme and expected states in the objective function are difficult to tune, resulting in significant differences between optimization and simulation costs. In this paper, each remote wind farm is paired with a conventional unit to dampen the effects of wind uncertainties without using expensive utility-scaled battery storage, and extra constraints are innovatively established to model pairing. Additionally, proper weights are derived through a novel quadratic fit of cost functions. The problem is solved by using a creative integration of our recent surrogate Lagrangian relaxation and branch-and-cut. Results demonstrate modeling accuracy, computational efficiency, and significant reduction of conservativeness of the previous approach.

Economic Assessments of LFAC and HVDC Transmissions for Large Offshore Wind Farms

Abstract Offshore wind farms extend a distance from an onshore grid to increase their generating power, but long distance and high power transmissions raise a lot of cost challenges. LFAC (Low Frequency AC) transmission is a new promising technology in high power and low cost power transmission fields against HVDC (High Voltage DC) and HVAC (High Voltage AC) transmissions. This paper presents an economic comparison of LFAC and HVDC transmissions for large offshore wind farms. The economic assessments of two different transmission technologies are analyzed and compared in terms of wind farm capacities (600 MW and 900 MW) and distances (from 25 km to 100 km) from the onshore grid. Based on this comparison, the economic feasibility of LFAC is verified as a most economical solution for remote offshore wind farms. Keywords: LFAC, HVDC, Offshore, wind farm I. INTRODUCTION In recent years, energy systems based on wind power have rapidly enlarged their application areas, especially towards large offshore wind farms (over 100 MW) and micro grid systems. The conventional onshore wind farms have small power generation and short distance power transmission to a power grid. However, for a large remote wind farms, a new power transmission system is required to provide high energy density and low loss power transmission characteristics with low investments. So, how to connect large remote wind farms to the onshore micro grid with low power losses and economic benefits is the prime concerns of researchers, and its economic power system and wind farm layouts for transmitting high power and long distance has gained more attentions. The conventional HVAC (High Voltage AC) system consists of wind generators, transformers, transmission cables and reactive power compensators, and the generated power is converted to a very high voltage (154 kV or 345 kV) by transformers. The HVAC power system transmits the power through 3 cores XPLE cables through underwater, but the transmission distance of the HVAC power system is the most critical factor against power transmission capability because reactive power losses are proportional to the distance. Therefore, HVAC transmission system is not adequate to long distance large offshore wind farms. Recently, new technologies for power systems have been reported [1]-[15] to provide alternative ways to maximize the power transmission capability. The most outstanding technology is HVDC power system, which has high economic benefits for long distant applications because HVDC power system has no limitation of the transmission capability. HVDC Transmission does not suffer from the reactive losses found in the transmission of HVAC system. However, in order to transmit DC power from a remote wind farms the generated AC power must be converted to the DC power and must be converted back to the AC power for a grid connection. Converting the AC power into the DC power requires an expensive AC to DC converter station to be installed at the remote wind farm area as well as a DC to AC power converter station at a receiving end, prior to the grid. An alternative technology is LFAC (Low Frequency AC) transmission system. LFAC transmission system uses lower frequency (50/3 Hz or 60/3 Hz) than a grid frequency (50 or 60 Hz) and requires no offshore power converter stations but an onshore frequency converter station. LFAC transmission system has an ability to extend a transmission distance and capability rather than the conventional HVAC transmission system. However, LFAC system can generate some audible noises and have transformer saturation and size problems. To adopt a best power system topology for large remote offshore wind farms, an economic analysis about HVDC and LFAC system should be performed. However, economic investments are directly dependent on a power system configuration, a distance and transmission capability. Therefore, this paper proposes HVDC and LFAC power system configurations and presents an economic assessments and comparison of LFAC and HVDC transmissions for large offshore wind farms. The economic assessments of two different transmission technologies are analyzed based on the proposed power configurations and compared in terms of wind farm’s capacities (600 MW and 900 MW) and distances (from 25 km to 100 km) from the onshore grid. From the comparison, the economic feasibility of LFAC is verified as a most economical solution for the large offshore wind farms.

Steady‐state and transient voltage stability analysis of a weak distribution system with a remote doubly fed induction generator‐based wind farm

AbstractIn modern, stressed distribution system, voltage stability is a major concern from planning and operation perspectives. Remote wind farm connected to a weak distribution system through a long line could adversely affect the voltage stability of the respective distribution network. This paper investigates the transient and steady‐state voltage issues of a distribution network with a distant doubly fed induction generator (DFIG)‐based wind farm. Results show that a distant DFIG‐based wind farm could improve the voltage stability of a distribution network with a large motor load in steady‐state operating condition as well as following disturbances, like three‐phase faults, sudden load tripping, and motor starting.

The role of energy storage in accessing remote wind resources in the Midwest

Replacing current generation with wind energy would help reduce the emissions associated with fossil fuel electricity generation. However, integrating wind into the electricity grid is not without cost. Wind power output is highly variable and average capacity factors from wind farms are often much lower than conventional generators. Further, the best wind resources with highest capacity factors are often located far away from load centers and accessing them therefore requires transmission investments. Energy storage capacity could be an alternative to some of the required transmission investment, thereby reducing capital costs for accessing remote wind farms. This work focuses on the trade-offs between energy storage and transmission. In a case study of a 200MW wind farm in North Dakota to deliver power to Illinois, we estimate the size of transmission and energy storage capacity that yields the lowest average cost of generating and delivering electricity ($/MWh) from this farm. We find that transmission costs must be at least $600/MW-km and energy storage must cost at most $100/kWh in order for this application of energy storage to be economical.

Stability analysis of power system with doubly fed induction generator-based wind farm connected through series flexible AC transmission SYSTEM device compensated line

Wind farm may be remotely located due to the availability of wind. Therefore, series compensation may be required to evacuate large wind power to a distant power system. The impact of series compensation on the stability of power system with wind farm is of concern for transmission and system operation. This paper investigates the stability issues of power system with remote wind farm. The studied power system network is connected to a remote wind farm through a series Flexible AC Transmission System device, Static Synchronous Series Compensator, compensated transmission line. The small signal stability and transient stability issues are studied for uncompensated and compensated system. The results show that damping ratio is increased for most of the oscillatory modes showing increase in small signal stability with series compensation. The eigenvalue sensitivity analysis is performed with the degree of compensation and voltage gain as sensitivity parameters. Transient analysis is performed for a three-phase fault, and the results show improvement in transient stability of compensated power system.

Control of a Wind Farm Based on Synchronous Generators With a Central HVDC-VSC Converter

A control scheme for wind farms based on synchronous generators connected to a single power converter is presented. The scheme is applicable to HVDC interfaced offshore or remote wind farms. The proposed control scheme is based on computing the optimal wind farm electrical frequency depending on the different incoming wind speeds. The power converter regulates the system frequency by adjusting the power injected to the HVDC circuit. Fault ride-through is also possible by reducing rapidly the injected active power. The proposed scheme is validated by means of simulations with a wind farm composed of four wind turbines.

Reliability & Availability of Wind Turbine Electrical & Electronic Components

Recent analysis of European onshore wind turbine reliability data has shown that whilst wind turbine mechanical subassemblies tend to have relatively low failure rates but long downtimes, electrical and electronic subassemblies have relatively high failure rates and short downtimes. For onshore wind turbines the higher failure rates of electrical and electronic subassemblies can be managed by a maintenance regime that provides regular and frequent attendance to wind turbine sites. This regime will be costly or impossible to sustain in more remote onshore or offshore wind farm sites. This paper gathers data supporting the contention that electrical and electronic subassembly failure modes are a significant contributor to wind turbine unreliability, identifying some of their root causes, showing how they will play a more significant part in the availability of offshore wind turbines. The paper concludes by showing how more can be learnt to eliminate or mitigate some of these electrical and electronic subassembly failure modes.