Intermittent Wind Power Generation Research Articles

Demand Flexibility Management for Buildings-to-Grid Integration with Uncertain Generation

We present a Buildings-to-Grid (BtG) integration framework with intermittent wind-power generation and demand flexibility management provided by buildings. First, we extend the existing BtG models by introducing uncertain wind-power generation and reformulating the interactions between the Transmission System Operator (TSO), Distribution System Operators (DSO), and buildings. We then develop a unified BtG control framework to deal with forecast errors in the wind power, by considering ancillary services from both reserves and demand-side flexibility. The resulting framework is formulated as a finite-horizon stochastic model predictive control (MPC) problem, which is generally hard to solve due to the unknown distribution of the wind-power generation. To overcome this limitation, we present a tractable robust reformulation, together with probabilistic feasibility guarantees. We demonstrate that the proposed demand flexibility management can substitute the traditional reserve scheduling services in power systems with high levels of uncertain generation. Moreover, we show that this change does not jeopardize the stability of the grid or violate thermal comfort constraints of buildings. We finally provide a large-scale Monte Carlo simulation study to confirm the impact of achievements.

Power Quality Issues and Mitigation for Electric Grids with Wind Power Penetration

Large penetration of wind energy systems into electric-grids results in many power quality problems. This paper presents a classification of power quality issues, namely harmonics and short-duration voltage variation observed due to the integration of wind power. Additionally, different techniques and technologies to mitigate the effect of such issues are discussed. The paper highlights the current trends and future scopes in the improvement of the interconnection of wind energy conversion systems (WECSs) into the grid. As the voltage variation is the most severe power quality issue, case studies have been presented to investigate this problem using steady-state time-series simulations. The standard IEEE test system namely IEEE 123-node test feeder and IEEE 30-node grid are solved under different operating conditions with wind power penetration. Typical daily load profiles of a substation in Riyadh, Saudi Arabia, and an intermittent wind power generation profile are used in all case studies. Mitigation of voltage variations due to wind intermittency is achieved using reactive power compensation of the interface inverter. The results show the effectiveness of these approaches to avoid voltage variation and excessive tap setting movements of regulators and keep the voltage within the desired operating conditions.

A state-of-the-art review on wind power deterministic prediction

With the continuous growth of wind power access capacity, the impact of intermittent and volatile wind power generation on the grid is becoming more and more obvious, so the research of wind power prediction method has been widely concerned. Accurate wind power prediction can provide necessary support for the power grid dispatching, combined operation of generating units, operation, and maintenance of wind farms. According to the existing wind power prediction methods, the wind power prediction methods are systematically classified according to the time scale, model object, and model principle of prediction. The physical methods, statistical methods include single and ensemble prediction methods related to wind power prediction are introduced in detail. The error evaluation indicator of the prediction method is analyzed, and the advantages and disadvantages of each prediction method and its applicable occasions are given. At the same time, in view of the existing problems in the wind power prediction method, the corresponding improvement plan is put forward. Finally, this article points out that the research is needed for wind power prediction in the future.

Robust optimization for optimal day-ahead economic dispatch of CCHP considering wind-load uncertainty

Distributed wind power generators (WPGs) have been increasingly deployed into power system through combined cooling, heat, and power (CCHP) system. However, uncertain load and intermittent wind power generation adversely affect the economy of the system operation. In order to improve the economy of the CCHP operation, this paper presents a two-stage robust optimization model for the CCHP day-ahead (DA) economic dispatch considering the uncertainties of wind power generation and electric load demand. The model aims at minimizing the total operation cost. The day-ahead first stage is to decide the state and base generation of controllable generators that can withstand the worst-case scenario of the uncertainty while the real-time (RT) second stage is to adjust the generation of the generators according to the actual scenario of the uncertainty. To solve the model, duality theory, Big-M method, and column-and-constraint generation (C&CG) decomposition approach are employed to convert the model into tractable master problem and sub problem, so that a column-and-constraint generation iteration algorithm can be applied to figure out the optimal dispatch solution. Finally, experimental results reveal the effectiveness of the presented model and the employed method.

Integrated transmission and storage systems investment planning hosting wind power generation: continuous‐time hybrid stochastic/robust optimisation

In this study, a continuous-time hybrid stochastic/robust optimisation is proposed for the integrated investment in transmission lines (TLs) and energy storage systems (ESSs) with high penetration of uncertain wind power generation (WPG) sources from a central planner viewpoint. The main objective of the problem is to achieve a simultaneous expansion of transmission assets, TLs and ESSs, whereas minimising the investment cost while taking the operational aspects of a power system into account to accommodate higher shares of uncertain and intermittent WPGs. However, the integrated expansion planning of joint TL and ESS to integrate WPGs via conventional hourly discrete time model can increase the operation cost and result in a non-optimal sizing and siting of TLs and ESSs, hence, can impose an opposite effect on the favourite. Accordingly, a continuous-time model is proposed to coordinate the expansion planning of both TL and ESS to deal with sub-hourly uncertainty of WPGs. Also, the WPG uncertainty in expansion planning problem is characterised using a hybrid stochastic/robust optimisation framework. Numerical tests are implemented on a modified IEEE RTS 24-bus system and the achieved results confirm the efficiency of the proposed model.

A robust SMES control for enhancing stability of distribution systems fed from intermittent wind power generation

The voltage and frequency stability issues of power systems are the main challenges that arise from high penetration levels of wind energy systems. This paper presents an effective solution for voltage and frequency stability problems by using a superconducting magnetic energy storage (SMES) system controlled with a fuzzy logic controller (FLC). The proposed control system can suppress the voltage and frequency fluctuations due to the high variations of wind speed. In addition, the proposed control system is suitable for both balanced and unbalanced distribution systems with high penetration levels of wind turbines (WTs). A squirrel cage induction generator (SCIG) is selected in the case study, which represents the worst scenario of WT generation from the voltage and frequency stability aspects. This is due to the high reactive power consumed by the SCIG from the utility grid during steady state and voltage fluctuations that may lead to harmful consequences for power system components. The proposed control method is validated using the IEEE 33-bus radial distribution network (RDN), wherein the SMES and WT systems are connected to the weakest points of the RDN. The obtained results demonstrate the superior performance of the proposed FLC-SMES system for alleviating the voltage and frequency fluctuations of the distribution power system during high variations of wind power.

Frequency and voltage control of microgrid with high WECS penetration during wind gusts using superconducting magnetic energy storage

The intermittent behavior of wind power generation results in a fast variation of both frequency and voltage magnitudes of isolated microgrids with high wind power penetration. In this paper, a hybrid energy microgrid with wind energy conversion system (WECS) and diesel synchronous generators are analyzed during wind gust conditions. Superconducting magnetic energy storage (SMES) is connected at the same node of the WECS to mitigate the intermittent wind power generation. A developed fuzzy logic controller has been applied to achieve active power sharing. The damping of voltage fluctuation depends on SMES reactive power, which is controlled by a voltage source converter. The studied microgrid comprises 33 nodes, two diesel SGs, and two WECSs of squirrel cage induction generator type at 30% penetration level. The results demonstrate the effectiveness of the proposed control strategy to mitigate the frequency fluctuations during the wind speed gusts by smoothing power output from WECSs/SMES system. Moreover, voltage control is achieved by injecting reactive power from the SMES system. All simulations are performed by MATLAB/Simulink package.

An Expeditious Methodology to Assess the Effects of Intermittent Generation on Power Systems

This paper proposes an expeditious methodology that provides hourly assessments of the effect of intermittent wind and solar power generation on the electrical quantities characterizing power systems. Currents are measured via circuit breakers to confirm the correct sizing of devices based on their rated currents. Nodal voltage magnitudes are assessed for compliance with limits imposed by regulatory authorities, whereas the active power produced by hydroelectrical generators is assessed for reserve energy. The proposed methodology leverages a fuzzy extended deterministic optimal power flow that uses in power balance equations the average hourly values of active power generated by wind and solar sources as well as hourly energy load. The power grid is modeled at the substation level to directly obtain power flow through circuit breakers. Uncertainties in power system electrical quantities are assessed for an optimal solution using a Taylor series associated with deviations from the average values of the active power produced by the wind and solar sources. These deviations are represented using a fuzzy triangular model reflecting the approximations of the probability density functions of these powers. The methodology takes into account a subjective investigation that focuses on the qualitative characteristic of these energy sources’ behaviors.

Distributed Probabilistic ATC Assessment by Optimality Conditions Decomposition and LHS Considering Intermittent Wind Power Generation

This paper investigates a probabilistic assessment of available transfer capability (ATC) by optimality condition decomposition (OCD) techniques and latin hypercube sampling (LHS) method in power systems with penetration of wind energy resources. First, the ATC assessment is mathematically formulated as a non-linear optimal power flow problem. Then, an iterative decomposition-coordination methodology based on OCD techniques is conducted for distributed assessment of the ATC. In order to estimate the probability density function and empirical cumulative density function under wind power fluctuations, LHS method is utilized for obtaining samples of the integrated wind power sources. Next, wind power samples are appended into the proposed decomposition-coordination approach to provide a fast LHS-based Monte Carlo (MC) simulation of the ATC at the current system state. In order to provide a preliminary approximation of the range variation of the ATC before executing the MC technique, OCD-based distributed computations of the average-case, best-case, and worst-case scenarios subjected to wind power variations are developed by following three approaches: first, assuming that the average-case of the ATC occurs at the mean power output of integrated wind farms, second, adding box-constraints related to the power output of each wind farm in order to estimate the best-case scenario, and third, developing an iterative sensitivity-based scheme to estimate the worst-case scenario. Numerical experiments in the standard IEEE 118-bus system demonstrate the correctness of the proposed distributed probabilistic ATC assessment.

Business Models and Profitability of Energy Storage

Storage technologies – such as batteries or hydrogen – are crucial for a transition towards a low-carbon economy as they complement intermittent wind and solar power generation without the emission of carbon dioxide to the atmosphere. Rapidly growing shares of these renewables, combined with the requirement for profit of potential investments, make clarity on business models and profitability of energy storage both urgent and essential. Here we identify the business models of conceivable storage applications, match them with available storage technologies via overlapping operational parameters and systematically examine opportunities and barriers for profitability, including supportive policy measures and priorities for research and development. Existing technologies could meet the need for storage in the power market, but widespread profitability relies on advances in both economic utilization and technological innovation.

Coordination of pumped-storage unit and irrigation system with intermittent wind generation for intelligent energy management of an agricultural microgrid

Abstract This paper presents a new coordination framework to optimize the joint operation of pumped-storage unit, irrigation system and intermittent wind power generation in an agricultural microgrid. The microgrid is an agricultural complex connected to the medium voltage network. This complex contains a farm needing water to be irrigated every day. The irrigation system has two large scale reservoirs located in different levels. These reservoirs have been planned to act as pumped-storage unit reservoirs. The microgrid contains different electrical loads such as industrial livestock, agricultural products packaging factory, drip irrigation system, lighting and other small loads. The microgrid is connected to the upstream network at the grid supply point (GSP) and supplies loads with power from the upstream network and a wind power unit located in the farm. The proposed framework optimizes day-ahead (DA) scheduling of power exchange with the upstream network, pumped-storage unit and irrigation system based on forecasted wind power, microgrid load demand and water needed for irrigation in a market environment. The two-point estimate method (TPEM) is implemented to model the uncertainties associated with wind power and wholesale market prices. Finally, the effectiveness of the proposed framework is evaluated on several case studies.

Emission‐economic dispatch of thermal power generation units in the presence of hybrid electric vehicles and correlated wind power plants

With the integration of plug-in hybrid electric vehicles (PHEVs) and renewable energy resources into the power system, the environmental-economic dispatch of conventional power generation units takes new dimensions due to several ineluctable uncertain factors. This study presents a probabilistic optimisation framework for the emission, economic dispatch of thermal power generation units, considering the stochastic charging demand of PHEVs, intermittent wind power generation and uncertain load demand. To characterise the uncertainty in the output variables, the point estimate method and Nataf transformation are employed, considering the correlation between wind power plants. To find Pareto optimal solutions concerning minimisation of the emission and fuel cost, heuristic fitness sharing mechanisms and a meta-heuristic algorithm are proposed. Monte Carlo simulation together with state-of-the-art optimisation techniques (NSGA-II and SPEA-2) are employed in a quantitative performance appraisal to scrutinise the effectiveness of the proposed method in the uncertainty quantification and multi-objective optimisation.

Electricity prices, large-scale renewable integration, and policy implications

This paper investigates the effects of intermittent solar and wind power generation on electricity price formation in Germany. We use daily data from 2010 to 2015, a period with profound modifications in the German electricity market, the most notable being the rapid integration of photovoltaic and wind power sources, as well as the phasing out of nuclear energy. In the context of a GARCH-in-Mean model, we show that both solar and wind power Granger cause electricity prices, that solar power generation reduces the volatility of electricity prices by scaling down the use of peak-load power plants, and that wind power generation increases the volatility of electricity prices by challenging electricity market flexibility.

Electricity Prices, Large-Scale Renewable Integration, and Policy Implications

This paper investigates the effects of intermittent solar and wind power generation on electricity price formation in Germany. We use daily data from 2010 to 2015, a period with profound modifications in the German electricity market, the most notable being the rapid integration of photovoltaic and wind power sources, as well as the phasing out of nuclear energy. In the context of a GARCH-in-Mean model, we show that both solar and wind power Granger cause electricity prices, that solar power generation reduces the volatility of electricity prices by scaling down the use of peak-load power plants, and that wind power generation increases the volatility of electricity prices by challenging electricity market exibility.

Risk-Averse Preventive Voltage Control of AC/DC Power Systems Including Wind Power Generation

Preventive voltage control (PVC) deals with the alert state of power systems, where the system operates in a stable regime but loading margin (LM) is insufficient or some operational constraints have been violated. Hence, the aim of PVC is to ensure a desired LM (i.e., restoration of normal operation state), while minimizing the corresponding control costs. This paper proposes a new stochastic PVC (SPVC) model for power systems operation, taking into account the uncertainties of wind power generation. The uncertainty of wind power generation is handled using a scenario-based modeling approach. The risk associated with each objective function (OF) is handled using conditional value at risk (CVaR). Voltage set-points of generation units, active power readjustment of predetermined generating units, load reduction of a predetermined load buses, along with the intermittent wind power generation, are employed as control measures in the proposed SPVC approach. Line-commutated converter high-voltage dc (LCC-HVDC) link constraints and doubly fed induction generators (DFIGs) capability curves are also considered in the proposed SPVC approach. To illustrate the effectiveness of the proposed approach, it is applied on the IEEE 39-bus test system. The obtained results substantiate the applicability of the proposed SPVC model to ensure secure operation of ac/dc power systems with high penetration of offshore wind farms.

Stochastic reactive power dispatch in hybrid power system with intermittent wind power generation

Environmental concerns besides fuel costs are the predominant reasons for unprecedented escalating integration of wind turbine on power systems. Operation and planning of power systems are affected by this type of energy due to the intermittent nature of wind speed inputs with high uncertainty in the optimization output variables. Consequently, in order to model this high inherent uncertainty, a PRPO (probabilistic reactive power optimization) framework should be devised. Although MC (Monte-Carlo) techniques can solve the PRPO with high precision, PEMs (point estimate methods) can preserve the accuracy to attain reasonable results when diminishing the computational effort. Also, this paper introduces a methodology for optimally dispatching the reactive power in the transmission system, while minimizing the active power losses. The optimization problem is formulated as a LFP (linear fuzzy programing). The core of the problem lay on generation of 2m + 1 point estimates for solving PRPO, where n is the number of input stochastic variables. The proposed methodology is investigated using the IEEE-14 bus test system equipped with HVDC (high voltage direct current), UPFC (unified power flow controller) and DFIG (doubly fed induction generator) devices. The accuracy of the method is demonstrated in the case study.

Comparative Assessment of SVC and TCSC Controllers on the Small Signal Stability Margin of a Power System Incorporating Intermittent Wind Power Generation

Wind power is highly variable due to the stochastic behavior of wind speeds. This intermittent nature could excite the electromechanical modes resulting in the small signal instability of a power system. In this study, the performance of static VAR compensation (SVC) and thyristor controlled series capacitor (TCSC) controllers in the damping of electromechanical modes is analyzed and compared. The study employs probabilistic modal analysis method using Monte Carlo simulation and Latin hypercube sampling techniques. Various scenarios are created to get insight into the study. The results obtained from the modal analysis are verified by using the time-domain simulation. Some of the key results show that SVC is more robust in the damping of electromechanical modes compared to TCSC. The result also reveals that allocation of power system stabilizer (PSS) using probabilistic method is more effective and robust compared to deterministic approach.

Battery Energy Storage Station Based Smoothing Control of Wind and Photovoltaic Power Generation Fluctuations Using SOC Control Strategy

The battery energy storage system (BESS) is the current typical means of smoothing intermittent wind or solar power generation. Such BESS hybrid power systems require a suitable control strategy that can effectively regulate power output levels and battery state of charge (SOC). This paper presents the results of a wind/PV/BESS hybrid power system simulation analysis under taken to improve the smoothing performance of wind and Photovoltaic (PV) power generation and the effectiveness of battery SOC control. A wavelet based power smoothing method is presented for reducing output power fluctuations of wind/PV hybrid power generation systems and regulating the battery SOC. The effectiveness of the proposed method was verified using MATLAB/SIMULINK software.

The impact of wind power generation on the electricity price in Germany

This paper investigates the relationship between intermittent wind power generation and electricity price behaviour in Germany. Using a GARCH model, I evaluate the effect of wind electricity generation on the level and the volatility of the electricity price in an integrated approach. The results show that variable wind power reduces the price level but increases its volatility. This paper's results also indicate that regulatory change has stabilised the wholesale price. The electricity price volatility has decreased in Germany after a modification of the marketing mechanism of renewable electricity. This gives confidence that further adjustments to regulation and policy may foster a better integration of renewables into the power system.

Analysis of wind power generation operation management risk in China

The Chinese government has made an important effort to diversify the country's energy mix and exploit different sources of renewable energy. Although China's installed wind power capacity has undergone a dramatic expansion over the past six years, the electricity generated from wind power has not increased as expected. Meanwhile, operational risks, such as high generation cost, mismatch between capacity and generation, intermittent wind power generation, power grid construction lag, deficient policy, and operation mechanism, have become increasingly prominent. If not controlled, these risks will negatively affect wind power development in China. Therefore, this paper established a quantitative analysis model of wind power operation management risk from two aspects, feed-in tariff and grid electricity (electricity being connected to the grid), based on an analysis of wind power operation management risk in China. Moreover, this study quantitatively assessed the risk of the operational management of a wind farm in Inner Mongolia. Finally, corresponding risk control strategies for the healthy development of wind power generation in China were proposed.