Optimal Power Control Strategy for Wind Farm with Energy Storage System

This paper presents an optimization model for determining the nominal capacity of an energy storage system is presented, which transfers excess amounts of electrical energy from solar power plants as part of a group of distributed generation power plants, based on the criterion of the minimum cost of supplying electricity to end consumers. The use of the developed optimization model allows to determine the optimal parameters of the energy storage system to achieve an economic balance between the excess amounts of electric energy of solar power plants that are transferred and the amount of restrictions on inverters that are subject to payment. Based on the developed method, based on the forecast level of electric energy consumption and statistical data on the level of electric energy production at wind and solar power plants for the territory of Ukraine, the installed capacity of the wind, solar, reserve power plant and the nominal capacity of the two-hour energy storage system were determined, which will provide the minimum levelized cost of energy of supplying to consumers during the entire period of commercial operation of a group of distributed generation power plants.

The demand on energy supply increases continuously as economies develop and world population grows. Most of the energy in the world comes from the fossil fuels and the increase in energy demand accelerates the rate of depleting the fossil fuel resources. As fossil fuel is finite and also due to the environmental considerations, renewable energy (RE) resources have been actively developed as the alternative sources for electricity generation. Renewable sources used for large-scale electricity production can include wind, photovoltaic (PV), waves and so on. Among all the RE resources, wind power generation is witnessing rapid developments in recent years. Unfortunately, wind tends to be unsteady. The fluctuating and uncertain output powers from wind farms can be problematic, especially if there is a high penetration level of the renewable source in a grid system. The fluctuations may lead to excessive voltage variations and unacceptable degree of frequency deviations. Moreover, the unsteady and uncertain input wind power can cause firm power dispatch commitment from wind farms a difficult task. Expensive generation reserves have to be provided for grid system to ensure adequate level of system security and reliability is guaranteed. In fact, power generation from wind farms has often been excluded in the dispatch planning of the grids. Unless other viable techniques can be found, the above issues can constitute major impediment to the successful large-scale integration of wind power generation into grid systems. In this connection, the use of energy storage system (ESS) is one possible solution to mitigate the negative impacts of the unsteady wind power on electricity supply systems and to improve on the dispatchability of the wind power. In this investigation, in order to smoothen the fluctuations in the wind and to realize the dispatch planning of the wind power in a way similar to that of conventional generators, it is proposed that a three-level ESS is incorporated in a large-scale wind power generation scheme. In essence, at cluster-level of wind turbine generators (WTG), the solution involves having the high- and mid-frequency components of the aggregated wind power routed to supercapacitors (SC) and battery banks respectively of a battery-supercapacitor hybrid energy storage system (BSHESS) by a high-pass filter (HPF) and a band-pass filter (BPF). It then results in the smoothening of the wind power harnessed by the cluster. In this thesis, the BSHESS control scheme to reduce the wind power perturbations has been shown. A statistical method is also developed to determine the capacities of the minimum-cost BSHESS to meet the power smoothing objective at pre-specified probability level. Application of the proposed design approach is demonstrated using data obtained from an existing wind farm. As for dispatch planning, attention is to use a low-pass filter (LPF) to extract the low-frequency intrinsic mode and residue functions of wind power. The relatively slow-changing characteristics of the low-frequency wind power components, which contain most of the energy in the wind power, allow accurate forecasts of the power components to be obtained using artificial neural network (ANN). Dispatch planning of the wind power is then realized through buffering the low-frequency power fluctuations by a proposed power flows control strategy applied to a pumped hydroelectric storage (PHS) system. Focusing on low-frequency wind power for dispatch planning is a distinct advantage over the dispatch planning methods proposed by other researchers. Furthermore, a statistical method to determine the power and energy capacities of the PHS is included. The efficacy of the developed approach to dispatch planning is again illustrated based on data obtained from an existing wind farm. In all the above works, suitable cut-off frequencies for the HPF, BPF and LPF are derived based on the developed concept of minimum overlap energy and the outcome of empirical mode decomposition (EMD) analysis. EMD method is used to gain insights into the frequency-time characteristics of wind power. In this manner, the wind power can then be grouped into high-, mid- and low-frequency bands.

The ESS is considered as an effective tool for enhancing the flexibility and controllability of a wind farm, and the optimal control scheme of a wind farm with distributed ESSs is vital to the stable operation of wind power generation. In this paper, a coordinated active and reactive power control strategy based on model predictive control (MPC) is proposed for doubly fed induction generator (DFIG)-based wind farm (WF) with distributed energy storage systems (ESSs). The proposed control scheme coordinates the active and reactive power output among DFIG wind turbines (WTs), grid-side converters (GSCs), and distributed ESSs inside the WF, and the aim is to decrease fatigue loads of WTs, make the WT terminal voltage inside the extent practicable, and take the WF economic operation into consideration. Moreover, the best reactive power references of DFIG stator and GSC are produced independently based on their dynamics. At last, the control scheme generates optimal power references for all ESS to make the SOC of each ESS converge to their average state. With the distributed ESSs, the WF controller regulates the WTs inside WF more flexibly. A WF composed of 10 DFIG WTs was utilized to verify the control performance of the proposed coordinated active and reactive power control strategy.

Due to the existence of wind turbines in virtual power plants (VPPs), to eliminate the fluctuation characteristics of the wind turbine in the VPP and quantify the impact of the capacity of the energy storage system (ESS) on VPPs’ profitability, a multi-objective optimal schedule model, including the operating cost of the VPP, operation cost of the ESS and the electricity cost between the VPP and the grid, was proposed, and was solved by a quantum-inspired evolutionary algorithm; the output of conventional distribution generation and the state of charge were analysed on two different load days; the impact of different sub-object weights on the ESS capacity and the ESS cost and VPP profit under different rated capacities were also investigated. The results showed that the wind turbines' output error can be eliminated by the ESS on peak load day and valley load day; different weights of the VPP operating cost and the trading power cost would result in different capacities of the ESS; and the VPP's profit would rise with the increase of the ESS capacity when the capacity of the ESS was less than 8 MW.

The increasing integration of renewable energy generation (REG) makes the capacity value (CV) estimation for the REG become more important in the process of generation expansion planning. However, most researches on the CV ignore the hybrid generation system based on multiple complementary energy resources, as well as the operation strategy of energy storage system (ESS). To solve these problems, the models of available capacity of ESS are developed based on three different strategies. Then, using the sequential Monte-Carlo simulation method, the models and methods are developed for reliability assessment of generation system and capacity value estimation for the hybrid power generation system based on WT/PV/ES (HGS-WPE). By the application in IEEE-RTS79, the feasibility of models and estimation methods are verified. Finally the impacts of the complementation of HGS-WPE, the capacity and operation strategy of ESS on the reliability assessment and capacity value estimation are analyzed.

China's wind power capacity is increasing so rapidly that some areas are not able to consume all the produced wind power. Therefore, it has already become the inevitable trend in wind power integration to achieve the controlled operation of wind turbine. This paper first offers a method to predict the maximum generation capacity of every type of wind turbine, including both under-controlled wind turbine and uncontrolled wind turbine. And then a strategy for active power control of wind farm based on the predicting results is proposed. Considering thoroughly the active power fluctuation of wind turbine and the error of the prediction, the strategy adopts both long and short controlling periods to carry out coordinated optimization control. The simulation results show that the strategy can keep the active power output of wind farm in step with the control order, and consequently the generating efficiency is improved. In addition, the strategy is also applicable to the wind farm with some uncontrollable wind turbines, and the controlling precision can be satisfied.

The use of energy storage systems is widely recognized as a key tool to create a more resilient energy infrastructure. At the same time, new technologies such as soft-open points and on-load tap changers are deserving growing attention for their potential applications in smart grids. In this paper we consider the coordinated use of on-load tap changer and energy storage systems for voltage support in distribution networks. We first formulate the optimal control problem over a given time horizon as a multi-period optimal power flow. To cope with uncertainties such as inaccurate forecasts, the optimal control problem is then inserted into a receding horizon scheme. The proposed approach requires very limited information to predict possible voltage problems and counteract them in advance. The control algorithm is tested on real data from a low voltage network featuring over- and undervoltages in the absence of voltage control. The obtained results show that the coordinated use of on-load tap changer and storage devices allows one to dramatically reduce the size of the installed storage units required to alleviate voltage issues.

During recent years, wind energy has moved from an emerging technology to a nearly competitive technology. This fact, coupled with an increasing global focus on environmental concern and a political desire of a certain level of diversification in the energy supply, ensures wind energy an important role in the future electricity market. For this challenge to be met in a cost-efficient way, a substantial part of new wind turbine installations is foreseen to be erected in big onshore or offshore wind farms. This fact makes the production, loading and reliability of turbines operating under such conditions of particular interest.

This paper provides an overview of promising options for the energy storage systems (ESS) use in centralized and off-grid power systems. The technical and economic efficiency analysis of the ESS use in off-grid power system is carried out as in the case of a real village located in the north of the Siberian Federal District of Russia. Comparing with the basic case the effect of optimizing the generation equipment composition and its loading modes provided savings on the fuel component and maintenance in the amount of 23% per year, which could be considered and the valuable result.

Integrating non-dispatchable renewable energy sources (RES) such as wave farms into electric power systems presents inherent challenges. Specifically, the variability of the resource and its non-dispatchable) nature introduces power imbalances and power system stability problems in the system over both short and medium terms. This issue is particularly relevant for isolated power systems, such as those found on several European islands, where interconnection with the mainland is lacking. Therefore, although wave energy has significant potential for integration into island power systems due to resource availability, determining the maximum RES penetration that such systems can sustain while maintaining stability is not straightforward. Power system stability is closely tied to frequency. A well-established solution for improving the stability of isolated systems when integrating non-dispatchable RES is to install devices capable of responding to over- or under-frequency events, such as energy storage systems (ESS). The literature extensively discusses ESS control techniques for frequency regulation, with one of the most straightforward approaches being to operate the ESS according to a droop control strategy (similar to a statism). In this method, the power dispatched or stored by the ESS increases proportionally to the deviation from the frequency reference value. This paper presents a case study analyzing the frequency stability of an island power system equipped with an energy storage system (ESS) when integrating a wave farm. Frequency stability is evaluated based on two variables: wave energy penetration and the ESS droop control parameter. The case study is based on the island of El Hierro (Canary Islands, Spain), an isolated electrical system with a very high penetration of RES. The island’s electrical generation system consists of a wind farm, a pumped-storage hydroelectric power plant, and conventional generation from a diesel power plant. The analysis is conducted through simulations in MATLAB Simulink. A wave farm is modeled to evaluate the generated power and its associated oscillations, based on the wave energy resource at various locations along El Hierro’s coast. Additionally, an aggregated inertial dynamic model of the electrical power system is employed to assess the impact of the wave energy farm's generation on the system’s frequency and the aging that the frequency excursions introduce in the elements of the system. The Spanish Grid Code is considered to ensure compliance with frequency regulation mechanisms in isolated systems. Simulations are performed across different scenarios, varying both the nominal power of the wave farm and the ESS droop control parameter, in order to evaluate the ESS capacity. The results identify the optimal droop control parameter for each wave farm size to ensure frequency remains within acceptable thresholds. Furthermore, the minimum ESS capacity required for each wave farm size is determined from the simulations. These findings provide a basis for ESS and wave farm dimensioning, which could be translated into economic terms to maximize revenue (this aspect is beyond the scope of the present work).

During the operation of solar and wind power plants, it is necessary to solve issues related to the guaranteed capacity of these plants, as well as the frequency stabilisation in the power system where they operate, and maintain an operating mode of self-sufficiency conditions. One of the solutions to these problems is the use of energy storage systems. This article proposes a mathematical model for the study of frequency and power regulation processes in power systems with distributed generation, which includes renewable energy resources and energy storage systems. The novelty of the model lies in the possibility of determining energy cost indicators based on instantaneous energy power data. The model allows us to estimate the conditions under which distributed generation becomes self-sufficient. The results of the model calculations of two variants of power system operation, which includes wind generators with a capacity of 1500 MW, demonstrate the ability of the proposed model to accurately reproduce the dynamics of the frequency stabilisation process. The calculation results of the energy-economic indicators of a real power system combined with a powerful subsystem of wind generation and a battery-type energy storage system prove the competitiveness of self-sufficient renewable energy power plants.

There is growing interest in the use of energy storage systems (ESS) to create combined “renewable energy plus storage” power plants. ESS based on lithium-ion batteries have drawn much attention due to their high energy density and low self-discharge. However, as lithium-ion batteries are still costly, a power producer should determine ESS capacity in a sophisticated manner to ensure profitability of the PV plus storage projects. During the project horizon, lithium-ion batteries undergo severe capacity degradation, which must be considered in ESS planning. The degradation rate depends on various stress factors which are affected by ESS sizes and operation. Therefore, this paper aims to propose an advanced framework for calculating the capacity of an ESS supplementing a photovoltaic system considering the effect of the size and operation of ESS on battery degradation while maximizing profitability. Depending on how batteries are used during the project horizon, two scenarios are discussed and an ESS sizing framework for each scenario is suggested. To deal with non-convexity and black-box parameters of the optimal ESS sizing problems, we introduce an iterative algorithm that finds a solution by accessing battery degradation and optimizing profitability repetitively. We adopted the South Korean market for analysis and simulation of the frameworks.

The operation of electrical systems is becoming more difficult due to the intermittent and seasonal characteristics of wind and solar energy. Such operational challenges can be minimized by the incorporation of energy storage systems, which play an important role in improving the stability and reliability of the grid. The economic viability of hybrid power plants with energy storage systems can be improved if regulations enable the remuneration of the various ancillary services that they can provide. Thus, the aim of this study is to provide a literature review regarding the economic feasibility of hybrid wind and solar photovoltaic generation with energy storage systems and its legal and regulatory aspects. Observing the global tendency, new studies should address the technical and economic feasibility of hybrid wind and solar photovoltaic generation in conjunction with, at least, one kind of energy storage system. In addition, it is very important to take into account the regulatory barriers and propose solutions to remove them. It was observed that although regulatory aspects can influence the economic feasibility of hybrid projects, little is known about this relationship among regulatory frameworks. The findings presented in this article are important not only for Brazil, but also for other countries that do not have regulations in force to support the use of energy storage systems in hybrid systems.

The random and intermittent nature of wind power (WP) makes the integration of large-scale wind farms into power system problematic. The energy storage system (ESS) is an effective means to smooth the WP. This paper presents a novel Kalman filter (KF) based adaptive wind power smoothing method to determine the power output of an ESS. ESS capacity can be significantly reduced by adjusting the parameters of KF adaptively according to the WP fluctuation. Meanwhile, a fuzzy logic controller is introduced to manage the remained energy level (REL) of the ESS. By considering the current WP fluctuation, the REL and the power output of the ESS together in the controller, the REL can be successfully managed to a reasonable range without deteriorating the WP fluctuation. A test case based on data from an actual wind farm validated the effectiveness of the proposed method.

Increasing wind power penetration and the size of Wind Power Plants (WPPs) brings challenges to the operation and control of power systems. Most of WPPs are located far from load centers and the short circuit ratio (SCR) at the Point of Connection (POC) is low, which means that fluctuations of the wind power can cause voltage variations. An optimal voltage control scheme for WPPs with STATCOMs is presented in the paper. It ensures that the voltages within the WPPs and at the high voltage side of the WPPs are within the limits and maximizes the dynamic Var reserve of the WPPs. Case studies were conducted with the simplified Anholt offshore WPP and the case study results demonstrate the efficacy of the proposed optimal voltage control scheme.