Conventional Generation Units Research Articles

Fast Power Reserve Emulation Strategy for VSWT Supporting Frequency Control in Multi-Area Power Systems

The integration of renewables into power systems involves significant targets and new scenarios with an important role for these alternative resources, mainly wind and PV power plants. Among the different objectives, frequency control strategies and new reserve analysis are currently considered as a major concern in power system stability and reliability studies. This paper aims to provide an analysis of multi-area power systems submitted to power imbalances, considering a high wind power penetration in line with certain European energy road-maps. Frequency control strategies applied to wind power plants from different areas are studied and compared for simulation purposes, including conventional generation units. Different parameters, such as nadir values, stabilization time intervals and tie-line active power exchanges are also analyzed. Detailed generation unit models are included in the paper. The results provide relevant information on the influence of multi-area scenarios on the global frequency response, including participation of wind power plants in system frequency control.

Gumbel copula based aggregated net load forecasting for modern power systems

Wind and solar have major share among the growing renewable penetration, due to their extensive availability and improved technologies. Both wind and solar generation are highly uncertain and intermittent as compared to system load. The increased number of such uncertain and intermittent variables necessitates complex multivariate operational strategies for system operation. A compilation of different uncertain and intermittent variables such as load, wind and solar generation, to a single uncertain variable called net load, reduces system operational planning complexity. Net load is the difference between total load and renewable generation. Thus, conventional generation units have to be scheduled for net load. Prior knowledge about net load can help optimum operational planning such as generation scheduling and power system flexibility estimations. There have been significant advancement in load and renewable generation forecasting over the last decades. Still, there is little attention towards net load forecasting (NLF). This study proposes a novel NLF model using Gumbel copula based joint probability distribution for load, wind and solar generation forecasting error aggregation. Gumbel copula covers all extreme forecasting errors due to max-stable property. Proposed model uses modified Grey index models for forecasting. Results show that proposed model has strong potential in very short-term NLF.

A Comprehensive Approach for Maximizing Flexibility Benefits of Electric Vehicles

Increasing variability and uncertainty coming from both sides of the power system equilibrium equation, such as wind energy on the generation side and increasing share of new consumers such as electric vehicles on the demand side, entail higher reserve requirements. While traditional approaches of assigning conventional generation units to maintain system stability can increase operational costs, greenhouse gas emissions, or give signals for new investments, utilizing intelligent control of distributed sources might mitigate those negative effects. This can be achieved by controllable charging of domestic electric vehicles. On the other hand, increasing number of public charging stations gives final users the opportunity to fast charge, making their vehicles an additional source of uncertainty rather than a provider of flexibility. This paper brings a full system assessment of combined effect of slow home charging of electric vehicles together with fast charging stations (both with and without integrated energy storage systems), cast as mixed integer linear programming unit commitment model. The contributions of this paper look into optimal periods when fast charging is beneficial for the system operation, as well as assess the benefits of integrating battery storage into fast charging stations to mitigate the negative effects to power system operation.

Two-Scale Stochastic Optimization for Controlling Distributed Storage Devices

This paper is motivated by a power system with storage devices at multiple locations which need to be controlled at a much finer timescale than that necessary for conventional generation units. We present a stochastic optimization model of the power system which captures interactions of decisions at these two timescales through a novel state-variable formulation. The model also includes transmission constraints approximated by a linearized dc network, fast response operating reserves, and renewable generation. To tackle this high-dimensional multistage stochastic optimization problem, we present a sequential sampling method which we refer to as the stochastic dynamic linear programming. This algorithm is a dynamic extension of regularized two-stage stochastic decomposition for stagewise independent multistage stochastic linear programs, and is targeted at the class of problems where decisions are made at two different timescales. We compare our algorithm with the stochastic dual dynamic programming (SDDP) which has been effectively applied in planning power systems operations. Our computational results show that our sequential Monte-Carlo approach provides prescriptive solutions and values which are statistically indistinguishable from those obtained from SDDP, while improving computational times significantly.

Look-ahead risk-constrained scheduling of wind power integrated system with compressed air energy storage (CAES) plant

Due to increasing penetration of the renewable energy resources in modern power systems, the uncertain nature of these resources should be managed in real and near real-time scheduling. This paper investigates the benefits and applicability of look-ahead scheduling of integrated system including conventional generation units, wind power and compressed air energy storage (CAES). Different scenarios have been generated to model the uncertain parameters in the scheduling problem. To control and evaluate this stochastic process, the conditional value at risk (CVaR) framework has been implemented. Demand response programs have applied on the model to minimize the total cost and increase the flexibility requirement. This problem is formulated as mixed integer non-linear programming (MINLP) model with consideration of technical constraints of conventional generation, wind and CAES units. According to the numerical results, the operating profit could be maximized by the use of look-ahead approach and implementation of DR program.

Optimal stochastic scheduling of cryogenic energy storage with wind power in the presence of a demand response program

Abstract This paper provides a stochastic method to conduct the optimal scheduling of the combination of wind power and new-type large-scale energy storage with considering the demand response program in the electricity market. The integration of ASU and CES make the opportunity to store energy in the form of liquid in the off-peak periods and recovering the electricity in the peak periods. The uncertainty of electricity price, load demand and wind speed considered as the stochastic model uncertain parameters. The optimal operation of wind turbine, CES, and conventional generation units, considering the stochastic models for price, demand, and wind speed, was formulated as a mixed-integer non-linear programming (MINLP) problem. The constraints of CES operation, liquid and gas product demands, and ASU production were considered in ASU-CES modeling. The startup cost, minimum on/off time constraints, ramp rate, and capacity limits were considered in the formulation of conventional power generation. The demand response (DR) program was adopted to increase the total expected profit and decrease the total operational cost. The results revealed that the application of CES to attest system containing ASU increases the total profit of power generation units and decreases the total cost of generating power to serve load demands.

Analytical model for heat transfer between vertical fractures in fractured geothermal reservoirs during water injection

Abstract In recent years, the demand for energy has vastly increased due to rapid commercialization. This increasing requirement has put a further strain on the conventional power generation units. In this paper, the problem of water injection into a fractured geothermal reservoir in Cartesian coordinate is considered and an exact analytical solution has been presented to describe the transient temperature distribution and advancement of the thermal front generate due to transient temperature of heat depleted water in a coupled fracture–matrix system at the scale of a single fracture. This solution is able to explain the following phenomena: convection transport in fractures, conduction heat transfers in matrix block and heat flux transfer between rock matrix and fracture. Also, the heat transfer shape factor can be defined by employing the convection-conduction equation in matrix and fracture. The derived analytical solution was used for investigating early and late time periods of heat transfer phenomenon in naturally fractured reservoirs. In addition, a conceptual definition for thermal recovery efficiency has been offered as the rest of included materials. In order to validate the predicted temperature by analytical model in fractured geothermal reservoirs, the presented analytical model is compared with numerical and pervious analytical model.

Flexibility contribution of heat ventilation and air conditioning loads in a multi‐stage robust unit commitment with non‐deterministic variability‐oriented ramp reserves

Aside from conventional generation units, heat ventilation and air-conditioning (HVAC) loads, thanks to their inherent thermal capacity storage, are reasonable alternatives to mitigate short-term variability impacts in power systems with high renewable energy sources (RES). Accordingly, HVAC loads are integrated into a multi-stage multi-resolution robust unit commitment considering non-deterministic variability-oriented reserves to address operational flexibility requirement in power systems. Since common two-stage robust optimisations are over-conservative, non-causal and in general NP-hard, a non-conservative extended affinely adjustable robust optimisation approach is proposed to provide causality, enhance computational tractability and improve optimality in a multi-stage robust decision-making framework. In addition, since existing hourly resolution scheduling is unable to track fast and frequent variations in RES, the proposed framework is multi-resolution including both hourly and sub-hourly resolutions. Moreover, unlike conventional deterministic flexible ramp reserve procurement, a robust variability-oriented reserve scheduling is presented to determine adequate while economic and technically deliverable flexible ramp reserves from both generation and demand sides. The effectiveness of the proposed model is illustrated on the IEEE 24-bus reliability test system.

Improving AGC Performance of Coal-Fueled Thermal Generators Using Multi-MW Scale BESS: A Practical Application

With the increasing penetration of renewables in power system, frequency regulation is becoming a big challenge for conventional coal-fueled thermal generator units. To address this issue, more stringent criteria of automatic generation control (AGC) has been established by grid operators to regulate the generators. However, old-fashioned units can hardly meet the requirements and thus are subject to penalty. In this paper, an approach of using battery energy storage systems (BESS) for coordinated frequency regulation is proposed to improve the AGC performance of such generators. A demonstration project with a 2 MW BESS has been commissioned at Shijingshan Thermal Power Plant, Beijing. The basic principles, coordinated control strategy, technical performance as well as economic benefits have been presented and validated with field test results. As a pioneer of its kind in China, this project offers an excellent demo of utilizing BESS for improving AGC performance under the context of high renewable integration.

Coordination of Heat Pumps, Electric Vehicles and AGC for Efficient LFC in a Smart Hybrid Power System via SCA-Based Optimized FOPID Controllers

Due to the high price of fossil fuels, the increased carbon footprint in conventional generation units and the intermittent functionality of renewable units, alternative sources must contribute to the load frequency control (LFC) of the power system. To tackle the challenge, dealing with controllable loads, the ongoing study aims at efficient LFC in smart hybrid power systems. To achieve this goal, heat pumps (HPs) and electric vehicles (EVs) are selected as the most effective controllable loads to contribute to the LFC issue. In this regard, the EVs can be controlled in a bidirectional manner as known charging and discharging states under a smart structure. In addition, regarding the HPs, the power consumption is controllable. As the main task, this paper proposes a fractional order proportional integral differential (FOPID) controller for coordinated control of power consumption in HPs, the discharging state in EVs and automatic generation control (AGC). The parameters of the FOPID controllers are optimized simultaneously by the sine cosine algorithm (SCA), which is a new method for optimization problems. In the sequel, four scenarios, including step and random load changes, aggregated intermittent generated power from wind turbines, a random load change scenario and a sensitivity analysis scenario, are selected to demonstrate the efficiency of the proposed SCA-based FOPID controllers in a hybrid two-area power system.

A Control Approach and Supplementary Controllers for a Stand-Alone System with Predominance of Wind Generation

This paper proposes a control approach and supplementary controllers for the operation of a hybrid stand-alone system composed of a wind generation unit and a conventional generation unit based on synchronous generator (CGU). The proposed controllers allow the islanded or isolated operation of small power systems with predominance of wind generation. As an advantage and a paradigm shift, the DC-link voltage of the wind unit is controlled by means of a conventional synchronous generator connected to the AC grid of the system. Two supplementary controllers, added to a diesel generator (DIG) and to a DC dump load (DL), are proposed to control the DC-link voltage. The wind generation unit operates in V-f control mode and the DIG operates in PQ control mode, which allows the stand-alone system to operate either in wind-diesel (WD) mode or in wind-only (WO) mode. The strong influence of the wind turbine speed variations in the DC-link voltage is mitigated by a low-pass filter added to the speed control loop of the wind turbine. The proposed control approach does not require the use battery bank and ultra-capacitor to control the DC-link voltage in wind generation units based on fully rated converter.

A Novel Design of Decentralized LFC to Enhance Frequency Stability of Egypt Power System Including Wind Farms

This paper presents a real hybrid power system in Egypt, which includes both conventional generation units and Renewable Energy Sources (RESs) for studying the Load Frequency Control (LFC) problem. The conventional generation system in the Egyptian Power System (EPS) is decomposed into three dynamic subsystems; non-reheat, reheat and hydro power plants. Moreover, real wind speed data extracted from Zafarana location in Egypt is used for achieving a realistic wind power study. Each subsystem of the EPS has its own characteristics compared to the others. Moreover, the physical constraints of the governors and turbines such as Generation Rate Constraints (GRCs) of power plants and speed governor dead band (i.e., backlash) are taken into consideration. Therefore, this paper proposes a decentralized controller for each subsystem independently, to guarantee the stability of the overall closed-loop system. Hence, an optimal PID controller-based Particle Swarm Optimization (PSO) algorithm is proposed for every subsystem separately to regulate the frequency and track the load demands of the EPS. The performance of the proposed decentralized controller of each subsystem is compared to the centralized one under different operational scenarios. The EPS is tested using the nonlinear simulation by Matlab/SIMULINK. The obtained results reveal the superior robustness of the proposed decentralized controller against different load disturbance patterns, real wind power fluctuations and EPS uncertainties.

Reliability assessment of generating systems containing wind power and air separation unit with cryogenic energy storage

The acceptance of wind power has been increased in power systems because of environmental problems and production cost of conventional generation units. High penetration of intermittent wind power can increase risk level in power systems. The combination of energy storage with wind power is considered as a solution for problems of high wind integration. Energy storage can increase the reliability of power systems with high penetration of renewable energies like wind farms. In this paper, the cryogenic energy storage is used, which stores the air in the form of liquid and recover the power when it is needed. The copula theory is employed to generate correlated random variables to determine the wind speed of different locations. Also, for calculating the probability of availability of wind farm and energy storage system, Markov approach is adopted. Monte Carlo Simulation (MCS) method is implemented for obtaining reliability index of the system. The proposed method is verified using comprehensive simulations on Roy Billinton test system (RBTS) reliability test system considering the capacity of wind farms, level of wind penetration and size energy storage.

Frequency Stabilization of Renewable Power Systems Based on MPC With Application to The Egyptian Grid

Abstract This paper presents a Model Predictive Control (MPC) technique for frequency stabilization of renewable power systems with inherent nonlinearities. To prove the effectiveness of the proposed technique, the Egyptian Power System (EPS), which includes both conventional generation units (i.e., non-reheat, reheat and hydraulic power plants) and wind turbines is tested using Matlab/SIMULINK® software. Furthermore, the performance of the proposed MPC technique is compared with an optimal Proportional-Integral (PI) controller-based Particle Swarm Optimization (PSO) algorithm under different load profiles and system uncertainties. The simulation results emphasize the superior robustness of the proposed MPC-based LFC in comparison to the optimal PI controller.

Classification of Microgrids for Effective Contribution to Primary Frequency Control of Power System

In this paper, the effect of the increased penetration of microgrids (MGs) on the frequency control of power systems is studied. Considering the fast dynamic response of MGs and their distribution in the network, the conventional model of load frequency control may fail for their consideration in the frequency control system. In this paper, an appropriate dynamic model of MGs is developed for the system frequency control. Then, the MGs are classified into two different groups based on their distance to the conventional generation (CG) units. The distance is determined to measure the effect of MGs on the CG units. In the proposed classification method, one group consists of MGs, which have a considerable effect on a group of coherent generators, and the other group consists of MGs, which affect two (or more) noncoherent CG units. The coherence of CG units is determined by the oscillation modes of the power system. For the MGs near the coherent CG units, the measured bus frequency is used as the input control signal, and for the other group, the transferred active power deviation is utilized. Simulation results show the effectiveness of the proposed controllers to improve the system frequency stability.

Receding Horizon Control of Wind Power to Provide Frequency Regulation

With the increased penetration of wind generation in power systems, there is a rising interest in the provision of frequency regulation by wind turbines in order to relieve the burden on remaining conventional generation units. As a first step, the possible contribution of wind power to frequency regulation by optimally anticipating load imbalances in the power system is investigated. This ability is studied by implementing a receding horizon control which takes future load and wind variations into account. In this way, the available energy reserves of the wind turbine over a certain time horizon are optimally exploited to damp frequency oscillations while keeping the energy losses within defined limits. Results indicate that the receding horizon controller will mainly damp overfrequencies as its upward regulation capability is restricted to the available kinetic energy in the turbines. Moreover, it is shown that load forecast errors only slightly influence the results as the controller iteratively determines the optimal trajectory. Even if no load forecast is available, the proposed controller is still capable of damping frequency variations resulting from the simulated load profile by 25%, while keeping the energy yield above 97% compared to optimal power point tracking.

Integration of exergy analysis into model-based design and evaluation of aircraft environmental control systems

The environmental control system of an aircraft is a complex energy intensive system and the most important non-propellant consumer of energy among all aircraft systems. Considering the highly competitive market for conventional aircraft, meaningful analysis methods for evaluation during conceptual design of ECS and effective modelling and simulation tools became more important. Hence, this paper focuses on energy and exergy analyses applied to the conventional aircraft environmental control system combined with the model-based design approach. The reported results are related to the different analysis methods for aircraft environmental control systems and cover the model-based design approach.The exergy method is applied to a model of a conventional air generation unit of a commercial aircraft. This model was developed using a model-based design framework. Within this framework, the exergy analysis was performed for four phases of a standard flight mission: Take-off, cruise, landing and taxi. The results obtained from the detailed exergy analysis show highly varying performances for the components at the different simulation cases. The exergy efficiencies range from 1% to 88%. A discussion about the special requirements for aircraft environmental control system analysis methods concludes the paper.

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.

Modelling and transient simulation of a supercritical coal-fired power plant: Dynamic response to extended secondary control power output

Conventional generation units are subject to a changing economic environment and have to adjust their role for modern society's power generation. With substantial amounts of renewable energy production encountering the markets, thermal power plants are facing an increased need for flexible operation and decreasing revenues from selling electricity. Technical adaptations are necessary, though have to be redeemed within very short time spans to secure the plant's profitability. Dynamic simulation in this context serves as a helping tool to evaluate technical improvements and is an established tool in industry as well as in research institutes. This paper focuses on the detailed modelling of a hard coal-fired power plant using the thermohydraulic simulation code Apros. Characteristic of this model is the implementation of the major part of the control system together with the physical model. The comprehensive model enables detailed dynamic simulations with very small error values to process data, as to be seen in the validation. As an application example, the extension of a qualified load jump for secondary control power is realised. The dynamic simulation is thereby used to clarify necessary modifications in the control system and to assess the implications on plant operation.

A novel approach to frequency support in a wind integrated power system

This paper discusses the impact of wind penetration on frequency control of a thermal dominated system considering Generation Rate Constraints (GRC) and dead band non-linearities. The hidden inertia emulation and coordinated operation of conventional power generation systems with wind energy can effectively alleviate the frequency excursions during sudden load disturbances. Conventional energy storage device like Flywheel Energy Storage (FES) system can be used in conjunction with wind integrated power system to overcome the intermittent nature of power generation. Thyristor Controlled Series Compensator (TCSC) is found to be effective in damping low frequency oscillations in weak tie-lines and supplement the frequency regulation. A stochastic population based evolutionary computation technique - Particle Swarm Optimization (PSO) is used to tune the controller gains. A strategy comprising inertia control, coordinated operation of conventional generation units with wind energy and TCSC-FES has been proposed to enhance the frequency regulation which is effective in controlling low frequency oscillations as established by the simulation results.