Power generation expansion planning with adaptive simulated annealing genetic algorithm

In this paper, an adaptive simulated annealing genetic algorithm is proposed to solve generation expansion planning of Turkey's power system. Least‐cost planning is a challenging optimization problem due to its large‐scale, long‐term, nonlinear, and discrete nature of power generation unit size. Genetic algorithms have been successfully applied during the past decade, but they show some limitations in large‐scale problems. In this study, simulated annealing is used instead of mutation operator to improve the genetic algorithm. The improved algorithm is applied to the power generation system with seven types of generating units and a 20‐year planning horizon. The planning horizon is divided into four equal periods. The new algorithm provides approximately 6.6 billion US$ (3.2%) cheaper solution than GA and also shows faster convergence. Copyright © 2006 John Wiley & Sons, Ltd.     

A multiple objective linear programming model for power generation expansion planning

The planning of new units for electrical power generation is a problem which involves different and conflicting aspects. Besides cost, security issues and environmental concerns must be explicitly incorporated into the models. In this way mathematical models become more realistic, and they enhance the decision maker's comprehension of the complex and conflicting nature of the distinct aspects of the problem. A multiple objective linear programming model for power generation expansion planning is presented. The model considers three objective functions (net present cost of the expansion plans, reliability of the supply system, and environmental impacts) and three categories of constraints (load requirements, operational restrictions and budget). Three generating technologies are considered for power system expansion: oil, nuclear and coal.     

Delegated dispatching of wind farms: an optimal approach considering continuous control and interruption capabilities

In grids with high wind power penetration, the System Operator may curtail the power injected at critical moments for security reasons. An intermediate operator can optimize this power reduction for a group of wind farms under its control, attending to their controllability. In this way, resources may be used efficiently, and in cooperation with the system operation. In this paper, an optimization‐based procedure is proposed to allocate the power reductions among the wind farms of a region. Application examples based on the Spanish situation are shown, because in that country, these intermediate entities (called Delegated Dispatches) are about to begin their full operation. Copyright © 2008 John Wiley & Sons, Ltd.     

Investment planning for electricity generation expansion in a hydro dominated environment

This paper presents the investment planning model, which has been developed to rigorously valorize the large hydroelectric potential resources of Cameroon. Based on Benders technique, the decomposition approach proposed allows each component of the problem (investment and operation) to be conveniently modelled and solved by adapted methods. Furthermore, the relative small size of the actual system, the long experience of the manual generation management in use over a long time by the national electricity company (Sonel), and the fundamental data of the problem are exploited as the basis of the approach, to define a more detailed and adapted model. Formulated as a multistage mixed linear programming problem, the decomposition procedure of the Benders technique is applied to isolate from the problem so modelled its two main subproblems (investment and operation). The investment subproblem is modelled as a multistage mixed linear programming problem and solved by a branch and bound technique. The operation subproblem is represented as a multistage stochastic linear problem and solved by a revised simplex‐based method. Subsequently, a solution algorithm for the whole problem, defined by a finite iterative process where the subproblems are alternatively solved, is derived from the co‐ordination procedure of Benders technique. Case studies with the southern interconnected network of the Sonel system are presented and analysed. Copyright © 2001 John Wiley & Sons, Ltd.     

A comprehensive state‐of‐the‐art survey on power generation expansion planning with intermittent renewable energy source and energy storage

Generation expansion planning (GEP) is a power plant mix problem that identifies what, where, when, and how new generating facilities should be installed and when old units be retired over a specific planning horizon. GEP ensures that the quantity of electricity generated matches the electricity demand throughout the planning horizon. This kind of planning is of importance because most production and service delivery is dependent on availability of electricity. Over the years, the traditional GEP approaches have evolved to produce more realistic models and new solution algorithms. For example, with the agitation for green environment, the inclusion of renewable energy plants and energy storage in the traditional GEP model is gradually gaining attention. In this regards, a handful of research has been conducted to identify the optimal expansion plans based on various energy‐related perspectives. The appraisal and classification of studies under these topics are necessary to provide insights for further works in GEP studies. This article therefore presents a comprehensive up‐to‐date review of GEP studies. Result from the survey shows that the integration of demand side management, energy storage systems (ESSs), and short‐term operational characteristics of power plants in GEP models can significantly improve flexibility of power system networks and cause a change in energy production and the optimal capacity mix. Furthermore, this article was able to identify that to effectively integrate ESS into the generation expansion plan, a high temporal resolution dimension is essential. It also provides a policy discussion with regard to the implementation of GEP. This survey provides a broad background to explore new research areas in order to improve the presently available GEP models.     

A stochastic‐fuzzy programming model with soften constraints for electricity generation planning with greenhouse‐gas abatement

Increased atmospheric CO₂ concentration is widely being considered as the main driving factor that causes the phenomenon of global warming, due to the ever‐boosting use of fossil fuels. In this study, a fuzzy‐stochastic programming model with soft constraints (FSP‐SC) is developed for electricity generation planning and greenhouse gas (GHG) abatement in an environment with imprecise and probabilistic information. The developed FSP‐SC is applied to a case study of long‐term planning of a regional electricity generation system, where integer programming technique is employed to facilitate dynamic analysis for capacity expansion within a multi‐period context to satisfy increasing electricity demand. The results indicate different relaxation levels can lead to changed electricity generation options, capacity expansion schemes, system costs, and GHG emissions. Several sensitivity analyses are also conducted to demonstrate that relaxation of different constraints have different effects on system cost and GHG emission. Tradeoffs among system costs, resource availabilities, GHG emissions, and electricity‐shortage risks can also be tackled with the relaxation levels for the objective and constraints. Copyright © 2012 John Wiley & Sons, Ltd.     

Diffused introduction of Organic Rankine Cycle for biomass‐based power generation in an industrial district: a systems analysis

Specific Organic Rankine Cycle (ORC) units dedicated to biomass‐based power production have recently been developed through the introduction of novel organic working media and technology innovation. For small systems, ORC technology appears as an efficient alternative to conventional generation if also process waste heat can be exploited, as resulted in the last few years from the successful operation of several demonstration plants in Austria and Switzerland. The present study aims to investigate the impact of the introduction of ORC units in an industrial context from a system perspective, with particular reference to industrial districts, which are characterized by the concentration in small areas of a large number of medium‐ and small‐sized firms. The paper focuses on the opportunity of combining ORCs, traditional Rankine cycles and multi‐source district heating to meet energy requirements in an industrial district in North Eastern Italy. To this end, a mixed‐integer linear programming model oriented to economical optimization of the system is developed and sensitivity analysis is carried out in order to determine the conditions for the expansion of biomass‐based power generation in the analyzed industrial district and to evaluate potential for CO₂ emission reduction. Copyright © 2004 John Wiley & Sons, Ltd.     

Bi‐objective optimization of a grid‐connected decentralized energy system

Motivated by the increasing transition from fossil fuel–based centralized systems to renewable energy–based decentralized systems, we consider a bi‐objective investment planning problem of a grid‐connected decentralized hybrid renewable energy system. In this system, solar and wind are the main electricity generation resources. A national grid is assumed to be a carbon‐intense alternative to the renewables and is used as a backup source to ensure reliability. We consider both total cost and carbon emissions caused by electricity purchased from the grid. We first discuss a novel simulation‐optimization algorithm and then adapt multi‐objective metaheuristic algorithms. We integrate a simulation module to these algorithms to handle the stochastic nature of this bi‐objective problem. We perform extensive comparative analysis for the solution approaches and report their performances in terms of solution time and quality based on well‐known measures from the literature.     

Power characteristics of a fuel cell micro‐grid with wind power generation

An independent micro‐grid connected with renewable energy has the potential to reduce energy costs, and reduce the amount of greenhouse gas discharge. However, the frequency and voltage of a micro‐grid may not be stable over a long time due to the input of unstable renewable energy, and changes in short‐period power load that are difficult to predict. Thus, when planning the installation of a micro‐grid, it is necessary to investigate the dynamic characteristics of the power. About the micro‐grid composed from 10 houses, a 2.5 kW proton exchange membrane fuel cell is installed in one building, and it is assumed that this fuel cell operated corresponding to a base load. A 1 kW PEM‐FC is installed in other seven houses, in addition a 1.5 kW wind turbine generator is installed. The micro‐grid to investigate connects these generating equipments, and supplies the power to each house. The dynamic characteristics of this micro‐grid were investigated in numerical analysis, and the cost of fuel consumption and efficiency was also calculated. Moreover, the stabilization time of the micro‐grid and its dynamic characteristics accompanied by wind‐power generation and fluctuation of the power load were studied. Copyright © 2007 John Wiley & Sons, Ltd.     

A novel sensorless current shaping control approach for SVPWM inverter with voltage disturbance rejection in a dc grid–based wind power generation system

A novel sensorless current shaping (CS) control strategy is proposed to avail better power quality (PQ) of a dc grid–based wind power generation system (WPGS) used on a poultry farm by generating an appropriate reference current for space vector pulse width modulation (SVPWM) inverter. The proposed CS strategy also offers adequate control for parallel operation of multiple generators and inverter applications, without requiring voltage and frequency synchronization. Further, to control the poultry farm–based WPGS, a two‐stage control loop is implemented such as energy flow control loop (EFCL) and harmonic control loop (HCL). The first loop is used to regulate the power flow, and the second loop is used to compensate harmonics. A mathematical current decomposition technique is suggested for an appropriate resistance emulation to realize a better power flow, higher harmonic rejection, and better inverter operation. In this planned approach for attaining constant wind speed, an electric ventilation fan in the poultry farm is used. A combined hybrid dc and ac grid approaches are suggested for facilitating variable load integration in a poultry farm–based microgrid system. Moreover, for achieving better power management during the islanded mode of operation, the battery energy storage (BES) device is integrated with the dc grid through a bidirectional converter. The proposed WPGS design and control approach has been simulated through MATLAB/Simulink software under various test conditions, to demonstrate the operational capability, to achieve better PQ, and to increase the flexibility and reliability in the microgrid operation.     

Boiling coal in water: Hydrogen production and power generation system with zero net CO2 emission based on coal and supercritical water gasification

Coal is the single most important fuel for power generation today. Nowadays, most coal is consumed by means of “burning coal in air” and pollutants such as NO_x, SO_x, CO₂, PM2.5 etc. are inevitably formed and mixed with excessive amount of inner gases, so the pollutant emission reduction system is complicated and the cost is high. IGCC is promising because coal is gasified before utilization. However, the coal gasifier mostly operates in gas environments, so special equipments are needed for the purification of the raw gas and CO₂ emission reduction. Coal and supercritical water gasification process is another promising way to convert coal efficiently and cleanly to H₂ and pure CO₂. The gasification process is referred to as “boiling coal in water” and pollutants containing S and N deposit as solid residual and can be discharged from the gasifier. A novel thermodynamics cycle power generation system was proposed by us in State Key Laboratory of Multiphase Flow in Power Engineering (SKLMFPE) of Xi'an jiaotong University (XJTU), which is based on coal and supercritical water gasification and multi-staged steam turbine reheated by hydrogen combustion. It is characterized by its high coal-electricity efficiency, zero net CO₂ emission and no pollutants. A series of experimental devices from quartz tube system to a pilot scale have been established to realize the complete gasification of coal in SKLMFPE. It proved the prospects of coal and supercritical water gasification process and the novel thermodynamics cycle power generation system.     

Wind turbines equipped with fractional‐order controllers: Stress on the mechanical drive train due to a converter control malfunction

This paper is on variable‐speed wind turbines with permanent magnet synchronous generator (PMSG). Three different drive train mass models and three different topologies for the power‐electronic converters are considered. The three different topologies considered are respectively a matrix, a two‐level and a multilevel converter. A novel control strategy, based on fractional‐order controllers, is proposed for the wind turbines. Simulation results are presented to illustrate the behaviour of the wind turbines during a converter control malfunction, considering the fractional‐order controllers. Finally, conclusions are duly drawn. Copyright © 2010 John Wiley & Sons, Ltd.     

Mesoscale modeling of offshore wind turbine wakes at the wind farm resolving scale: a composite‐based analysis with the Weather Research and Forecasting model over Horns Rev

The use of mesoscale modeling to reproduce the power deficits associated with wind turbine wakes in an offshore environment is analyzed. The study is based on multiyear (3 years) observational and modeling results at the Horns Rev wind farm. The simulations are performed with the Weather Research and Forecasting mesoscale model configured at a high horizontal resolution of 333 m over Horns Rev. The wind turbines are represented as an elevated momentum sink and a source of turbulent kinetic energy. Composites with different atmospheric conditions are extracted from both the observed and simulated datasets in order to inspect the ability of the model to reproduce the power deficit in a wide range of atmospheric conditions. Results indicate that mesoscale models such as Weather Research and Forecasting are able to qualitatively reproduce the power deficit at the wind farm scale. Some specific differences are identified. Mesoscale modeling is therefore a suitable framework to analyze potential downstream effects associated with offshore wind farms. Copyright © 2014 John Wiley & Sons, Ltd.