Sharif Digital Repository

Stand-alone hybrid power systems are an alternative to main electricity grids, where the grid extension is costly or the trifling local consumption would not justify its expansion. However, lack of consistency and uniformity in renewable energy sources, and the restrictions of energy storage systems make system sizing a challenging task. Optimum size of a stand-alone system depends on several factors including energy demand function. In this paper, different types of demand functions are addressed for optimising a solar-hydrogen supply system. Different parameters are defined to investigate the impact of household population on the power generation cost, and also to determine the optimum... 

Stand-alone hybrid power systems are an alternative to main electricity grids, where the grid extension is costly or the trifling local consumption would not justify its expansion. However, lack of consistency and uniformity in renewable energy sources, and the restrictions of energy storage systems make system sizing a challenging task. Optimum size of a stand-alone system depends on several factors including energy demand function. In this paper, different types of demand functions are addressed for optimising a solar-hydrogen supply system. Different parameters are defined to investigate the impact of household population on the power generation cost, and also to determine the optimum... 

The combination of concentrating photovoltaic (CPV) and organic Rankine cycle (ORC) systems not only leads to a reduction of photovoltaic (PV) operating temperature, but also leads to an additional electric power production. Increase in the temperature of the PV decreases its operating efficiency, while increases the ORC efficiency. Therefore, there is an optimum temperature in which the total electricity produced by the combined system will be maximum. In this study, a modified CPV/ORC system is simulated and the optimum operating temperature of the PV panel is determined for different PV efficiencies. The most striking result is that increase in the PV nominal efficiency will result in the... 

Stirling engines operate in a variety of temperatures and the electric power production via dish Stirling systems could be considered as an appropriate alternative for high-temperature solar concentrator energy harvesting systems. To this end, by performing various studies and analyses on the engine, Stirling cycle, and heat exchangers while utilizing the solar energy as the input thermal energy of the Stirling engine, parameters with the highest effect on the output power and engine stability are detected and considered as optimization variables. In this case, output power, thermal efficiency, and economic evaluation are taken to be the three suitable objective functions for multi-objective... 

The combination of concentrating photovoltaic (CPV) and organic Rankine cycle (ORC) systems not only leads to a reduction of photovoltaic (PV) operating temperature, but also leads to an additional electric power production. Increase in the temperature of the PV decreases its operating efficiency, while increases the ORC efficiency. Therefore, there is an optimum temperature in which the total electricity produced by the combined system will be maximum. In this study, a modified CPV/ORC system is simulated and the optimum operating temperature of the PV panel is determined for different PV efficiencies. The most striking result is that increase in the PV nominal efficiency will result in the... 

Stand-alone hybrid power systems are an alternative to main electricity grids, where the grid extension is costly or the trifling local consumption would not justify its expansion. However, lack of consistency and uniformity in renewable energy sources, and the restrictions of energy storage systems make system sizing a challenging task. Optimum size of a stand-alone system depends on several factors including energy demand function. In this paper, different types of demand functions are addressed for optimising a solar-hydrogen supply system. Different parameters are defined to investigate the impact of household population on the power generation cost, and also to determine the optimum... 

This article explores the application of a wind farm layout optimization framework using a particle swarm optimizer to three benchmark test cases. The developed framework introduces an increased level of detail characterizing the impact that the wind farm layout can have on the levelized cost of energy by modelling the wind farm’s electrical infrastructure, annual energy production, and cost as functions of the wind farm layout. Using this framework, this paper explores the application of a particle swarm optimizer to the wind farm layout optimization problem considering three different levels of wind farm constraint faced by modern wind farm developers. The particle swarm optimizer is found... 

This paper reviews the merits of modernizing the power grid and discusses the way electric utilities in various countries are directing their practices toward offering enhanced sustainability, reliability, resilience, security, and economics to their respective consumers. The modernization of the electricity grid, which has evolved as the brainchild of electricity restructuring, has been made all the more urgent by the virtually pervasive dependence of modern lives on a reliable, clean, and secure supply of affordable electricity. The electric utility industry restructuring, which has staged many institutional, regulatory, and business models, has enabled the modern electricity grid to take... 

Excitation Controlled Synchronous Generator-based Wind Turbine (ECSG WT) is a recently proposed Wind Turbine (WT) scheme that has not been fully investigated in detail. This paper intends to analyze the performance of the ECSG WT scheme and compare it with those of two mainstream WT schemes based on electrically excited synchronous generator, i.e., VSC-based full converter WT and diode bridge rectifier-based WT equipped with boost converter on its Direct Current (DC) link. The objective of this comparison is to demonstrate great potentials of ECSG WT to be considered in the wind industry. To do so, two successful Wind Turbine (WT) schemes in the market that are structurally close to ECSG WT... 

Demand response (DR) is known as a key solution in modern power systems and electricity markets for mitigating wind power uncertainties. However, effective incorporation of DR into power system operation scheduling needs knowledge of the price–elastic demand curve that relies on several factors such as estimation of a customer’s elasticity as well as their participation level in DR programs. To overcome this challenge, this paper proposes a novel autonomous DR scheme without prediction of the price–elastic demand curve so that the DR providers apply their selected load profiles ranked in the high priority to the independent system operator (ISO). The energy and reserve markets clearing... 

Electricity demand forecasting has been a real challenge for power system scheduling in different levels of energy sectors. Various computational intelligence techniques and methodologies have been employed in the electricity market for short-term load forecasting, although scant evidence is available about the feasibility of these methods considering the type of data and other potential factors. This work introduces several scientific, technical rationales behind short-term load forecasting methodologies based on works of previous researchers in the energy field. Fundamental benefits and drawbacks of these methods are discussed to represent the efficiency of each approach in various... 

This paper focuses on expansion co-planning studies of natural gas and electricity distribution systems. The aim is to develop a mixed-integer linear programming (MILP) model for such problems to guarantee the finite convergence to optimality. To this end, at first the interconnection of electricity and natural gas networks at demand nodes is modelled by the concept of energy hub (EH). Then, mathematical model of expansion studies associated with the natural gas, electricity and EHs are extracted. The optimization models of these three expansion studies incorporate investment and operation costs. Based on these separate planning problems, which are all in the form of mixed-integer nonlinear... 

This paper focuses on expansion co-planning studies of natural gas and electricity distribution systems. The aim is to develop a mixed-integer linear programming (MILP) model for such problems to guarantee the finite convergence to optimality. To this end, at first the interconnection of electricity and natural gas networks at demand nodes is modelled by the concept of energy hub (EH). Then, mathematical model of expansion studies associated with the natural gas, electricity and EHs are extracted. The optimization models of these three expansion studies incorporate investment and operation costs. Based on these separate planning problems, which are all in the form of mixed-integer nonlinear... 

In this paper, a new transmission expansion planning (TEP) model considering wind farms (WFs) optimal integration to power systems is proposed based on the information-gap decision theory (IGDT). The uncertainties of WFs output power and forecasted demand are considered in the problem, and IGDT is used to control the investment risk as well as to reduce the effects of these uncertainties on the investors' strategies. The TEP model is formulated for the risk-averse and risk-seeker investors through the robustness and opportunity models, respectively. Moreover, this TEP model allows WF lines and network lines to be added at multiple time points during a multi-stage time horizon. A genetic... 

This paper introduces a new fuzzy-based design procedure for more efficient application of reward-penalty schemes in distribution sector. To achieve a fair as well as applicable regulation scheme, the fuzzy C-means clustering algorithm is employed to efficiently determine the similarity among distribution companies. As setting procedure of the reward-penalty scheme parameters can significantly affect the income of different companies, a new procedure based on the membership degrees obtained from the fuzzy C-means algorithm is proposed to fairly determine these parameters for each electricity distribution company. Some numerical studies are performed on the Iranian electricity distribution... 

We study the application of cooperative control and game theoretic approaches to wind farm optimization. The conventional (greedy) wind farm control strategy seeks to individually maximize each turbine power. However, this strategy does not maximize the overall power production of wind farms due to the aerodynamic interactions (wake effect) between the turbines. We formulate the wind farm power optimization problem as an identical interest game which can also be used to solve other cooperative control problems. Two model-free learning algorithms are developed to obtain the optimal axial induction factors of the turbines and maximize power production. The algorithms are simulated for a... 

We study the application of cooperative control and game theoretic approaches to wind farm optimization. The conventional (greedy) wind farm control strategy seeks to individually maximize each turbine power. However, this strategy does not maximize the overall power production of wind farms due to the aerodynamic interactions (wake effect) between the turbines. We formulate the wind farm power optimization problem as an identical interest game which can also be used to solve other cooperative control problems. Two model-free learning algorithms are developed to obtain the optimal axial induction factors of the turbines and maximize power production. The algorithms are simulated for a... 

Electric power systems try to maximize resilience by various enhancement strategies as preventive and corrective actions against extreme weather events. This paper presents an operational network reconfiguration strategy during a high wind event to strengthen the resiliency of distribution networks. In the proposed resilience enhancement strategy, a bi-level optimization problem is formulated with two conflicting objectives (i) maximizing grid resilience and (ii) realize the primary objective by a minimum number of out-of-service lines (OSLs) switching operations. Furthermore, the algorithm considers the priority of loads, which is an important characteristic of modern distribution grids.... 

Increasing the intermittent outputs of renewable energy sources (RESs) has forced planners to define a new concept named flexibility. In this regard, some short- and long-term solutions, such as transmission expansion planning (TEP) and energy storage systems (ESSs) have been suggested to improve the flexibility amount. A proper optimization procedure is required to choose an optimal solution to improve flexibility. Therefore, a mixed-integer linear programming (MILP) direct-optimization TEP versus ESSs co-planning model is presented in this paper to enhance power system flexibility. In doing so, a novel RES-BESS-based grid-scale system flexibility metric is proposed to investigate the... 

In most of the existing studies, the frequency response in the variable speed wind turbines (VSWTs) is simply realized by changing the torque set-point via appropriate inputs such as frequency deviations signal. However, effective dynamics and systematic process design have not been comprehensively discussed yet. Accordingly, this paper proposes a proportional-derivative frequency controller and investigates its performance in a wind farm consisting of several VSWTs. A band-pass filter is deployed before the proposed controller to avoid responding to either steady state frequency deviations or high rate of change of frequency. To design the controller, the frequency model of the wind farm is...