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With the inclusion of significant wind power into the power system, the unit commitment (UC) has become challenging due to frequent variations in wind power, load and requirement of reserves with sufficient ramp rate. The pumped storage units with lesser startup time and cost can take care of these sudden variations and reduce their impact on power system operation. The aim of this paper is to provide a solution model for UC problem in a hybrid power system.

The model developed has been implemented through GAMS optimization tool with CONOPT solver. The model has been called into MATLAB platform by using GAMS‐MATLAB interfacing to obtain solutions.

The model provides an efficient operating schedule for conventional units and pumped storage units to minimize operating cost and emission. The effects of wind power and load profiles on emission, operating cost and reserve with enough ramping capabilities have been minimized with the use of pumped storage unit. The commitment schedule of thermal and pumped storage units have been obtained with significant wind power integrated into the system for best cost commitment (BCC) and for a combined objective of cost and emission minimization.

This paper finds that the operating cost and emission in a commitment problem can be reduced significantly during variable wind and load conditions in a hybrid system. The model proposed provides operational schedules of conventional and pumped storage units with variable wind power and load conditions throughout operating horizon. The coordinated optimization approach has been implemented on a hybrid system with IEEE‐30 bus system.

The purpose of this paper is to analyze lubrication characteristics of a bidirectional thrust bearing in a pumped storage, considering the effect of the thermal elastic deformation of the pad and collar.

This study used the fluid–solid interaction (FSI) technique to investigate the lubrication characteristics of a bidirectional thrust bearing for several typical operating conditions. The influences of the operating conditions and the thrust load on the lubrication characteristics were analyzed. Then, various pivot eccentricities were investigated to analyze the effects of the pivot position.

It is found that the effect of the radial tilt angle of the collar runner on the oil film is compensated for by the radial tilt of the pad. The central pivot support system is the main factor limiting the loads of bidirectional thrust bearings.

This paper has preliminarily revealed the lubrication mechanism of bidirectional tilting-pad thrust bearings. A three-dimensional FSI method is suggested to evaluate the thermal–elastic–hydrodynamic deformations of thrust bearings instead of the conventional method, which iteratively solves the Reynolds equation, the energy equation, the heat conduction equation and the elastic equilibrium equation.

The purpose of this paper is to reveal the transient thermo-elasto-hydrodynamic lubrication mechanism of a bidirectional thrust bearing in a pumped-storage unit, and to propose the transient simulation method of two-way fluid-solid-thermal interaction of thrust bearing.

The transient fluid-solid-thermal interaction method is used to simulate the three-dimensional lubrication of the thrust bearing, during the start-up and shutdown process of a pumped storage unit. A pad including an oil hole is modelled to analyze the temporal variation of lubrication characteristics, such as the film pressure, thickness and temperature, during the transient operation process.

The injection of the high-pressure oil sufficiently affects the lubrication characteristics on film, in which the hysteresis phenomena were found between the start-up and shutdown possess.

This paper reveals the transient lubrication mechanism of tilting pad in a thrust bearing, by means of transient fluid-solid-thermal interaction method. Lubrication characteristics are simulated without assuming the temperature relationship between the oil film inlet and the outlet and the heat transfer on the pad free surface. This paper provides a theoretical basis for the safe design and stable operation of thrust bearings.

The purpose of this study is to solve the optimal operation strategy problem of plug-in electric vehicles (PEV) parking as a demand response (DR) program and hydro storage as an energy storage system in a smart grid environment using a heuristic algorithm.

Studying the smart grid with DR, renewable energy resources and energy storage systems is necessary. To do this, the heuristic optimization algorithm is developed to solve the scheduling problem. This deterministic algorithm benefits from the definition of appropriate fitness functions.

For validation, it is shown that reduction of 1.1%–12.5% in pollution and 8.8%–34.8% in total cost are achieved, as compared with literature. Also, the suggested operation strategy of PEVs parking and hydro storage results in reducing the total cost by 6.21%.

DR programs such as PEV parking play a major role in smart grid developments. Also, energy storage systems such as hydro storage lead to better performance of distributed generations and lower costs and pollution by thermal units. However, based on the literature, the effects of PEV parking and hydro storage on smart grid operation strategy are not considered. Therefore, contributions of this study are: effects of hydro storage on the smart grid are considered, effects of PEV parking on the smart grid are considered, a heuristic algorithm is developed to solve operation strategy problem for PEV parking and hydro storage in a smart grid environment.

The purpose of this paper is to study investments in renewable energy projects which are jointly operated with an energy storage system, with particular focus on risk-return characteristics from the perspective of private and institutional investors, taking into account resource risk, energy price risk, inflation risk and policy risk.

To this end, this paper presents a stochastic discounted cash flow model which is then applied to a wind farm with a pumped hydro storage system.

The results show that energy storage systems have the potential to increase the expected present value of future investment cash flows and to hedge (downside) risk. However, to realize this potential, storage systems have to be cost-effective in terms of fixed operation, maintenance, staffing and insurance costs. Also, several key factors are identified which have a considerable influence on the performance of the operation strategy.

The paper contributes to the literature by conducting an analysis of (downside) risk and return of renewable energy investments with a storage system taking into account stochastic policy, resource, inflation and energy price risk.

The purpose of this paper is to solve economic emission dispatch problem in connection of wind with hydro-thermal units.

The proposed hybrid methodology is the joined execution of both the modified salp swarm optimization algorithm (MSSA) with artificial intelligence technique aided with particle swarm optimization (PSO) technique.

The proposed approach is introduced to figure out the optimal power generated power from the thermal, wind farms and hydro units by minimizing the emission level and cost of generation simultaneously. The best compromise solution of the generation power outputs and related gas emission are subject to the equality and inequality constraints of the system. Here, MSSA is used to generate the optimal combination of thermal generator with the objective of minimum fuel and emission objective function. The proposed method also considers wind speed probability factor via PSO-artificial neural network (ANN) technique and hydro power generation at peak load demand condition to ensure economic utilization.

To validate the advantage of the proposed approach, six- and ten-units thermal systems are studied with fuel and emission cost. For minimizing the fuel and emission cost of the thermal system with the predicted wind speed factor, the proposed approach is used. The proposed approach is actualized in MATLAB/Simulink, and the results are examined with considering generation units and compared with various solution techniques. The comparison reveals the closeness of the proposed approach and proclaims its capability for handling multi-objective optimization problems of power systems.

The purpose of this study is to explore the transient characteristics of mixed-flow pumps during startup process.

This study uses a full-flow field transient calculation method of mixed-flow pump based on a closed-loop model.

The findings show the hydraulic losses and internal flow characteristics of the piping system during the start-up process.

Large computational cost.

Improve the accuracy of current numerical simulation results in transient process of mixed-flow pump.

Simplify the setting of boundary conditions in the transient calculation.

The purpose of this paper is to examine the feasibility of an ideal power network that combines many different renewable energy technologies such as wind power, concentrated solar power (CSP) and hydroelectric power. This paper emphasizes in finding the benefits arising from hydrothermal coordination compared to the non-regulated integration of the hydroelectric units, as well as the benefits from the integration of wind power and CSP.

Artificial Neural Networks were used to estimate wind power output. As for the CSP system, a three-tier architecture which includes a solar field, a transmission-storage system and a production unit was used. Each one of those separate sections is analyzed and the process is modeled. As for the hydroelectric plant, the knowledge of the water’s flow rated has helped estimating the power output, taking into account the technical restrictions and losses during transmission. Also, the economic dispatch problem was solved by using artificial intelligence methods.

Hydrothermal coordination leads to greater thermal participation reduction and cost reduction than a non-regulated integration of the hydrothermal unit. The latter is independent from the degree of integration of the other renewable sources (wind power, CSP).

Hydrothermal coordination in a power system which includes thermal units and CSP for cost and emissions reduction.

Reverse osmosis (RO) has become an important method of desalination to meet the ever-growing water needs around the world. Its integration with renewable energy source (RES) reduces the environmental impact of gas emissions and cost of conventional fossil energy sources. The optimal sizing of energy sources to power RO desalination system is intended mainly to minimize the annualized cost of the system and by extension minimize freshwater cost while maximizing production.

In this study, a mathematical optimization approach is used to determine the optimal energy mix, which includes grid power, diesel generator and a photovoltaic (PV) module to supply an RO desalination unit. Three cases of optimal sizing approach were compared. Case 1 is a system with only grid power and diesel generator as energy sources; Case 2 has PV incorporated in the energy supply mix while Case 3 has the three energy sources and a Time of Use (TOU) demand response program on the demand side.

The results of implementing the optimization models show that Case 3 turnout the highest freshwater production (1,521 m³/day) at a unit cost of 1.36$/m³ when compared to Case 1 with daily freshwater production of 1,250 m³/day at a unit cost of 1.68$/m³ and Case 2 having a daily freshwater production of 1,501 m³/day at a unit cost of 1.33$/m³.

The integration of RES to power desalination system with application of TOU demand response is the significance of this study.

This paper aims to present a forecast for renewable energy production in the USA. Growth curves are used to conduct the forecasts.

The analysis is based upon a literature review, supplemented by collection of secondary data. The study then focuses on applying the Pearl growth curve.

The authors' results show that biomass energy production is growing the fastest followed by geothermal and wind. Additionally, the forecast for solar energy production shows little to no growth over the next two decades.

If the US government hopes to achieve its goals in renewable energy, considerable funding and incentives will have to be put forth to accelerate the growth of renewable energy. Since the biomass technology is already growing nicely it makes sense to put the additional resources behind the other three technologies to close the 10.3 percent gap being forecasted. The government also needs to put more funding into dual renewable plants such as wind or solar combines with pumped hydro, this will ensure environmental and reliability are both maintained. Finally, for renewable energies to be competitive in the long term, considerable research needs to go into driving down the cost so there is not a need for subsidies.

This study provides value in providing a forecast for expected future growth for renewable energy sources.