INTEGRATED SCHEDULING OF SOLAR AND WIND ENERGY WITH PUMPED STORAGE

Abstract

Today, world is facing environmental challenges for meeting the energy demands. The steep rise in prices of hydrocarbon fuels, depleting fossil fuel resources, and climate change have thrown doubt on the future usage of traditional energy sources such as coal, oil, Nuclear etc. Solar, wind, biomass and hydro renewable energy sources are environmentally benign, relatively cheaper, available globally and have long-term advantages. India, like other nation, has made many changes and adopted policies to accelerate the growth of renewable energy. Among the various renewable sources of energy, solar and wind power are growing at the highest pace globally including India. Despite the obvious benefits of solar and wind energy, their variable and intermittent nature pose significant challenges to power system operation. Solar-Wind-Pumped Storage plant system (SWPS) is an integrated system comprising of power generated from solar and wind together with pumped storage plant (PSP). This combination ensures improved quality, performance, and reliability of the power delivered together with cost-effective development and operation of these sources. The present study aims to develop optimal schedule for an integrated SWPS, such that profit is maximized while taking into account its predicted generation of the following day. Also, the market imbalance is decreased by managing the variations in the electrical energy from solar and wind sources while considering the energy available in the grid and PSP. An hourly schedule for a day, has been investigated for a SWPS system from the state of Gujarat, India. A mixed-integer type model is developed to optimize the hourly power commitments from SWPS while meeting the various diverse constraints. Four cases have been considered. Initially the simplest Case-I, is taken to maximize the profit of the system supplying energy generated by combination of solar and wind only. For Case-II, solar-wind system integrated with a PSP with fixed speed pumping is used to maximize the profit. Case III is taken with PSP pumping at two different speeds. Case-IV is considered, where pumping in PSP is done at variable speeds, which leads to further reduction in market imbalance caused by the solar and wind systems.The stochastic algorithm is an efficient tool to reach optimal solution for optimiza tion problems linked with uncertainties. The input data represent different instances and prob ability of their occurrence, which can be obtained by representing the random variable with a probability distribution function (PDF). Hence, stochastic method can be used for finding optimal schedule for different case scenarios. To simplify the computation process, PDF for each random variables is discretized by dividing it into different intervals to construct different states, which are then blended to produce a scenario set. Ascheme involving Taguchi method has been utilized for computing and managing uncertainty risk. An approach using an orthogonal array-based structure was developed and is simple in modeling and requires minimal computational time as it needs a small number of tests. Results obtained show that profit increased by 50 % in solar-wind-PSP scheduling with fixed speed operation as compared to SWPS operation without PSP. Further, compared to fixed-speed operation, with two-speed and variable speed operation, the profit of the inte grated SWPS enhanced to 61 % and 65 % respectively. Compared to fixed speed, two speed operation, the variable speed operation reduced the pumping charges by 37.5 % and 28.5 % respectively. Considering the uncertainty in the solar and wind generation, from the analysis, it is found that compared to fixed speed and two-speed operation of the PSP, the variable-speed operation reduced the pumping charges by approximately 17 % and 2.8 % and the imbalance penalty has also been reduced by 5 % and 3.4 % respectively. The variable-speed operation increased the profit by approximately 8.5 % and 3.0 % compared to fixed and two-speed operations, respectively. The orthogonal array technique employed fewer experiments to save computation time and reduced the operation risk by 10.6 % for the SWPS under solar and wind data un certainty. The main benefit of this technique is that it allows the creation of a SWPS that can tolerate higher level of risk while maintaining consistent performance under variable condi tions. For mixed-integer optimization, General Algebraic Modeling System (GAMS) con tains a number of solvers. The solvers CIPLEX, DICOPT, and GUROBI have been investi gated for optimization. The CPLEX solution outperforms DICOPT and GUROBI in terms of profit maximization for both two speed and variable speed cases considered. Compared to the two-speed operation, the variable speed operation resulted in increased profit by 4.5 %. The pumping charges for using grid power has also been reduced by 13 %. The study shows that PSP can be effectively used to manage the uncertainties linked with the solar and wind power. Theproposed integrated Solar-Wind-PSP model can be utilized for the day-ahead energy market scheduling and decision-making process by generating utilities.