Integrating GIS technologies in hydro power plant cascade simulation model

. The paper presents the calculation algorithm for water-energy regime of a hydroelectric power plants cascade. The block diagram of the algorithm is given for implementing the simulation model and automating the process of calculating the regime. The proposed algorithm allows to evaluate the efficiency of the cascade, as well as to optimize the regime according to various criteria. Additionally, an option is proposed for integrating GIS monitoring data into the calculation algorithm.


Introduction
Simulation modeling is a research method in which the system involved is replaced by a model that describes the real system with sufficient accuracy (the model describes the processes as they would be in reality), with which experiments are conducted in order to obtain information about this system.
Simulation modeling, at present, has become widespread and is presented in diverse types of studies: business processes, population dynamics, traffic, rail transportation, market and competition, healthcare, engineering and many others. If the control object is a hydro power plant (HPP) cascade, process modeling should take into account not only various control algorithms for this facility, but also changing input parameters driven by natural conditions.
In the theory of simulation modeling, three main methods are distinguished: discrete event modeling, agent modeling and system dynamics. For complex systems involved, multi-approach models can be used.
HPPs are complex, artificially created open-type systems with specific properties: the probabilistic nature of parameters that change over time, close relationships with social, economic, and natural factors. The complexity of the production process, the duration of operation and the variability of the natural factors impact during the year make it urgent to create a simulation model of a HPP. The simulation model allows replacing full-scale tests, -playing over‖ and analyzing many states, adjustment of operating modes [1].
The authors elaborated a simulation model that combines the hydraulic and electric modes of the electric power system [2]. When modeling the operating modes and status of the HPP reservoir, it is important to use reliable statistical information. Actual input information, as well as its short-term and long-term forecast can be obtained on the data of territory spatial monitoring system, technologies of geoinformation modeling.
Often, data from ground-based surveillance tools are costly, and provide an insufficient coverage area (both in territorial and temporal aspects) [3]. The optimal solution would be the use of earth remote sensing (ERS). As a rule, earth remote sensing data refer to satellite images obtained from man-made Earth satellites that have undergone processing and are a raster image of the Earth's surface, as well as a spatial image data file [4]. ERS data are available for any territory and, accordingly, for any existing or planned HPP. An additional advantage is that this information with the accuracy sufficient for scientific research is freely available. ERS data can be used in conditions where ground-based research methods are impossible, for example, mountainous terrain, remote areas, glacial drifts, etc. ERS data are used as the basis for geographic information systems (GIS).

ERS opportunity analysis
Herewithin it is necessary to evaluate the possibilities of ERS by applicability in calculating the regime of a HPP cascade and also narrow down the list of possible source data to the most significant parameters for the simulation model. The scheme for integrating GIS technologies into the simulation model is presented in Figure 1. Conventionally, ERS data relevant to the described problem can be divided into two categories: geographical and climatic. The first category includes: 1. Relief geometric parameters. Based on a digital relief model, using geographic information systems, a number of derived parameters can be obtained that comprehensively describe a specific place on the Earth's surface [5] (Figure 2): slope -a value that determines the steepness of the relief and representing the maximum variability coefficient of the current cell of the digital relief model, relative to neighboring cells. It is taken into account, for example, when calculating the water flow speed; exposure -the direction of the cardinal directions in which the plane of the slope is oriented for each cell of the digital relief model. Most often it is taken into account when determining the amount of sunlight received by this part of the slope, or the flow direction; curvature -a value indicating the degree of concavity or convexity of the surface, which is used in calculating the position of the catchment areas; topographic position index (TPI) -the calculated complex value of the excess index, which allows to determine the characteristics and classify watersheds, slopes and relief elements.
Given the study object, these parameters are important in assessing: • volume of water in the river network; • flow direction; • provisions of areas in case of precipitation; • estimated amount of melting snow based on its position relative to the prevailing direction of solar irradiation.
2. Hydrographic objects geometric parameters. These include: water-surface area and the width of the dam site.
The geometrical parameters of hydrographic objects are subject to change and will depend on the date of the study. To calculate geometrical parameters, it is necessary to select the boundaries of hydrographic objects on satellite images by manually indicating the contour, or by automatically selecting pixels based on some automated decryption algorithm (Figure 3).
The parameters of the geographical group are basic. By combining them, an additional system of hydrological parameters will be obtained (watercourses, flow directions and cumulative flow points, catchment areas), which can also be used to construct a simulation model of the HPP cascade.
The second category includes: 1. Temperature. Two options can be used in the calculations -the air temperature obtained from meteorological stations and the earth's surface temperature obtained from satellite images based on thermal spectral channels [6,7] (Figure 4).
3. Quantitative indicators of the snow cover of the territories forming the runoff of the analyzed river -the snow cover surface and its thickness, based on the indirect parameter of the water equivalent ( Figure 5). These indicators are important for medium and longterm forecasting [11,12].
A summary of possible source data is given in Tables  1 and 2. It should also be noted that since all the parameters described above are based on raster representation data, the resolution is indicated for a basic assessment of their planned accuracy.

ERS integration in HPP regimes modeling
Using geographic and climatic data, it must be taken into account that most of them are three-dimensional matrices containing in total millions of parameter values, and it is not possible to use them in their original form for most algorithms and mathematical models. In addition, the initial data and their sources are selected in such a way that for each of the criteria and for each analyzed section of the area it was possible to obtain a number of retrospective values. Thus, we obtain the analyzed data presented in the form of four-dimensional matrices. Therefore, in the study, it is necessary to consider and analyze possible ways of reducing the dimension of each of the parameters and taking into account the past values of the parameters (in the form of the values themselves, the rate of change, the difference between the forecast and true values, etc.). GIS monitoring data provide accurate and up-to-date information on the hydrological, hydrographic, and climatic parameters of the river with a high refresh rate. At the design stage, the use of GIS technology will increase the accuracy of calculating the design parameters of HPPs and reservoir capacity. During the operation of a HPP, the use of an ERS database will increase the accuracy of predicting the natural inflow to the HPP site, as well as losses caused by natural factors. A list of possible tasks solved on the basis of ERS data is shown in Figure 6.

Result and Discussions
Let's consider the tasks in more detail.
1. One of the most important tasks at the stage of HPP designing is to determine the useful volume of a plant's reservoir.
The parameters of the reservoir directly depend on the terrain, and its area can extend to hundreds of km 2 . Using satellite information is faster, has a greater coverage of the territory and often more accurately than traditional methods allows determining the reservoir flood zone and calculating its characteristics.
The use of GIS technologies will automate the constructing a correlation curve between the level of the upstream (the mark of the height of the water level in HPP site) and the volume (surface) of the reservoir. This curve describes the dynamics of changes in water reserves and the level of the HPP upstream. The volume of water that is pumped or stored in the reservoir determines the level of water flow through the HPP, which leads to a change in power and the amount of electricity generated. The HPP operation without a predetermined curve between the level of the upstream and the volume of the reservoir is impossible.
Similarly, a correlation curve between the downstream level and the flow rate can be constructed. An example of the correlation curves of the upstream and downstream is shown in Figure 7. The solution to the correlation curves tracing is relevant not only for HPP under construction. On the territory of Russia and the CIS countries there are hydroelectric power plants that do not have accurate information about the parameters of their own reservoirs, or reservoirs data has undergone changes over many years of operation. In this case, monitoring of the hydrographic parameters of the alignment will make it possible to correct the data available to the plant staff, which will lead to an increase in the efficiency of controlling plant modes.
2. Data on surface curvature and distance between plants should remain a priority. They can be used to calculate the time it takes for a wave to travel from one plant to another. This will allow more accurate calculation of time corrections in the HPP connected in a cascade operation mode. Formula for calculating the wave travel time: where L -distance between first and second plant, flow speed.
The flow speed directly depends on the slope of the river and the hydraulic radius of the channel: where С -speed coefficient, mean R -average hydraulic radius of the river channel in the area between the cascade HPPs, mean J -average river slope.

3.
At the stage of HPP operation, a special role is given to the tasks of short-term and long-term planning of HPP regimes. The regime planning is based on the forecast of changes in runoff parameters, based on the identification of patterns of change in natural factors within the considered time interval, using the statistical information for the previous stages of observations.
So, based on data on snow cover reserves and temperature changes during the year, a model for predicting inflow to the reservoir site can be constructed. Data on changes in reservoir surface and ambient temperature can be used to calculate evaporation and ice formation losses. To calculate the average water loss for ice formation, you can use the following: where Ii h -ice depth, I  = 0,9 -ice density, Freservoir surface at various elevations, w t -the length of the winter period, determined by the period of the reservoir. The water losses by evaporation are determined by: The data obtained are used to adjust the operating mode of the plant. The algorithm for calculating the operational parameters of the HPP based on the forecast of inflow to the hydroelectric power plant and the requirements of the power system is presented in Figure 8.
Let's consider the blocks of the algorithm in detail.  where i R и i J -hydraulic radius and slope of the river section. L -distance between HPPs.
The use of a GIS monitoring system allows to accurately determine the geographic parameters of the river channel between plants, which makes it possible to increase the accuracy of the travel time calculation and to exclude the corresponding errors.

Conclusions
The planning of electric power systems with a large share of hydrogeneration long-term and short-term operation modes is inextricably associated with waterenergy calculation. It is possible to increase the effectiveness of plans with the correct consideration of climatic and geographical parameters through the use of GIS monitoring. Creating a simulation model of a HPP cascade with the ERS integration gives advantages in HPP actual parameters calculating.