Modeling and Simulation of Pico-Hydro Power Plant. Case Study in Southern Carpathians

Transcription

1 Modeling and Simulation of Pico-Hydro Power Plant. Case Study in Southern Carpathians CAMELIA BARBU, ADRIAN DINOIU, PETRE VAMVU Department of Control Engineering, Computers, Electrical and Power Engineering University of Petrosani 2 University Street, 3326, Petrosani ROMANIA tabacarucamelia@yahoo.com, adidinoiu@yahoo.com, petre_vamvu@yahoo.com, Abstract: - In this paper the pico hydro power plant implementation is presented using the systemic approach and based on the environmental conditions. For that purpose an algorithm is designed to determine the structure and possibilities of a pico-hydro power implementation. This paper presents a case study from the Romanian Southern Carpathian Mountains, the Jiu Valley. An analysis is performed starting from the local environmental conditions using modeling and simulation methods, to see how this system can be implemented. There is proposed a block diagram of the control unit, control algorithm and operation simulation. The results are validated by comparing experimental data with similar data from literature. Key-Words: - Flow forecasting, hydrological model, modeling, simulation, systemic approach. 1 Introduction There are many pico hydro arrangements (in our country and abroad), but most of them are facing the water resource management problem. During wet season the water is used irrationally while in dry season the water resource doesn t exist. So, it is very important to estimate a flow variation forecast of the water resource where the pico hydro turbine will be installed, starting from the real precipitation and hydrographic data. Hydro electric turbines are the most efficient and cost effective systems for producing electricity from renewable resources. If a small river is available, that can provide a few liters / sec with a level difference at least 3 m, renewable and clean electricity can be obtained with minimal costs. For this, the environment and the river will have to be prepared and cared for, which is also a great environmental benefit. A feasibility study must be conducted in order to implement a pico-hydro power plant, starting with the evaluation of the real precipitation data acquired from the specific area. The data provides an overview of the rain patterns and annual precipitation fluctuations, models of the water cycle in the local area. Feasibility of such a project (fig. 1) can be viewed from a systemic approach, by analyzing the following problems: water cycle model, parameters determination, equipment choice and determining investment. Fig. 1. The feasibility study for a pico-hydro power plant implementation Some parts of the feasibility algorithm have alternatives that can improve energy efficiency, but can increase the investment costs. For these reasons the last design stage requires investment cost optimization, for example applying linear programming methods. ISBN:

2 2 Problem Formulation Without a forecast of the water resource, investing isn t approachable no matter how small it is. For a systemic approach, the first step is to analyze the flora area, geographic location and hydrological data over a long period (5-1 year, any disturbances that occurred and their consequences, any arrangements, afforestation and greening etc. Data about solar radiation and circulation of clouds, rain and torrents formation is collected. The water cycle is responsible for the renewal of the water resource. For quantitative analysis of water flow in the area a hydrological forecasting model is designed with 3 accumulations (fig.2), according to the systems theory. Fig. 2. Hydrological model: a) Area of study; b) Conceptual model; c) Block diagram These model allow us to analyze the phenomenon of evaporation, clouds formation and river flow, as a hydro energy resource. Each water flow and storage has an input and output flow. The input vectors (q i, q d, q e ) are used for infiltrations, direct and exfiltrations, output vectors (q u, q o, q) for underground, surface and river. The vectors (α, β, γ) represent the fraction of the amount of net rain for each input vector, and Ti, To, T are time constants for the accumulations. Each accumulation is a first order element with: qout ( G( (1) qin( Based on the block diagram, the following transfer function is obtained: q( a + a1 s G( (2) 2 3 qr ( b + b1 s + b2 s + s where the coefficients are: a α + β + γ T T i α + ( β + γ ) i + Ti a1 T b 1 T i T i (3) (4) (5) T + Ti + T b1 (6) T i T i + T + Ti b2 (7) T i The state equations of the forecast model in the observer version are: x 1 b2 1 x1 + x 2 b1 1 x2 a1 qr (8) x 3 b x3 a q x1 The above coefficients can be estimated based on the experimental data. The hydrological simulation model of flow variation over a period of time is obtained using these equations. The resulted parameter vectors are useful when preparing a package of measures to manage the water resource and ecological rehabilitation of the area. Also, measures for increasing energy efficiency can be used, like afforestation, albedo reduction, greening, hydrological arrangements etc. 3 Problem Solution Pico-hydro turbines can be installed either in area with high slope, where the rivers are fast and have low flow rates, or in lower areas with higher flow. As we know, hydroelectric power is proportional to the product of water flow Q [m 3 /s] and the height of the water source called head, h [m]. P[ W ] η g Q h (9) where η is the total efficiency of pico-hydro plant (η ) and g is gravitational acceleration (g 9.81 m/s 2 ). Head h is a constant of arrangement and it should be reduced by the pressure loss that occurs to the forced pipe. With h, flow velocity v [m/s] and diameter of pipelines d [m] or flow Q [m 3 /s] are determined using the following equations: v.97 2 g h (1) 4 Q d π v (11) ISBN:

3 2 v d Q π (12) 4 The turbine generator produces DC power which is then stored in batteries and should allow autonomy of 1-2 days. The electrical system of pico-hydro power plant consists of two parts: the power unit (generator, breaker, with the necessary protections, batteries and inverter) and the control unit (controller). These systems work automatically using a PLC (Programmable Logic Controller). Fig. 3 represents the block diagram of the control unit, control algorithm and operation simulation. Fig. 3. The control system: a) The block diagram; b) The algorithm For the application, let s consider a case study that applies the design algorithm of a pico-hydro power plant in a mountainous area of the Southern Carpathians. The area selected is in the northwestern side of the Parang Mountain with one of its rivers, the Jiet, which flows into the Western Jiu River. The Parang Mountains are part of the Southern Carpathians, Parang-Sureanu-Lotru group, the largest mountain chain of Romania. From east to west they measure about 5 km and about 25 km from north to south. The Jiu Valley has a temperate continental climate with wet and cold character, with precipitation in the form of rain and snow that forms its hydrographic network. The Jiu Valley hydrographic network (fig.4) consists of two major rivers: Eastern and Western Jiu, which join at Livezeni - Bumbesti. These two rivers have many branches with sufficient flow for the installation of pico hydro power plants, as follows: Jiet, Taia, Banita, Maleia, Slatioara, Salatruc on the Eastern Jiu and Buta, Pilugul, Braia, Morisoara, Aninoasa on the Western Jiu. ISBN:

4 Fig. 4. Jiu Valley hydrographical basin The case study is based on the following data: Hydrographical basin is about 2 km 2, mostly forest, with vegetation and trees; The mountain area is oriented to the southeast, provides a reserve of water from melting snow until the months April to May; Even if the rainfalls in July-August are reduced, the average flow is sufficient to power a pico-hydro power plant; Clouds are formed mainly in the northwest of the basin and are attracted by currents to produce rain with an average duration of 1-2 hours, at least once a week; The area is isolated and requires an independent electricity supply; There are ways of communication that would allow ecological rehabilitation necessary due to environmental aggression; Water supply arrangement is done with a simple dam with a maximum depth of 2 m and 1 m length with discharge; The average head is 2 m with the average flow 15 l/s; A Turgo hydro turbine 2 W/12 V DC is used; The water flows through the 4 mm diameter forced pipe; A Klöckner Moeller PLC (Programmable Logic Controller) with 6 outputs for control and monitoring is used; The real data of the monthly average rainfall from the local weather station is acquired and used as the inputs for the general model (fig.5). WINTER Months December January February Weeks / month SPRING Months March April May Weeks / month ISBN:

5 SUMMER Months June July August Weeks / month AUTUMN Months September October November Weeks / month Fig.5. The monthly average rainfall local area from Southern Carpathian In the following, the forecast general model is designed for a feasible and working hydro power plant arrangement, the controller and the power stage (fig. 6). The model design is based on the formulas presented above. Fig. 6. The general model and simulation results ISBN:

6 As input in the general model we use the monthly precipitations variation h (obtained from a local weather station), the studied area surface S [km 2 ] and evaporation variation. All the other data was determined on the empirical method, having as outputs the flow Q [l/s], the water level variation of accumulation h [m] and the hydro turbine power P [W]. Although the flow is variable because of the precipitation variations, the output power, the main hydro turbine parameter, is almost constant, when using the controller and the corresponding water level variation. Comparing the above obtained results with others, the advantages are obvious, because a flow forecast is used and based on that, the level and hydro power control is achieved. 4 Conclusion The main contributions of this paper are the systemic theory approach for designing, modeling, simulation and implementation of a pico hydro power plant and the determination the mathematical model that helps in establishing the viability of a pico hydro turbine implementation in a local area. This kind of model can be applied to other areas if the inputs data are known. This data is obtained from local weather stations. Nowadays, it is crucial to all of us to realize the importance of renewable resources in order to obtain green electricity and heat. This must be the main concern of all humankind regardless of their background and age, from teachers to engineers, from children to elderly people. A good approach, for an efficient implementation of a renewable energetic system, is in our opinion, the systemic approach, starting from modeling and simulation to implementation. As we demonstrated, the implementation of a pico hydro system in the studied area it s viable and can be a clean source for local electricity and heat for many years. References: [1] Badea A., Pop E., Badea F., VHDL Code Generation Based on a Hierarchical Node Structural, Proceedings of the 11th WSEAS Interantional Conference on Data Networks, Communications, Computers (DNCOCO 12), Sliema, Malta, September 7-9, 212, ISBN , 212. [2] Bolton W., Control engineering, Addison Wesley Longman Limited, England, ISBN , [3] Maher P., Smith N., Pico hydro for village power: A practical manual for schemes up to 5 kw in hilly areas, UK Department for International Development (DfID), 21. [4] Patrascoiu N., Tomuş A.M., Rosulescu Cecilia, Using Thermocouples in Programmable Systems for Temperature Measuring, Annals of the University of Petroşani. Electrical Engineering. Vol 1 (XXXVII), pag. 73-8, ISSN , 28. [5] Patrascoiu N., Modeling and Simulation of Systems (Modelarea si simularea sistemelor), Editura FOCUS, Petrosani, Romania, ISBN , 21. [6] Pop E., Control engineering in mining industry (Automatizari in industria miniera), Editura Didactica si Pedagogica, Bucuresti, Romania, [7] Pop E., Bubatu R., Teoria Sistemelor. Educatie prin e-learning, Editura Universitas, 212. [8] Pop M., Masurari electrice, Lecture Notes, University of Petrosani, 212 [9] Sochirca B., Poanta A., Dedicated Microcontroller for Multi Drives Control, Proceedings of the 11th WSEAS Interantional Conference on Data Networks, Communications, Computers (DNCOCO 12), Sliema, Malta, September 7-9, 212, ISBN , 212. [1] Seely B., Kimmins J.P., A forest hydrology model for simulating the effect of stand management and climate change on forest water dynamics, University of British Columbia, Forest Sciences Department, 23. [11] Williams A., Pico hydro for cost-effective lighting, Boiling Point Magazine, pp , 27. [12] Whitehead D., Hinckley T.M., Models of water flux through forest stand: critical leaf and stand parameters, Oxford Journal, Life Sciences, Tree Physiology, 9(1-2), 35-57, [13] Hazem M. El-Bakry, Nikos Mastorakis, A new fast forecasting technique using high speed neural networks, Transactions on Signal Processing, 28 [14] Dunca E. - The Role of the Geo-synthetics in the Process of Byological Recultivation of the Ribiţa Settling Pond. 9th International Symposium Continuous Surface Mining, Petroşani, 28 ISBN: