Location of Energy Storage Units

Transcription

1 Location of Energy Storage Units Base-Load Generation Scenarios Dimitrios I. Doukas, Antonios Marinopoulos and Panagiotis Bakas ABB AB Corporate Research Västerås, SE-72178, Sweden Abstract Energy Storage is typically proposed as an efficient way to overcome the problem of intermittency of renewable energy sources. Lately, in parallel with the increase of PV installed capacities and with larger in size power plants, different operation scenarios of PV plants came to the fore and are worth of detailed investigation. A typical example of alternative approaches of combining energy storage with utility-scale PV power plants is the base-load operation scenario. Thus, PV power plants are combined with Energy Storage, in order to provide constant power level for predetermined time period. Energy Storage Sizing results from previous research activities for six locations of favorable meteorological characteristics have been used as inputs for the needs of this paper. [1] The main target is to economically evaluate scenarios of integrating energy storage in different parts of a grid connected PV power plant. Based on this evaluation possible cost savings that could justify an extended use of energy storage and balance the increased investment cost can be identified. The whole analysis takes into account voltage level and cost of transmission and concludes with a proposal of where and how Energy storage should be included within a PV power plant in the order of GW for base-load operation. Keywords- energy storage, photovoltaic power systems, distributed power generation, base-load generation. I. STUDY OBJECTIVES & APPROACH Large-scale penetration of renewables to the grid may result in power quality and security concerns because of their intermittent and unpredictable nature. Energy storage could be used, to deal with these issues, to decongest electricity grids when operated as distributed units and to benefit from the fluctuation between on and off-peak electricity prices. Especially, for utility-scale PV power plants, energy storage could be used for base-load generation purposes in order the PV power plant to adopt a generation profile similar to the conventional and dispatchable power plants. There are several alternative ways to approach the baseload generation implementation that depend on the power level and the time period needed from the grid operator and / or chosen by the PV plant owner. Although extended research has been done based on different operation technics, this paper focuses on what we call annual and monthly daylight period base-load respectively. [1] Annual means operation at the same constant power level for the whole year, while monthly means constant power generation during a whole month, but in different power level for the twelve months, depending on each month s maximum solar energy potential. On the other hand, daylight means that the PV plant will provide a constant power output instead of the typical PV curve- for the period of daylight. Explanatory graph follows, (Fig. 1). Figure 1. "Daylight" Base-Load The purpose of this paper is to deal with positioning of Energy storage scenarios - as a bulk unit or as a set of distributed units before or after the transmission line or even inside the PV power plant - in parallel with the most appropriate choice of voltage level of transmission line (132kV, 220kV and 400kV cables or OHL). In Fig. 3, possible placements of Energy storage are indicated (point C: Storage after transmission as bulk unit, point B: Storage before transmission as bulk unit, points A: Storage distributed inside PV plant). The main idea is that Energy storage integration in a utility-scale PV power plant, especially for base-load operations, results in operation at power levels approximately equal to 45%-55% of peak values (Fig. 1). Thus, since the power level will be always lower than the peak value, transmission dimensioning and costs could be calculated for lower power values as well. Lower capacity transmission results in lower financial cost that could possibly justify, or at least compensate, the extended use of expensive energy storage in such parks. The tool that was implemented for the needs of this paper is based on energy storage sizing results from previous research activities and will propose best location practices of energy storage within similar PV power plants and the best voltage level for the power transmission in terms of cost savings. [1,2] The energy storage sizing results, expressed as a percentage of the PV installed capacity, for all locations and scenarios are shown in the following figure (Fig. 2).

2 132kV, 220kV and 400kV are compared for every scenario. The final output is the transmission cost for each case including reactive compensation cost for large transmission distances. In addition, the total number of parallel transmission circuits, which could be up to 6 in case of 132kV, is also provided as output. Figure 3. Placement of Energy Storage Figure 2. Energy Storage Sizing III. RESULTS TRANSMISSION II. MODEL DESCRIPTION As already mentioned, Energy storage sizing results were the tool s fundamental input. (Fig. 2) More specifically, the most essential input was the power level of base-load operation and the corresponding duration for all locations examined. Furthermore, the power plant s capacity is also needed in order to calculate the cabling lengths inside the PV plant (different PV plant installed capacities between 100MW and 1450MW were studied). Moreover, cable cost parameters are affected in some extent by the price of copper and thus, could vary over time. Thus, the tool was designed to be dynamic to such changes and offer to the user the possibility to experiment with these parameters as well. Finally, an input of significant importance is the transmission line length. Since, the tool is implemented to indicate what should be the best way to transmit the predecided PV plant installed power; transmission length is something that cannot be overlooked. Regarding the tool outputs, these can be listed as: Transmission cost for all scenarios examined and possible cost savings in case of including energy storage before the transmission line; either as a bulk unit (point B of Fig. 3) at the Point of Common Coupling (PCC) before the line or equally distributed inside the PV power plant (points A of Fig. 3). This profit could in some cases (and depending on the scenario examined) justify a big investment on energy storage for base-load operation reasons. A comparison between different AC transmission technologies (cables and overhead lines) and voltage levels, depending both on the plant s capacity and of course on the transmission distance. The main target was to identify what would be the best (in financial terms) solution and at which voltage level to transmit that power. OHL and cables at We have applied the pre-described model for 6 locations of promising meteorological characteristics. These areas are desert areas such as Tamanrasset (Algeria), Ordos (Mongolia) and Tucson (USA), areas of high altitude, which combine high radiation levels and low temperature like Lhasa (Tibet) and areas of high radiation levels close to existing grid infrastructure such as Naples (Italy) and Seville (Spain) and are the same locations used for the previous Energy storage Sizing project (1). It is important to note, that this analysis and the proposed technics would not have been appropriate for locations of different radiation and meterological profiles, since solar energy potential is strictly combined with the energy output and therefore similar cabling and storage placement may be proved inadequate. In the following graphs (Fig. 4 and Fig. 5) interdependence between voltage level of transmission and PV installed capacity for both base-load approaches is indicated and best transmission solutions are highlighted. The vertical and horizontal axes represent different locations and PV installed capacities respectively. It should be noted regarding the transmission costs, we have focused mainly on transmission cost (inverters, transformers and other components have not been included). Blue color illustrates that 132kV solution is the most suitable one in terms of financial cost for the corresponding scenario, while red and green color mean the same for 220kV and 400kV. The last line indicates a rough average between all locations. The following figures (AD: annual-daylight, MD: monthlydaylight) represent annual and monthly daylight base-load scenarios respectively. Of course, and as expected, as the installed capacity increases, the transmission s voltage level follows the same pattern. The main idea was to identify the critical capacities for which solutions of 132kV and 220kV were not suitable and greater voltage levels should be selected.

3 IV. RESULTS STORAGE PLACEMENT Figure 4. Annual Daylight & Transmission Voltage Figure 5. Monthly Daylight & Transmission Voltage Some conclusions that could be drawn from the previous graph indications: Given the fact that locations are presented in a descending way in terms of solar energy potential, stronger interdependence between solar energy potential and annual base-load than in monthly base-load could be noted. Energy storage sizing (Fig. 2) and power level of operation are more dependent on installed capacity for annual scenarios than for monthly ones. On the other hand for monthly base-load scenarios case studies exhibit a more homogenous behavior. An important conclusion, which was drawn from previous research study, is that, monthly base-load implementation results in better exploitation of solar energy than the annual one. [1] Higher base-load power levels could be translated into greater need for transmission capacity for the same size of PV power plant. That is why, for monthly scenarios, 132kV is the most appropriate solution for PV capacities up to 200MW, while for annual scenarios the same transmission may be proposed even for capacities up to 800MW. Consequently, for annual scenarios, 400kV is proposed only for the best - in terms of energy production - locations and for capacities greater than 1200MW. For monthly scenarios though, 400kV is always suggested for capacities greater than 1200MW regardless of the location. Energy storage could be connected to our system before or after the transmission line, either as a bulk unit or as a set of distributed sub-units (Fig. 3). For a PV power plant without energy storage, the transmission line should be dimensioned at power level equal to the PV nominal installed capacity. The same applies if energy storage is connected after the transmission line of the PV power plant. This paper focuses on the financial benefits in case storage is connected before the transmission line. Base-load operation means conversion of the PV curve to a rectangular of constant power level (Fig. 1); this power level, for such scenarios, is usually approximately within 45% and 55% of the PV curve s peak. Lower power level could be translated at the end into a significant reduction of the transmission cost that may balance the high investment cost of energy storage. For the same scenarios, as illustrated previously in Fig. 4 and Fig. 5, transmission cost was compared in case energy storage is connected as a bulk unit before or after the transmission line. Although distribution of energy storage (points A, Fig. 3) could bring the extra benefit of lowerrated cables between panels and the coupling point before transmission and better utilization of inverters, problems in case of partial clouding of the PV power plant led us not to include this scenario into the whole analysis. Another reason is that, regarding only the cabling/transmission cost when distributing energy storage within the PV power plant would result in an insignificant improvement (less than 1%), when compared to the scenario of energy storage as a bulk unit before transmission, because the inside-plant cabling cost is much lower when compared to the total transmission cost. Thus, the comparison will be done for the scenarios where Energy storage is a bulk unit either before or after the transmission line. In the following figures (Fig. 6 and Fig. 7), detailed graphs for both annual and monthly base-load scenarios can be found. The vertical axis represents the improvement (%) by means of reduction of transmission cost when energy storage is connected before the transmission line (instead of integration after the transmission line) and the horizontal axis represents, similarly to previous, different installed PV capacities. It is important to note that for all scenarios examined a constant transmission distance, equal to 100km, was assumed. The target was to highlight the connection between this financial benefit and the installed capacity of the power plant. Figure 6. AD - Improvements & Storage Placement

4 Figure 7. MD - Improvements & Storage Placement It is important to note that the greatest improvement (%) does not necessarily mean the optimal solution in terms of total financial cost; that was indicated in the previous graphs. Each graph is divided into 3 different colored areas. In case the font is light blue, no matter which voltage solution appears to bring the biggest improvement, 132kV solution, is the least expensive way to transmit the produced energy. That comes directly from the previous graphs, where the optimal in terms of cost voltage solutions for every scenario were indicated. Similarly, light red and light green fonts indicate that the best voltage level solution is 220kV and 400kV respectively. Every line of each graph represents one transmission solution of different voltage (132kV, 220kV, 400kV) and every line s value is the average between values of all 6 locations. The margins surrounding the lines represent maximum and minimum values depending on all scenarios. Since, the purpose was to have an overall understanding, a greater overview, of such PV plants and Energy storage operation, only the average graphs are being presented here. Finally, it is important to note that this analysis could be used as a guide only for locations of similar prosperous meteorological characteristic because transmission and energy storage sizing depends on the location s irradiation characteristics. Some conclusions based on the previous analysis and figures: 1. Improvement (transmission cost reduction) is most of the times slightly higher for annual scenario in comparison with monthly one. This happens because annual base-load operation means the whole year s output is based on the worst in production month s data. Due to that, for these scenarios, there is greater room for improvement in case storage is connected before transmission. 2. Variability of cost improvement is most of the times bigger in case of annual scenarios when compared with monthly ones. The surrounding margins especially for 132kV and 220kV are considerably wider in case of annual scenarios. This fact could mean that in case of monthly base-load there is not so great dependence on the location itself, and scenarios for all locations of similar meteorological characteristics present similar behavior. Solution of 400kV though, presents a totally different behavior in terms of variability of cost reduction for different locations. Energy output for monthly scenarios is greater and transmission should be rated for higher power capacities. In this research, for some locations and for capacities greater than 1100MW a second circuit of 400kV will be needed and that is the reason for the wider margins. 3. In case of dividing these graphs in 3 capacity areas and assuming a transmission distance equal to 100km, the following generalized conclusions could be drawn: a MW. Usually 132kV is the best transmission solution. Solution of 132kV is also the one with the greatest improvement as well (up to 60% for annual scenarios, usually less than 50%). b. 300MW-1100MW. Although, 132kV could present greater improvement (%), usually 220kV is the best transmission solution in terms of minimal cost for this installed capacities range. Improvements within this range lie between 50% and 75% in case of 132kV and 220kV; solution of 400kV has a maximum of 50%. c. 1100MW-1400MW. For this range of high installed PV capacities 400kV is most of the times needed, since the energy to be transmitted is significantly high regardless the greater improvement of 132kV and 220kV that could be even more than 80%. V. CONCLUSIONS For the needs of this paper a method to calculate transmission cost for different placement scenarios of energy storage and to estimate the best, in terms of financial cost, transmission solution for utility-scale PV power plants was developed. Transmission type (voltage level, number of circuits, design and cost) and benefit from including storage before transmission are exported as the main results for each scenario examined. Calculating the transmission cost for remote (most of the times) renewable generation power plant is a rather complex problem because of insufficient cost data and strong dependence on the geographic location. It is difficult to build a tool that calculates exactly the transmission cost under different operation strategies and for a variety of capacities and locations. However, with the proposed method and the corresponding pre-described tool, a blend of several cost models and transmission cost data have been integrated in order the output to be of the greatest accuracy. To sum up the results and conclusions from the research done for the needs of this paper: Location for PV power plants of size more than 100MW plays an important role in the energy storage sizing process. Thus energy output and transmission sizing are also dependent on the solar energy potential of each location. However, according to the results extracted from the tool, the interdependence between location and transmission characteristics appears to be stronger for annual base-load scenarios than for monthly ones. 220kV is the proposed solution for transmission for the majority of the examined PV installed capacities. 132kV and 400kV should be considered as competitive solutions for installed capacities lower than 300MW and greater than 1100MW respectively. Increased energy output for monthly scenarios is usually consistent with the need of higher voltage level of transmission for the same PV power plant.

5 Energy storage placement before the transmission results in a reduction of the total transmission cost that could exceed 50% when compared with placement after the transmission line (Fig. 6 and Fig. 7). This benefit is not capable to balance the high investment cost of energy storage but if considered among with the other benefits from energy storage may justify Energy Storage use for base-load generation purposes. Such methods should be applied to a case study with great care and only for similar locations, power plants and operation scenarios because it is very easy to be led to wrong conclusions. Regarding possible future work, there is great room for improvement of the proposed method. HVDC transmission could be included to the tool as another promising transmission solution, especially for large capacities on remote locations. Furthermore, additional detailed analysis can be done and factors that have been omitted can be taken into account in order the results to be of greater accuracy. The whole method could be applied for a bigger variety of locations, in order to have a better overview of such extended use of energy storage for base-load operations. REFERENCES [1] D. Doukas, K. Papastergiou, P. Bakas, A. Marinopoulos, Energy Storage Sizing for Large Scale PV Power Plants Base-Load Operation - Comparative Study & Results, in 2012 IEEE PVSC, Austin Texas, June [2] Stefan Lundberg, Performance Comparison of Wind Park Configurations, PhD Thesis, Chalmers University of Technology, Göteborg, Sweden [3] M.G. Hoffman, A. Sadovsky, M.C. Kintner-Meyer, J.G. DeSteese, Analysis Tools for sizing and placement of energy storage in grid applications A literature review, in ASME th International Conference on Energy Sustainability, August 7 10, 2011, Washington, DC, USA. [4] Z. Hu, W.T Jewell, Optimal power flow analysis of energy storage for congestion relief, emissions reduction, and cost savings, presented at Power Systems Conference and Exposition (PSCE), 2011 IEEE/PES, March 2011, Phoenix, Arizona, USA. [5] S. Chatzivasileiadis, M. Bucher, M. Arnold, T. Krause, G. Andersson, Incentives for optimal integration of fluctuating power generation, in 17th Power Systems Computation Conference (PSCC), August 2011, Stockholm, Sweden. [6] Y.M. Atwa, E.F. El-Saadany, Optimal allocation of ESS in distribution systems with a high penetration of wind energy, IEEE Transactions on Power Systems, Vol. 25, no. 4, pp , Nov [7] F.J. Adamek, Optimal storage location in power supply systems, in Cigré Session, Paris, France, August [8] Meteonorm software, Global Meteorological Database, [9] J. Eyer, G. Corey, Energy Storage for the Electricity Grid: Benefits and Market Potential Assessment Guide, Sandia National Laboratories, Albuquerque, California, USA, Feb [10] A. Oudalov, R. Cherkaoui, A. Beguin, Sizing and optimal operation of battery energy storage system for peak shaving application, in 2007 IEEE Lausanne Powertech, Lausanne, July