Using stormwater detention tanks as storage system for sustainable energy management in a smart city framework

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1 1 Using stormwater detention tanks as storage system for sustainable energy management in a smart city framework D. Menniti, A. Pinnarelli, N. Sorrentino, G. Belli, G. Barone Members, IEEE Abstract This paper proposes an innovative management strategy for a stormwater detention tank, whose main function is to prevent the risk of flooding in urban environment due to intense rainfall events. In the moments when the tank is not required to carry out its main function, the proposed use involves the operation of the tank as energy storage system, thanks to the introduction of a pump/turbine group, whose operation will be regulated by electrical market prices. The paper presents the management model implemented in Matlab/simulink environment, showing how the operation as storage system is well coordinate with eventual renewable generation systems. Index Terms Stormwater detention tank, storage system, sustainable energy management. T I. INTRODUCTION he warm climate changes impose a radical transformation in the way the whole world understands the progress. Indeed, today the progress is to be understood as sustainable development. Sustainable development is not a choice between environment protection and social welfare, but rather it is a fusion of economic and social development that would be compatible with the environmental defence. In this way, the development ensures appropriate, secure and wealth life for all people; the sustainability allows to live and labour in accordance with the biophysical limits of the nature [1]. This must be the cornerstone on which to plan the future because only through sustainable development of human activities, they can continue to exist and with them the life of men. The energy sector is one of the most important to realize the sustainable development and in the same time, the wellness of men. In that sector, it is necessary to think firstly to the rational use and the replenishment of natural resources. In this context, every action that recovers energy is welcome. The recovery of energy can be achieved in many different ways, by the rationalization of consumption; the more efficient production, the application of more effective energy management strategies, from production to consumption; the use of renewable sources for the energy generation. In particular, the use of renewable sources allow to obtain energy with zero environmental impact and at lower cost compared to the use of fossil fuels. Due to these advantages, in last years, the spread of renewable sources technologies (Distributed Generation DG), especially of small size, has grown. Paradoxically, the excess spread of such systems has caused problems on transmission networks (as inverse energy flows) and on the planning of traditional generation plants (that must give the priority to the energy produced by renewable sources). On all problems, renewable sources are not programmable so their use depends on their availability. To mitigate this limit, it is necessary to think to an energy management that can use the most of the potential of renewable resources and can recover energy as much as possible. To this end, the use of energy storage systems must be encouraged. In this context, the paper shows an innovative management strategy for a Stormwater Detention Tank (SDT) as energy storage system. The system is composed of a SDT whose main function is to collect and to store the rainfall water, avoiding the risk of flooding in urban environment near to the site of the tank, and to return the collected water volumes at the end of the meteoric event. For the use as an energy storage system, the SDT is equipped with a mini - hydroelectric system [2-3], using water as an energy carrier, in the hours when the SDT is not required to carry out its main function. The solution proposed in this paper is well adapt in a Smart City context, where a more efficient energy management is required of all the devices and all the operators who take part in the complicated national electricity system, from production to distribution and consumption, through all stages of the electricity market. Indeed, for a correct use of the SDT as energy storage system, a management model with national electric market signals like purchase and sale price, as references, is proposed in the paper. In this way, a SDT that works as energy storage systems contributes to resolve some common current problems on distribution networks, such as: facilitate interconnection among different micro-sources from renewables (solar, wind, fuel-cells, etc.) and may make them more reliable and efficient; operate the micro-sources properly, efficiently and permanently at the full power, with the surplus of generated energy available to charge the energy storage systems;

2 2 compensate load variations [4-7]. The paper is divided as following: in the next Section, a brief description of the SDT and of the mini-hydroelectric system is presented; in Section III, the management model of the tank as storage system is explained; in the last Section, some numerical results are shown. II. STORMWATER DETENTION TANK SYSTEM Firstly, an urban area of the city of Cosenza Piazza Loreto, in Italy, is indicated as a possible installation site of the tank (see Fig.1a). The area chosen to host the SDT is in the city centre at an altitude of 274 m above sea level, while the area chosen to host the pond necessary to the whole system, is located at an altitude of 238 m above sea level, along a river. The available head from the higher point to the lower one is 36 m. After the identification of the installation area, Piro et alii [8] have studied the design of the SDT system, in order to limit the risk of flooding in the above-mentioned zone. A schematic of the SDT system is reported in Fig. 1b. It consists of: (1) a SDT located upstream the watershed of interest, (2) an artificial wet pond located downstream, and (3) a pipeline linking the two tanks equipped with a pumping system/turbine, as shown in Fig.1a. A pre-treatment unit, in which the combined sewage (wastewater and stormwater) from the drainage network is subject to a process of screening and sedimentation, precedes the SDT. The operating principle is the following one. During rain events, the storm-water detention tank stores a portion of the urban runoff volume coming from the watershed of interest in the city of Cosenza. Fig. 1. a) Localized area of city of Cosenza. b) Schematic of the system. III. MANAGEMENT MODEL OF A SDT AS STORAGE SYSTEM In this Section, the management model of a SDT as an energy storage system is illustrated. The model receives as input signals the purchase and sale prices from the national electricity market: according to these data and to the water level contained in it, it decides when and how much energy generate, or when and how much water pump upstream, minimizing the cost of both operations. Of course, it is worth to underline immediately that the tank is built to its main function, that is limit the risk of flooding, so the operation as storage system starts only after the management model has received the weather forecasts and therefore the water level contained in the tank. The management model is an optimization problem that minimizes the cost of the operation of the SDT as energy storage system. It is shown as follows: min Fval = 24 h=1 (C h R h ) (1) with R h = r h P h g = r h h a Q g (2) C h = c h P p h = c h b Q p h (3) s.t. Q h 1 h + Q rain + Q h p Q h g Q tank (4) Q h p Q p_max (5) Q g h Q g_max (6) Q p h Q g h = (7) In (1), the function to minimize is Fval: it is equal to the sum, for each hour h of the day taking into account, of the difference between the hourly costs (C h ) and the hourly gains (R h ). Notice that the gains are represented with negative values because the optimization problem researches the minimum of the costs, so a negative result of Fval has to consider as an utility. In (2) and (3), R h and C h are shown in details: in (2), R h is equal to the product between the hourly sale electricity price (r h ), established through national electricity market, and the electric power that the turbine is able to generate in the hour h (P h g ). P h g is equal to the product between r h, a coefficient a that takes into account all the turbine parameters (also the efficiency) and the hourly flow rate processed by the turbine (Q h g ). Similarly, (3), C h is equal to the product between hourly purchase electricity price (c h ), established through national electricity market, and the electric power that the pump is able to absorb in the hour h (P h p ). P h p is equal to the product between c h, a coefficient b that takes into account all the pump parameters (also the efficiency) and the hourly flow rate absorbed by the pump (Q h p ). From (4) to (7) the optimization problem constraints are presented. The (4) is an inequality constraint that limits the maximum quantity of water containable into the SDT (Q tank ). The (4) indicates that the quantity of water contained in the tank is equal to the sum of: the quantity of water contained at the hour h-1 (Q h-1 ), the quantity of the stormwater fallen in the hour h (Q h rain ), the quantity of the pumped water at hour h (Q h p ), minus the quantity of water needed to electric generation by the turbine at the hour h (Q h g ). The (5) and (6) constraints present the lower bounds and the upper bounds of Q h p and Q h g, respectively. For both the constrains, the lower bound is zero; for Q h p, the upper bound is equal to the maximum flow rate that the pump can absorb (Q p_max ), while for Q h g, the upper bound is equal to the maximum flow rate that the turbine can operate (Q g_max ).

3 3 The (7) is a constraint of exclusion: it imposes the condition such that in the same hour h, the whole SDT system operates to push the water upstream or to generate energy. IV. NUMERICAL RESULTS To test the effectiveness the proposed management model, some simulations are carried out, taking into account a 25 m 3 SDT. The tank was equipped with a mini-hydro group composed of a 45 kw - Calpeda NM4 15/4 pump with a flow rate of 268 m3/h and a hydraulic head of 4.7 m; and an 18 kwe Calpeda NM4 125/315 turbine with a flow rate of 24 m3/h and a hydraulic head of 28 m [6]. The simulation are carried out for three typical days: a day with poor rainfall (6/1/212), a day with rich rainfall (14/4/212) and a sunny day (21/6/212). The rainfall levels are shown in Table I [9]. Day Hour TABLE I RAINFALL [M 3 ] 16/1 14/4 21/ For those days, the values of purchase and sale prices are obtained through the national electricity market. Purchase prices correspond to the values of the rate by hour applied by a typical distribution operator to a non-domestic user with committed capacity exceeding 16.5 kw [1]; sales prices are the zonal prices of the national electricity market [11] obtained for the days taking into account. The values are reported in Table II, in function of the considered day and by hour. TABLE II HOURLY PRICES [M 3 ] 6/1/212 14/4/212 21/6/212 h r h c h r h c h r h c h 1,8127,8223,8195,846,841,8394 2,6756,8223,7344,846,7499,8394 3,6733,8223,6543,846,7395,8394 4,698,8223,6544,846,736,8394 5,699,8223,6215,846,7445,8394 6,5297,8223,6543,846,7412,8394 7,35,9899,6913,1292,7645,8394 8,4962,117,7791,1826,949,1118 9,6322,117,8751,1826,198,1959 1,653,117,9158,1826,1629, ,665,117,8354,1826,1367, ,6617,117,7649,1826,918, ,6496,117,675,1826,74, ,6117,117,6211,1826,73, ,619,117,6136,1826,8, ,6325,117,6345,1826,82, ,7114,117,6914,1826,9, ,8863,117,7744,1826,15, ,9122,9899,8285,1292,9999,1118 2,9415,9899,113,1292,1249, ,9262,9899,1153,1292,1118, ,9191,9899,1,1292,1816, ,8533,8223,8,846,9157, ,7578,8223,75,846,85,8394 A first case of simulations has considered only the operation of the tank with the level of rainfall: the management model, as a function of price signals, has not returned the convenience in pumping water upstream, for which the trend of Qp is always zero for all three days. This is due to the purchase and sale prices of energy that are very close to each other and so the model does not find economically advantageous to pump water first and then send it in a turbine to generate energy to sell. In addition, in the calculation of the pumping and generation power, the machine efficiencies have been taken into account: due to the same value given by the authors, of course, the management model will find only convenience if there is a substantial discrepancy between the purchase and sale prices. In Fig.2 the trend of Qg for the days under examination is shown: on days when the rainfalls occur (6th January and 14th April), a quantity of stormwater is available in the tank, so it is possible to generate energy. In the sunny day (21st June), there is no available stormwater so Qg is zero on all 24 hours and there is no electricity generation. For these reasons, the value of Fval in 6th January is equal to -7.51, in 14th April is equal to , while in 21st June is zero. Flow rate [m3] Generation flow rate Qg Fig. 2. Hourly generation flow rates for the days taking into account Qg_6/1 Qg_14/4 Qg_21/6 A second case of simulations is considered by imposing a discount on the purchase price of energy, so on pumping action. This choice is justified considering what happens more and more often in the distribution network. Indeed, with the massive penetration of distributed generation, especially from renewable sources, it often happens that the distribution

4 4 networks are subject to congestion caused by the huge reverse flows of energy into the network. When that happens, serious problems on security of the network may appear and the network operator (Terna, in the Italian case), requires to the producers of distributed generation to cut their production. The production cut is obviously an action to prevent for the economic loss that involves, but especially for the energy loss which can be recovered in no way. To prevent the cut of the production, the SDT should work as energy storage system, pumping water upstream when there is a large amount of energy not required by the consumers, and then returning it in the form of energy when the selling price is favourable. Therefore, the idea of applying a discount to the energy purchase price is equivalent to have an available excess energy that can reset or reduce the pumping cost. In Fig.3, the values of Fval is shown as a function of the variation of the discount applied to the energy purchase price for the three days considered. For all three days, the tank operating as an energy storage system is able to guarantee a utility. The values of the discount applied ranging from 1% to 7% on the purchase price: more than this value, the management model considers no longer cost-effective the pumping and does not execute it. Observing Fig.3, it is worth to underline that as in the simulations without discount, the lower utility is obtained in the case of sunny day. In case with discount that reduces the purchase price, the action of pumping water from the pond to the tank is feasible and the later energy generation recovers economically the action. The day with poor rainfalls, (6th January) allows a not bad utility, while in the day with heavy rainfall the utility is much more significant. [ ] Fval 1% 9% 85% 8% 7% % Fva_6/1l Fval_14/4 Fval_21/6 Fig. 3. The trend of Fval for the days taking into account, as a function of the discount on the purchase price. [m 3 ] Fig. 4. The trend of Qp for the days taking into account. In Fig.5, the trends of the quantity of the water sent into the turbine for electricity generation for the three days considered are shown. It is clear that the water contained in the tank, that is the stored energy, can provide valuable assistance to meet the electricity demand during peak hours, without prejudice the security of the operation of the tank to limit the risk of urban flooding. [m3] Pumped flow rate_1% sale on c h Generation flow rate_1% sale on c h Fig. 5. The trend of Qg for the days taking into account. Qp_6 /1 Qp_14 /4 Qp_21 /6 Qg_6/ 1 Qg_14/ 4 Qg_21/ 6 The Fig.6 shows the trends of the quantity of water moved in the tank (Q) for the three days under examination, when the tank works to accumulate water. If the tank is not used to accumulate water, the trend of Q depend only on the rainfalls and on the action of power generation when requested by the users. In this case, the energy excess that may appear within a few hours of the day, not injectable into the network, however, would be cut off. Now, the results of the case with 1% discount on the purchase price are discussed. This situation is equivalent to the case in which there is an excess of energy that can cover all the necessary energy to pump water from the pond to the tank. In Fig.4, the trends of the quantity of pumped water from downstream to upstream for the three days are depicted. In contrast to the common believe, it can be observed how the pumping not happens only in the night hours where the energy price is lower, but also it occurs during the hours of demand peak and then when the highest energy prices are reached.

5 5 3 Total flow rate_1% sale on c h A future aim of the authors is to introduce the SDT as energy storage system in the aggregator model illustrated in [11]. [m3] Fig. 6. The trend of Q for the days taking into account. In Table III, the values of Fval are indicated, with and without the 1% discount on energy purchase price. Day Discount on P h p TABLE III FVAL[ ] 16/1 14/4 21/6 % % The last analysis gives an annual estimate of how much is the utility if the tank works as an energy storage system. The results are shown in Table IV, having assumed that for the area chosen as location of the tank, on average in the year, the 1% of the days are very rainy like the 14/4/212, the 25% of days are modest rainy like the 6/1/212 and the remaining 65% of days are sunny like the 21/6/212. TABLE IV ANNUAL FVAL[ ] Discount on P h p Fval Q_6 /1 Q_14 /4 Q_21 /6 ACKNOWLEDGMENT This work was financed by the Italian Ministry of Economic Development (MISE) and the Ministry of Education, University and Research (MIUR), through the National Operational Program for Development and Competitiveness , Project PON 42a_E "SRS". REFERENCES [1] R.Ciegis, J.Ramanausakiene, B.Martinkus, The concept of sustainable development and its use for sustainability scenarios, Inzinerie Ekonomika-Engineering Economics, 29 [2] H. Chen, T.N. Cong, W. Yang, C. Tan, Y. Li, Y. Ding, Progress in electrical energy storage system: a critical review, Progress in Natural Science,, Elsevier, 29, Pages [3] H. Ibrahim, A. Ilinca, J. Perron, Energy storage systems, Characteristics and comparisons, Renewable and Sustainable Energy Reviews, Volume 12, Issue 5, June 28, Pages [4] N.S. Wade, P.C. Taylor, P.D. Lang, P.R. Jones, Evaluating the benefits of an electrical energy storage system in a future smart grid, Energy Policy, Vol. 38, November 21, Pages , [5] G. Belli, G. Brusco, A. Burgio, D. Menniti, A. Pinnarelli, N.Sorrentino, "A feed-in tariff to favorite photovoltaic and batteries energy storage systems for grid-connected consumers", Innovative Smart Grid Technologies Europe (ISGT EUROPE), 213 4th IEEE/PES, vol., no., pp.1,5, 6-9 Oct. 213 [6] J.P. Barton, D.G. Infield, "Energy storage and its use with intermittent renewable energy," Energy Conversion, IEEE Transactions on, vol.19, no.2, pp.441,448, June 24 [7] J.M. Eyer, J.J. Iannucci, G.P. Corey, Energy storage benefits and market analysis handbook, Sandia Laboratories, 24 [8] G. Garofalo, M. Carbone, P. Piro, Storwater detention Tank for sustainable energy management in urban environment [9] [1] Economic conditions for customers of enhanced protection - Enel Energia, [11] [12] D. Menniti, A. Pinnarelli, N.Sorrentino, A. Burgio, G. Belli, Management of storage system in local electricity to avoid renewable power curtailment in distribution networks, AUPEC 214, Perth, Australia, 28 th Sep 3 rd Oct. 1% % % % % V. CONCLUSION The simulation results have shown how a SDT can be used, in addition to its main function that is prevent flooding, even as efficient energy storage system. In particular, this innovative use is justified considering the significant energy excess from renewable sources that cannot be inject into the grid, causing congestions on power lines, in some hours of the day. This type of tanks not only allows to "save" the energy that would otherwise be lost or cut off by the network operators, but also allows to get a utility by pumping water and subsequent release the same in a turbine, producing electricity.