I drift away from investor-relations sites, and I go back to my ‘Energy Ponds’ concept. I feel like going through it once again. First thing first, I want to lay out the idea such as I have figured it out so far. The second of the first things is that I am describing a yet-unimplemented, tentative technological solution, which combines water management with the generation of renewable energies. Ram-pumps are installed in the stream of a river. Kinetic energy of the river creates a by-flow through the ram-pumps, endowed with its own kinetic energy and flow rate, derived from those of the river. That by-flow is utilized in two ways. Some of it, within the limits of environmental sustainability of the riverine ecosystem, is pumped into wetland-type structures, which serve the purpose of water retention. On the way to wetlands, that sub-stream passes through elevated tanks, which create a secondary hydraulic head and allow placing hydroelectric turbines on pipes leading from elevated tanks to wetlands, i.e. back to ground level. The remaining part of the ram-pumped by-flow, before going back into the river, is recirculated through hydroelectric turbines located close to the ram-pump. The basic idea is shown graphically in Figure 1.

The remaining part of the article develops a complex proof of concept for ‘Energy Ponds’. Component solutions are discussed against the background of relevant literature, and a quantitative simulation of its basic parameters is presented, for simulated location in Poland, author’s home country.

Figure 1

‘Energy Ponds’ are supposed to create a system of water retention with as little invasive change in the landscape as possible. Typical reservoirs, such as artificial ponds and lakes, need space, and that space ought to be taken away from other employments thereof. This is a dilemma in land management: do we use a given portion of terrain for a retention reservoir or do we use it for other purposes? In densely populated regions, that dilemma becomes acute, when it comes to mutual arrangement of human architectural structures, agricultural land, and something which, fault of a better word, can be called ‘natural landscape’ (quotation marks refer to the fact that many landscapes which we intuitively gauge as ‘natural’ are actually man-made and artificially maintained).  

Water management, as a distinct field of technology, with an environmental edge, could benefit from innovation-boosting tools typical for other technological fields (Wehn & Montalvo 2018[1]; Mvulirwenande & Wehn 2020[2]). Technological change as regards water management is needed both in rural areas and in cities. Interestingly enough, urban environments seem to be more conservative than agriculture in terms of water management (Wong, Rogers & Brown 2020[3]). There is a quest for scientifically based constants in water management, such as the required quantity of water per person per day; Hogeboom (2020[4]) argues it is roughly 3800 liters after covering all the conventional uses of water. On the other hand, Mohamed et al. (2020[5]) claim that the concept of ‘arid region’, so far reserved for desertic environments, is de facto a type of environmental context when we systematically lack accurate environmental data as regards quickly changing availability of water. Kumar et al. (2020[6]) go even further and postulate something called ‘socio-hydrology’: human societies seem to develop characteristically differentiated patterns of collective behaviour in different hydrological conditions. Other research suggests that societies adapt to increased use of water by visibly increasing the productivity of that use, whilst increased income per capita seems being correlated with increased productivity in the use of water (Bagstad et al. 2020[7]).

In the ‘Energy Ponds’ concept, retention of water is supposed to be a slow, looped recirculation through local ecosystems, rather than accumulation in fixed reservoirs. Once water has been ram-pumped from a river into wetlands, the latter allow slow runoff, via ground waters, back into the hydrological system of the river basin. It is as if rain was falling once again in that river basin, with rainwater progressively collected by the drainage of the river. In hydrology, such a system is frequently referred to as quasi-reservoirs (Harvey et al. 2009[8]; Phiri et al. 2021[9]). Groundwater seems being the main factor of the observable water storage anomalies (Neves, Nunes, & Monteiro 2020[10]). Purposeful control of the size and density in the patches of green vegetation seems to be a good practical regulator of water availability, whence the interest in using wetlands as reservoirs (Chisola, Van der Laan, & Bristow 2020[11]).

Ram-pumps placed in the stream of a river become distributed energy resources based on renewable energy: they collect and divert part of the kinetic energy conveyed by the flow of water. Of course, one can ask: isn’t it simpler to put just hydroelectric turbines in that stream, without ram-pumps as intermediary? A ram-pump, properly instrumented with piping, becomes a versatile source of kinetic energy, which can be used for many purposes. In ‘Energy Ponds’, the idea is to use that energy both for creating a system of water retention, and for generating electricity. The former has its constraints. The amount of water to adsorb from the river is limited by the acceptable impact on ecosystems downstream. That impact can be twofold. Excessive adsorption upstream can expose the downstream ecosystems to dangerously low water levels, yet the opposite can happen as well: when we consider wetlands as pseudo-reservoirs, and thus as a reserve of water, its presence can stabilize the flow downstream (Hunt et al. 2022[12]), and the biological traits of ecosystems downstream are not necessarily at risk (Zhao et al. 2020[13]). Strong local idiosyncrasies can appear in that respect (Xu et al. 2020[14]).

Major rivers, even those in plains, have a hydraulic head counted in dozens of meters and a flow rate per second in the hundreds of cubic meters per second. With the typical efficiency of ram-pumps ranging from 35% to 66%, the basic physical model of ram-pumping (Fatahi-Alkouhi et al. 2019[15];  Zeidan & Ostfeld 2021[16]) allows pumping from the river more water than it is possible to divert into the local wetlands.  

Thus, two sub-streams are supposed to be ram-pumped in the ‘Energy Ponds’ system: one sub-stream ultimately directed to and retained in the local wetlands, and another one being the non-retainable excess, to be redirected immediately back into the river. The latter can immediately flow through hydroelectric turbines placed as close as possible to ram-pumps, in order not to lose kinetic energy. The other goes further, through the system of elevated tanks. Why introducing elevated tanks in the system? Isn’t it better to direct the retainable flow of water as directly as possible to wetlands, thus along a trajectory as flat as is feasible in the given terrain? The intuition behind elevated tanks is the general concept of Roman siphon (e.g. Angelakis et al. 2020[17]). When we place an artificially elevated tank along the flow of water from the river to the wetlands, it allows transporting water over a longer distance without losing kinetic energy in that flow. Therefore, the wetlands themselves, as well as the points of discharge from the piping of ‘Energy Ponds’ can be spread over a greater radius from the point of intake from the river. That gives flexibility as regards adapting the spatial distribution of the whole installation to the landscape at hand. Elevated water tanks can increase the efficiency of water management (Abunada et al. 2014[18]; Njepu, Zhang & Xia 2019[19]).

A water tank placed at the top of the Roman siphon is a reserve of energy in pumped storage, and thus allows creating a flow with the same kinetic energy as was generated by ram-pumps, yet further away from the point of intake in the river. Depending on the volumetric capacity and the relative height of the elevated tank, various amounts of energy can be stored. Two points are to consider in that respect. ‘Energy Ponds’ is supposed to be a solution as friendly as possible to the landscape. Big water towers are probably to exclude, and the right solution for elevated tanks seems closer to those encountered in farms, with relatively light structure. If there is need to store more energy in a local installation of ‘Energy Ponds’, there can be more such elevated tanks, scattered across the landscape. With respect to the relative height, documented research indicates a maximum cost-effective elevation between 30 and 50 meters, with 30 looking like a pragmatically conservative estimate (Inthachot et al. 2015[20]; Guo et al. 2018[21]; Li et al. 2021[22]). Elevated tanks such as conceived in ‘Energy Ponds’ can be various combinations of small equalizing tanks (serving just to level up intermittence in the flow of water), and structures akin raingardens (see e.g. Bortolini & Zanin 2019[23]), thus elevated platforms with embedded vegetal structures, capable of retaining substantial amounts of water.

As an alternative to artificial elevated tanks, and to the extent of possibilities offered by natural landscape, a mutation of the STORES technology (short-term off-river energy storage) can be used (Lu et al. 2021[24]; Stocks et al. 2021[25]). The landscape needed for that specific solution is a low hill, located next to the river and to the wetland. The top of such hill can host a water reservoir.

The whole structure of ‘Energy Ponds’, such as conceptually set for now, looks like a wetland, adjacent to the channel of a river, combined with tubular structures for water conduction, ram pumps and hydroelectric turbines. As for the latter, we keep in mind the high likelihood of dual stream: one close to ram-pumps, the other one after the elevated tanks. Proper distribution of power between the generating units can substantially reduce the amount of water used to generate the same amount of energy (Cordova et al. 2014[26]).

Hydroelectricity is collected in energy storage installations, which sell electricity to its end users. The whole concept follows the general stream of research on creating distributed energy resources coupled with landscape restoration (e.g.  Vilanova & Balestieri 2014[27]; Vieira et al. 2015[28]; Arthur et al. 2020[29] ; Cai, Ye & Gholinia 2020[30] ; Syahputra & Soesanti 2021[31]). In that path of research, combinations of energy sources (small hydro, wind and photovoltaic) plus battery backup, seem to be privileged as viable solutions, and seem allowing investment in RES installations with an expected payback time of approximately 10 – 11 years (Ali et al. 2021[32]). For the sake of clarity in the here-presented conceptualization of ‘Energy Ponds’, only the use of hydropower is considered, whilst, of course, the whole solution is open to adding other power sources to the mix, with limitations imposed by the landscape. As wetlands are an integral component of the whole concept, big windfarms seem excluded from the scope of energy sources, as they need solid support in the ground. Still, other combinations are possible. Once there is one type of RES exploited in the given location, it creates, with time, a surplus of energy which can be conducive to installing other types of RES power stations. The claim seems counterintuitive (if one source of energy is sufficient, then it is simply sufficient and crowds out other sources), yet there is evidence that local communities can consider RES according to the principle that ‘appetite grows as we eat’ (Sterl et al. 2020[33]). Among different solutions, floating solar farms, located on the surface of the wetland, could be an interesting extension of the ‘Energy Ponds’ concept (Farfan & Breyer 2018[34]; Sanchez et al. 2021[35]).

Material and methods

The general method of studying the feasibility of ‘Energy Ponds’ is always specific to a location, and it unfolds at two levels: a) calibrating the basic physical properties of the installation and b) assessing its economic viability. Hydrological determinants are strongly idiosyncratic, especially the amount of water possible do adsorb from the local river and to retain in wetlands, and the impact of retention in wetlands upon the ecosystems downstream. With wetlands as a vital component, the conceptual scheme of the ‘Energy Ponds’ naturally belongs to plains, as well as to wide river valleys surrounded by higher grounds. That kept in mind, there are conceptual developments as regards artificially created wetlands in the mountains (Shih & Hsu 2021[36]).

The local feasibility of ‘Energy Ponds’ starts with the possible location and size of wetlands. Places where wetlands either already exist or used to exist in the past, before being drained, seem to be the most natural, as local ecosystems are likely to be more receptive to newly created or expanded wetlands. Conflicts in land management between wetlands and, respectively, farmland and urban settlements, should be studied. It seems that the former type is sharper than the latter. There is documented technological development as regards the so-called Sponge Cities, where urban and peri-urban areas can be transformed into water-retaining structures, including the wetland-type ones (Sun et al. 2020[37]; Köster 2021[38]; Hamidi, Ramavandi & Sorial 2021[39]). On the other hand, farmland is a precious resource and conflicts between retention of water and agriculture are (and probably should be) settled in favour of agriculture.   

Quantitatively, data regarding rivers boils down to the flow rate in cubic meters per second, and to the hydraulic head. Flow and head are the elementary empirical observables of the here-presented method, and they enter into the basic equation of ram-pumping, as introduced by Zeidan & Ostfeld (2021 op.cit.), namely:

H_R*Q_R*η = H_T*Q_T                     (1)

…where H_R is the hydraulic head of the river, Q_R is its flow rate in m³/s, H_T is the relative elevation where water is being ram-pumped, Q_T is the quantity of pumped water, and η is a coefficient of general efficiency in the ram-pumps installed. That efficiency depends mostly on the length of pipes and their diameter, and ranges between 35% and 66% in the solutions currently available in the market. Knowing that Q_T is a pre-set percentage p of Q_R and, given the known research, p = Q_T/Q_R ≤ 20%, it can be written that Q_T = Q_Rp. Therefore, equation (1) can be transformed:  

η = [H_T*Q_R*p] / [H_R*Q_R] = H_T*p / H_R              (2)

The coefficient η is predictable within the range that comes with the producer’s technology. It is exogenous to the ‘Energy Ponds’ system as such unless we assume producing special ram-pumps in the project. With a given flow per second in the river, efficiency η natural dictates the amount of water being ram-pumped, thus the coefficient of adsorption p.  Dual utilization of the ram-pumped flow (i.e. retention in wetlands and simple recirculation through proximate turbines) allows transforming equation (1) into equivalence (3):

{[H_RQ_RH_Tp / H_R] = [H_RQ_C + H_TQ_W] }  {Q_RH_Tp = [H_RQ_C + H_TQ_W]}         (3)

…where Q­_C stands for the sub-flow that is just being recirculated through turbines, without retention in wetlands, and Q_W is the amount retained. The balance of proportions between Q_C and Q_W is an environmental cornerstone in the ‘Energy Ponds’ concept, with Q_W being limited by two factors: the imperative of supplying enough water to ecosystems downstream, and the retentive capacity of the local wetlands. The latter is always a puzzle, and its thorough understanding requires many years of empirical observation. Still, a more practical method is proposed here: observable change in the surface of wetlands informs about changes in the amount of water stored. Of course, this is a crude observable, yet it can serve for regulating the amount of water conducted into the wetland.      

The hydraulic head of the river (H_R) is given by the physical properties thereof, and thus naturally exogenous. Therefore, the fundamental technological choice in ‘Energy Ponds’ articulates into four ‘big’ variables: a) the producer-specific technology of ram-pumping b) the relative height H_T of elevated tanks c) the workable fork of magnitudes in the amount of water Q_W to store in wetlands, and d) the exact technology of energy storage for hydroelectricity. These 4 decisions together form the first level of feasibility as regards the ‘Energy Ponds’ concept. They are essentially adaptive: they manifest the right choice for the given location, with its natural and social ecosystem.

A local installation of ‘Energy Ponds’ impacts the local environment at two levels, namely the retention of water, and the supply of energy. Water retained in wetlands has a beneficial impact on the ecosystem, yet it is not directly consumable: it needs to pass through the local system of supply in potable water first. The direct consumable generated by ‘Energy Ponds’ is hydroelectricity. Besides, there is some empirical evidence for a positive impact of wetlands upon the value of the adjacent, residential real estate (Mahan et al. 2000[40]; Tapsuwan et al. 2009[41]; Du & Huang 2018[42]). Thus comes the second level of feasibility for ‘Energy Ponds’, namely the socio-economic one. As ‘Energy Ponds’ is an early-stage concept, bearing significant uncertainty, the Net Present Value (NPV) of discounted cash flows seems suitable in that respect. Can the thing pay its own bills, and bring a surplus?

Answering that question connects once again to the basic hydrological metrics, namely head and flow. Hydroelectric power is calculated, in watts, as: water density (1000 kg/m3) * gravity acceleration constant (9,8 m/s2) * Net Head (meters) * Q (water flow rate m3/s). The output of electricity is derived from the power generated. It is safe to assume 50 weeks per year of continuous hydrogeneration, with the remaining time reserved for maintenance, which gives 50*7*24 = 8400 hours. Based on the previous formulations, power W generated in an installation of ‘Energy Ponds’ can be expressed with equation (4), and the resulting output E of electricity is given by equation (5):

W[kW] = ρ * g * (H_RQ_C + H_TQ_W) = 9,81 * (H_RQ_C + H_TQ_W)      (4)

E[kWh] = 8400 * W           (5)

The Net Present Value (NPV) of cash flow in an ‘Energy Ponds’ project is the residual part of revenue from the sales of electricity, as in equation (6).

The revenue is calculated as R_E = P_E*E , with P_E standing for the price of electricity per 1 kWh. Investment outlays and the current costs of maintenance can be derived from the head and the flow specific to the given location. In that respect, the here-presented method, including parameters in equation (6), follows that by Hatata, El-Saadawi, & Saad (2019[43]). A realistic, technological lifecycle of an installation can be estimated at 12 years. Crossflow turbines seem optimal for flow rates inferior or equal to 20 m³ per second, whilst above 20 m³ Kaplan turbines look like the best choice. Investment and maintenance costs relative to ram pumps, elevated tanks, and the necessary piping remain largely uncertain, and seemingly idiosyncratic as regards the exact location and its physical characteristics. That methodological difficulty, seemingly inherent to the early conceptual phase of development in the ‘Energy Ponds’ concept, can be provisionally bypassed with the assumption that those hydraulic installations will consume the cost which would normally correspond to the diversion weir and intake, as well as to the cost of the powerhouse building. The variable I_H corresponds to investment outlays in the strictly hydrological part of ‘Energy Ponds’ (i.e. ram-pumps, piping, and elevated tanks), whilst the I_TU component, on the other hand, represents investment in the strictly spoken turbines and the adjacent power equipment (generator, electrical and mechanical auxiliary, transformer, and switchyard). The LCOS variable in equation (6) is the Levelized Cost of Storage, estimated for a discharge capacity of 6 hours in Li-Ion batteries, at €0,28 per 1 kWh (Salvini & Giovannelli 2022[44]; Chadly et al. 2022[45]). The ‘0,000714’ factor in equation (6) corresponds to the 6 hours of discharge as a fraction of the total 8400 working hours of the system over 1 year.

Case study with calculations

The here presented case study simulates the environmental and economic impact which could possibly come from the hypothetical development of the ‘Energy Ponds’ concept in author’s own country, namely Poland. The concept is simulated in the mouths of 32 Polish rivers, namely: Wisła, Odra, Warta, Narew, Bug, Noteć, San, Wieprz, Pilica, Bzura, Biebrza, Bóbr, Łyna, Drwęca, Barycz, Wkra, Gwda, Prosna, Dunajec, Brda, Pisa, Wisłoka, Nida, Nysa Kłodzka, Wisłok, Drawa, Krzna, Parsęta, Rega, Liwiec, Wełna, Nysa Łużycka (the spelling is original Polish). Flow rates, in cubic meters per second, as observed in those mouths, are taken as the quantitative basis for further calculations, and they are provided in Table 1, below. Figure 1, further below, presents the same graphically, on the map of Poland. The corresponding locations are marked with dark ovals. There are just 28 ovals on the map, as those located near Warsaw encompass more than one river mouth. That specific place in Poland is exceptionally dense in terms of fluvial network. Further in this section, one particular location is studied, namely the mouth of the Narew River, and it is marked on the map as a red oval.  

Table 1

River name	Mouth opening on…	Average flow rate [m3/s]	River name	Mouth opening on…	Average flow rate [m3/s]
Wisła	Baltic Sea	1080	Prosna	Warta	17,4
Odra	Baltic Sea	567	Dunajec	Wisła	85,5
Warta	Odra	216	Brda	Wisła	28
Narew	Wisła	313	Pisa	Narew	26,8
Bug	Narew	155	Wisłoka	Wisła	35,5
Noteć	Warta	76,6	Nida	Wisła	21,1
San	Wisła	129	Nysa Kłodzka	Odra	37,7
Wieprz	Wisła	36,4	Wisłok	San	24,5
Pilica	Wisła	47,4	Drawa	Noteć	21,3
Bzura	Wisła	28,6	Krzna	Bug	11,4
Biebrza	Narew	35,3	Parsęta	Baltic Sea	29,1
Bóbr	Odra	44,8	Rega	Baltic Sea	21,1
Łyna	Pregoła[46]	34,7	Liwiec	Bug	12,1
Drwęca	Wisła	30	Wełna	Warta	9,2
Barycz	Odra	18,8	Nysa Łużycka	Odra	31
Wkra	Narew	22,3

Figure 2

The hypothetical location of Energy Ponds installations at the mouths of rivers is based on the availability of hydrological data, and more specifically the flow rate in cubic meters per second. That variable is being consistently observed at the mouths of rivers, for the most part, unless some specific research is conducted. Thus, locating the simulated Energy Ponds at the mouths of rivers is not a substantive choice. Real locations should be selected on the grounds of observable properties in the local ecosystem, mostly as regards the possibility of storing water in wetlands. 

The map of location chosen for this simulation goes pretty much across all the available fluvial valleys in Poland, the physical geography of which naturally makes rivers grow as they head North, and therefore the northern part of the country gives the most water to derive from rivers. Once again, when choosing real locations for the Energy Ponds installations, more elevated ground is a plausible location as well. Most of the brown ovals on the map are in the broad vicinity of cities. This is another feature of the Polish geography: high density of population, the latter being clearly concentrated along rivers. This is also an insight into the function of Energy Ponds in real life. Such as it is simulated in Poland, i.e. in a densely populated environment, it is a true challenge to balance environmental services provided by wetlands, on the one hand, and the need for agricultural land, on the other hand. The simulation allows guessing that Energy Ponds can give more to city dwellers than to those living in the countryside.  

Another important trait of this specific simulation for Energy Ponds is the fact that virtually all the locations on the map correspond to places where wetlands used to exist in the past, before being drained and dried for the needs of human settlements. Geological and hydrological conditions are naturally conducive to swamp and pond formation in these ecosystems. It is important to prevent any ideological take on these facts. The present article is far from pushing simplistic claims such as “nature is better than civilisation”. Still, the draining and drying of wetlands in the past happened in the context of technologies which did not really allow reliable construction amidst a wetland-type environment. Today, we dispose of a much better technological base, such as comfortable barge-based houses, for example. The question of cohabitation between wetlands and human habitat can be reconsidered productively.   

Three levels of impact upon the riverine ecosystem are simulated as three hypothetical percentages of adsorption from the river through ram pumping: 5% of the flow, 10% and 20%, where 20% corresponds to the maximum possible pump-out as regards environmental impact. With these assumptions, the complete hypothetical set of 32 installations would yield 5 163 231 600 m³ a year at 5% of adsorption, and, respectively 10 326 463 200 m³ and 20 652 926 400 m³ with the adsorption rates at 10% and 20%.  In 2020, the annual precipitations were around 201,8 billion of m³, which means the 32 hypothetical installations of Energy Ponds could recirculate from 2,5% to 10% of that total volume, and that, in turn, translates into a significant environmental impact. 

Let’s focus on one particular location in order to further understand the environmental impact: the place where the Narew River mouths into Vistula River, north of Warsaw. The town of Nowy Dwór Mazowiecki, population 28 615, is located right at this junction of rivers. With the average consumption of water at the level of households being around 33,7 m³ a year, that local population consumes annually some 964 326 m³ of water. The flow rate in the Narew River close to its mouth into Vistula is 313 m³ per second, which amounts to a total of 9 870 768 000,00 m³ a year. Adsorbing 5%, 10% or 20% from that total flow amounts to, respectively, 493 538 400 m³, 987 076 800 m³, and 1 974 153 600 m³. From another angle, the same annual consumption of water in households, in Nowy Dwór Mazowiecki, corresponds to 0,0098% of the annual waterflow in the river mouth. The ‘Energy Ponds’ concept would allow to recirculate easily into the surrounding ecosystem the entire annual household consumption of water in this one single town.           

Let’s stay in this specific location and translate water into energy, and further into investment. The first issue to treat is a workable approach to using the capacity of ram-pumps in that specific location, or, in other words, a realistic estimation of the total pumped volume Q_C + Q_W . Metric flow per second at the mouth of the Narew River is 313 m³ on average. It is out of the question to install ram-pumps across the entire width of the stream, i.e. some 300 metres on average, as Narew is a navigable river. Still, what if we replaced width with length, i.e. what if a row of ram-pumps was placed along one bank of the river, over a total length of 1 km? Then, with the average efficiency of ram-pumps pegged at 50,5%, it can be assumed that 50,5% of the total flow per second, thus 50,5%*313 m³/s = 158,065 m³/s would flow through ram-pumps. With the baseline head of the Narew River being 92 meters, Table 2 below offers an estimation of the electric power thus possible to generate at the mouth, in an installation of ‘Energy Ponds’, according to equation (4).

Table 2 – Electric power [kW] possible to generate in an installation of ‘Energy Ponds’ at the mouth of the Narew River, Poland.

	Percentage of the total flow to be stored in wetlands (QW)
The relative height of elevated tanks	5%	10%	20%
10 meters	130 067,65	117 478,48	92 300,13
20 meters	131 602,92	120 549,01	98 441,19
30 meters	133 138,18	123 619,54	104 582,25

Source: author’s

When the highest possible elevated tanks are chosen (30 m), combined with the lowest percentage of the flow retained in wetlands (5%), electric power generated is the greatest, i.e. 133,138 MW. The optimal point derives logically from natural conditions. Comparatively to the artificially elevated tanks and their 30 meters maximum, the head of the river itself (92 meters) is an overwhelming factor. An interesting aspect of the ‘Energy Ponds’ concept comes out: the most power can be derived from the natural denivelation of terrain, with elevated tanks and their Roman siphon being just an additional source of potential energy. Further calculations, as regards the necessary investment outlays and the cost of storage, demonstrate that the lowest investment per unit of useful power – 987,16 Polish Zloty (PLN) per 1 kW – is reached precisely at the same point. Comparatively, the lowest power – generated at 20% of the flow adsorbed into wetlands and the lowest height of 10 meters of elevated tanks – is connected to the highest investment per unit, namely 1 111,13 PLN per 1 kW.       

The local urban population in Nowy Dwór Mazowiecki represents an annual consumption of electricity amounting to 828 752 048 kWh, and electricity hypothetically generated at that greatest power amounts to 1 118 360 718,72 kWh a year, thus covering, with an overhead, the local needs. This output of energy would be currently worth PLN 845,48 million a year at the retail prices of electricity[47] (i.e. when sold in a local peer-to-peer market). Should it be sold at wholesale prices[48], to the national power grid, it would represent PLN 766,08 million annually. Corrected with an annual Levelized Cost of Storage estimated at 107 161,99 PLN for Li-Ion batteries, that stream of revenue gives a 12-year discounted present value of PLN 5 134 million at retail prices, and PLN 4 647 million at wholesale prices.  With investment outlays estimated, according to the method presented earlier in this article, at some PLN 131,43 million, the project seems largely profitable. As a matter of fact, it could reach a positive Net Present Value already on the first year.

Comparatively, at the point of lowest power and highest investment per unit thereof, thus at 20% of adsorption into wetlands and 10 meters of height in elevated tanks, the 12-year discounted stream of revenue corrected for LCOS would be PLN 3 555,3 million (retail) and PLN 3 217,8 million (wholesale), against an investment of PLN 102,56 million.                   

Conclusion

The above-presented case study in the hypothetical implementation of the ‘Energy Ponds’ concept sums up optimistically. Still, the ‘Energy Ponds’ is still just a concept, and the study of its possible feasibility is hypothetical. That suggests caution, and the need to take a devil’s advocate’s stance. The case study can be utilized for both outlining the positive potential in ‘Energy Ponds’ and showing the possible angles of stress-testing the concept. The real financial value and the real engineering difficulty of investment in the basic hydraulic infrastructure of ‘Energy Ponds’ has been just touched upon, and essentially bypassed with a few assumptions. Those assumptions seem to be holding when written down, but confrontation with real life can bring about unpredicted challenges. This superficiality stems from the author’s own limitations, as an economist attempting to form an essentially engineering solution. Still, even from the economic point of view, one factor of uncertainty emerges: the pace of technological change. The method used for this feasibility study is a textbook one, similar to calculating the Levelized Cost of Energy: there is an initial investment, which we spread over the expected lifecycle of the technology in question. However, technologies can change at an unexpected pace, and the actual lifecycle of an installation – especially a highly experimental one – might be much shorter than expected. In the author’s (very intuitive) perspective, technological uncertainty is a big pinch of salt to add to the results of the case study.

Another factor of uncertainty is the real possibility of restoring wetlands in densely populated areas. Whilst new technologies in construction and agriculture do allow better overlapping between wetlands, cities, and farming, this is still just overlapping. At the bottom line, wetlands objectively take land away from many other possible uses. Literature is far from decisive about solutions in that respect. The great majority of known projects in the restoration of wetlands aim at and end up in restoring wildlife, not in assuring smooth coexistence between nature and civilisation. Some serious socio-economic experimentation might be involved in projects such as ‘Energy Ponds’.

Hydrogeneration in ‘Energy Ponds’ belongs to the category of Distributed Energy Resources (DER). DER systems become more and more popular, across the world, and they prove to be workable solutions in very different conditions of physical geography (McIlwaine et al. 2021[49]). Connection to local markets of energy, and into local smart grids, seems critical for the optimization of DER systems (Zakeri et al. 2021[50]; Touzani et al. 2021[51]; Haider et al. 2021[52]; Zhang et al. 2022[53]). How necessary is the co-existence – or pre-existence – of such a local network for the economically successful deployment of ‘Energy Ponds’?  What happens when the local installation of ‘Energy Ponds’ is the only Distributed Energy Resource around?

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