Hybrid Renewable Energy Systems - Powering large industrial loads
- Jul 20, 2021 8:29 am GMT
Note: The ideas and views expressed in this article are the authors alone and do not reflect those of any employer or other organisation. This work is based on hybrid renewable energy system (HRES) techno-economic optimisation models the author has independently developed.
There is clearly an urgent need to decarbonise all human activities to mitigate anthropogenic climate change. This is likely to require a rapid transition of all energy production and usage, including electricity generation, to net zero emissions. In order to continue powering major industrial activities, reliable large-scale sources of electricity produced with close to zero greenhouse gas emissions will be required. Large-scale hybrid renewable energy systems could play key roles in decarbonised electricity grids. Optimisation modelling of such systems for powering large industrial loads is discussed.
- A constrained non-linear optimisation modelling methodology has been developed for the sizing and operation of a large-scale hybrid renewable energy system (HRES) based on variable renewable energy (VRE) generation and energy storage.
- The example HRES consists of a solar PV farm and pumped hydro energy storage (PHES) system.
- The optimisation results point to a large-scale HRES technical design and operational strategy that could provide firm balancing for a large industrial load with constant power consumption.
- Simulation results indicate that a hybrid 3 GW solar farm and 1.6 GW / 12 GWh two unit aggregated pumped hydro system could power a 1 GW constant industrial load using intra-day energy shifting, for a location with good solar resources and low inter-day variance but relatively modest difference in reservoir elevation.
- Variable-speed pump-turbine units are necessary to provide sufficiently flexible dispatchable power for reliable firming and balancing over a diurnal period.
- HRES energy arbitrage revenue opportunities in the Australian National Electricity Market, capital costs, operating and maintenance expenditures, and regulatory issues are not discussed here.
- Optimisation modelling utilising conservative lower estimates of solar (or wind) local energy resources could permit HRES sizing to reliably power large industrial loads to a specified level of long-term risk.
What is the problem and how was it solved?
A hybrid renewable energy system (HRES) combines multiple renewable energy and/or energy storage technologies into a single plant. These integrated systems could play a key role in the present energy transition by efficiently providing reliable, low to zero emissions, low cost, dispatchable electrical power. There is an extensive HRES mathematical modelling literature, including for hybrid pumped hydro-wind-solar systems.
Variable renewable energy (VRE) sources, including solar, wind, wave and tidal, are intermittent or fluctuating on varying time scale(s) at a given location. The integration of high levels of VRE generation into electricity grids presents enormous decarbonisation opportunities but also some potential challenges around system reliability and security.
A constrained non-linear optimisation model has been developed for the sizing and operation of an example large-scale (grid-scale) HRES consisting of a hybrid solar photovoltaic (PV) farm and pumped hydro energy storage (PHES) system. A ‘load-following’ optimisation problem is solved for the large-scale HRES design and operational strategy that provides ‘good’ balancing power for a 1-Gigawatt (GW) load representative of a large industrial plant operated repetitively at constant power over 24-hour periods. The objective of the optimisation problem is to co-minimise the sum of half-hourly squared differences between the total electrical power output by the HRES and the load profile plus the squared fractional grid electrical power consumed in PHES pumping. The PHES upper reservoir is constrained to be ‘re-charged’ at the end of the day to near its initial state. An artificial intelligence evolutionary algorithm is primarily used to solve the non-linear, non-convex constrained optimisation problem.
An off-river (closed-loop) PHES system is hypothesised for storage of solar PV farm generated energy and time shifting to power the load when it is most needed (in this case when the sun is down). The PHES system is based on water flow through penstocks (usually pipes or tunnels), between two reservoirs at different elevations. The gravitational potential energy of the water stored in the upper reservoir is converted to kinetic energy in the water flow through the penstocks to the lower reservoir. Electrical power is generated by water flow through turbine units in a powerhouse near the lower reservoir. Water is later pumped back to the upper reservoir (requiring electrical power), with a net loss of energy across the PHES charge-discharge cycle. Co-location of the HRES generation and storage components (and as close as practicable to the industrial load) should minimise transmission losses, variability and connection costs. The off-river nature of the PHES system is emphasised in order to minimise potential environmental impacts and gain social licence.
The PHES system is modelled as an aggregate of two reversible pump-turbine units of unknown nameplate capacity that can be variable- or fixed-speed, with literature values for pumping and generating mode efficiency and minimum output. The storage capacity of the PHES system and the hydrostatic head due to elevation difference between the upper reservoir water intake and egress in the bottom reservoir are unknowns. Solar resources are consistent with a ‘typical’ north Queensland (Australia) summer day in a region with limited seasonality. The solar farm has unknown nameplate capacity.
Figure 1 schematically illustrates the flow of electrical power between the key components of the modelled system, composed of the HRES, industrial load and the electricity grid. The flow of electrical power associated with pumping, idle and generating states for each of the PHES units at various times of the day are indicated by arrows in the diagram. The possible flow of power from the HRES components to the electricity grid and from the electricity grid to the industrial load are indicated by the grey lines in the diagram as permitted but not explicitly modelled in this study.
Figure 1: Schematic of the flow of electrical power between the key components of the modelled system. The direction of flow of electrical power is indicated by arrows. The HRES boundaries are schematically illustrated by the dashed lines. PHES pump-turbine unit individual operational states at various times of the day are shown inside ovals.
What HRES design provided ‘good’ load-following results?
Figure 2 shows the contributions to the electrical power flow between the HRES and the industrial load for the optimal ‘load-following’ modelled day. Results indicate that a suitably sized HRES of this type can reliably power a 1 GW constant load over most of the modelled day. The pump-turbine nameplate capacity is estimated to be about 1020 Megawatt (MW) for one PHES unit and 580 MW for the other. The minimum PHES storage capacity for repetitive diurnal operation is estimated to be about 12 Gigawatt-hours (GWh) [a storage duration of about 12 hours] or about 36 Gigalitres (GL) of water. This was for twin reservoirs of 100 hectares (1 square kilometre) cross-sectional area. The minimum difference in reservoir elevation is as little as 120 metres for PHES reservoirs of equal cross-sectional area, depending on the maximum flowrate permitted by the PHES pump-turbine units and penstocks. By comparison, the Snowy 2.0 PHES system currently under construction in Australia has 2 GW power rating and 350 GWh of storage. The solar PV farm is estimated to have a nameplate capacity of about 3030 MW.
What HRES operational profile provided ‘good’ load-following results?
The industrial load is almost entirely powered by the HRES over the modelled day. The best ‘load-following’ capabilities are found for variable-speed PHES units, with model power output of the hybrid system being balanced to within about 20 MW of the required load for 22 hours of the day. The optimal operational strategy is to power the load exclusively by solar PV for about 11 hours during the day, exclusively by PHES generation for about 10.5 hours during the night and use a combination of solar PV and PHES generation to power the load for the remainder of the day. Solar PV also powers PHES pumping for 10.5 hours during the day. The lower power PHES unit is primarily utilised for pumping during the day, while the higher power PHES unit is used for both pumping during the day and generation at night. There is negligible use of grid power for PHES pumping, implying almost nil associated greenhouse gas emissions to power the load. There is also almost no potential curtailment of the output of the solar PV farm for the modelled day.
What are the effects on HRES operation of limits on PHES flexibility?
The flexibility limitations of the PHES units are apparent in figure 2 as deviations of the HRES total power output from the required load for an hour in both the early morning and late afternoon, associated with changes between pumping and generating modes (shown in ovals). The limited shortfalls in electrical power provided by the HRES to the industrial load at certain times could be compensated by direct connection to the electrical grid. Conversely, excess power from the HRES at certain other times could be sold directly to the grid.
Figure 2: Contributions to electrical power flow to the industrial load and electrical grid for the optimal ‘load-following’ modelled day. Net total power provided to the load and grid over the day is indicated by the red line. Net total power at times where limitations in PHES flexibility result in a substantial mismatch with the load requirements are indicated in ovals.
What did the PHES actually do?
Figure 3 shows the contributions to the electrical power flow to and from the PHES for the same ‘load-following’ modelled day. The constant PHES generation at night to fully power the industrial load is readily apparent. The flexible dispatchable response of the PHES units (ability to be ramped up or down on demand) is apparent in the decreased/increased generation output in the early and late daylight hours. Both PHES units are idle for only half an hour in the entire modelled day. Solar PV powering of flexible PHES pumping during most of the daylight hours is also readily apparent throughout the day. A maximum of about 1500 MW of solar PV power is used for PHES pumping in the middle of the day.
Figure 3: Contributions to the electrical power flow to and from the PHES for the same ‘load-following’ modelled day. Net PHES generated power provided to the load and grid over the day is indicated by the red line.
What power was generated by the solar PV farm and where did it go?
Figure 4 shows the electrical power flow generated by the solar PV farm for the same ‘load-following’ modelled day. Contributions to the electrical power flow to the industrial load and grid plus for PHES pumping are shown over the day. The split of power from the solar PV farm that goes to PHES pumping between 07:30 and 17:30 varies from about 33% in the early morning and late afternoon to a maximum of about 60% in the middle of the day. For the periods 06:00-07:00 and 18:00-19:00, all solar PV power goes to the load and grid, in accordance with the flexibility limitations of PHES pumping.
Figure 4: Contributions of electrical power flow generated by the solar PV farm to the industrial load and grid plus to PHES pumping for the same ‘load-following’ modelled day. Total solar PV farm generated power over the day is indicated by the red line.
How could you get better ‘real-world’ and modelling results?
Enhanced balancing and firming capabilities for the HRES could be gained by increasing the number of pump-turbine units, improving PHES flexibility, using a combination of energy storage technologies (electrochemical batteries for shallow storage duration of a few hours), over-build of solar PV or PHES generation capacity, or use of complementary solar and wind resources.
Further decreases in the minimum required difference in reservoir elevation to permit the best ‘load-following’ HRES capabilities can be achieved when the lower reservoir has a substantially larger cross-sectional area than the upper. The underlying large-scale energy storage, generation and consumption (pumping) process model for the PHES considers electrical power generated by the kinetic energy of water drainage from the upper to the lower reservoir. This is primarily due to the standard pumped hydro effect, derived from water gravitational potential energy proportional to the hydrostatic head associated with reservoir elevation difference. It also includes a lagoon hydraulic effect, derived from water gravitational potential energy proportional to the squared depth of the water column in the upper reservoir that is subject to drainage. The lagoon hydraulic effect for drainage between reservoirs with unequal cross-sectional areas increases in relative importance to the pumped hydro effect for smaller differences in reservoir elevation difference hydrostatic head. PHES designs that take advantage of the lagoon hydro effect (balanced against increased reservoir construction costs) could assist in relaxing the geographical constraints on siting of such systems due to minimum required differences in reservoir elevation.
There are numerous modelling issues associated with large-scale HRES with significant potential practical impact that could be explored. This includes analysis of the economic feasibility of large-scale HRES systems options for specific applications and locations within electricity markets. Comparative modelling of more distributed options for HRES powering of large industrial loads, such as various combinations of large-scale VRE and multiple electrochemical batteries (or other forms of energy storage including hydrogen from electrolysis). Optimisation modelling of inter-day and longer-term HRES sizing and operation to assess the statistical accuracy of an approach based on a single or small number of days with risk-based historical estimates of VRE resources. The effect of the stochastic (random) aspect of VRE resources on optimal HRES sizing and operation. Assessment of the limitations and opportunities for HRES in geographical locations with strong renewable resource seasonality. Finally, investigation of optimisation of HRES sizing and operation for more complex load profiles and relaxed firming requirements.
It is important to remember that in most endeavours, you can get to where you want to go by several paths, but only if you are sufficiently motivated, have clearly defined objectives and the constraints are well understood.
Get Published - Build a Following
The Energy Central Power Industry Network is based on one core idea - power industry professionals helping each other and advancing the industry by sharing and learning from each other.
If you have an experience or insight to share or have learned something from a conference or seminar, your peers and colleagues on Energy Central want to hear about it. It's also easy to share a link to an article you've liked or an industry resource that you think would be helpful.