Pieces of a puzzle: solar-wind power synergies on seasonal and diurnal timescales tend to be excellent worldwide

Nyenah, Emmanuel; Sterl, Sebastian; Thiery, Wim

doi:10.1088/2515-7620/ac71fb

Cited by 8 publications

(7 citation statements)

References 41 publications

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“…Therefore, Huang et al formulated complementary metrics for assessing the time and magnitude based on the probability of renewable energy power meeting load requirements and the frequency of insufficient energy supply occurrences (Huang et al, 2022). Meanwhile, Nyenah et al exploited the Pearson correlation coefficient to describe the complementarity under different operating conditions of the system (Nyenah et al, 2022). However, the above studies made many assumptions to attain the linear correlation coefficient.…”

Section: Introductionmentioning

confidence: 99%

Deep learning-based correlation analysis for probabilistic power flow considering renewable energy and energy storage

Xia,

Xiao,

2024

Front. Energy Res.

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Developing photovoltaic (PV) and wind power is one of the most efficient approaches to reduce carbon emissions. Accumulating the PV and wind energy resources at different geographical locations can minimize total power output variance as injected into the power systems. To some extent, a low degree of the variance amplitude of the renewable resources can reduce the requirement of in-depth regulation and dispatch for the fossil fuel-based thermal power plants. Such an issue can alternatively reduce carbon emissions. Thus, the correlation problem by minimizing the variance of total PV and wind power plays a vital role in power system planning and operation. However, the synergistic effect of power output correlation is mainly considered on the generation side, and it is often neglected for the correlation relationship between the power grid components. To address this problem, this paper proposes a correlation coefficient analysis method for the power grid, which can quantify the relationship between energy storage and the probabilistic power flow (PPF) of the grid. Subsequently, to accelerate the mapping efficiency of power correlation coefficients, a novel deep neural network (DNN) optimized by multi-task learning and attention mechanism (MA-DNN) is developed to predict power flow fluctuations. Finally, the simulation results show that in IEEE 9-bus and IEEE14-bus systems, the strong correlation grouping percentage between the power correlation coefficients and power flow fluctuations reached 92% and 51%, respectively. The percentages of groups indicating weak correlation are 4% and 38%. In the modified IEEE 23-bus system, the computational accuracy of MA-DNN is improved by 37.35% compared to the PPF based on Latin hypercube sampling. Additionally, the MA-DNN regression prediction model exhibits a substantial improvement in assessing power flow fluctuations in the power grid, achieving a speed enhancement of 758.85 times compared to the conventional probability power flow algorithms. These findings provide the rapid selection of the grid access point with the minimum power flow fluctuations.

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Section: Introductionmentioning

confidence: 99%

Deep learning-based correlation analysis for probabilistic power flow considering renewable energy and energy storage

Xia,

Xiao,

2024

Front. Energy Res.

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“…This brings a number of operational planning issues in power systems with high variable RES penetration levels [10]. However, the complementarity or synergy of the wind and PV energy availability, which exists in almost all regions in the world [11,12], is a favorable feature of these energy sources that should be taken advantage of when planning the optimal structure of generating capacities in national energy systems. The main challenge is to maintain equality between the generated active power and the consumed active power by unit commitment and dispatching of suitable balancing capacities through operational planning for different time scales (yearly, monthly, weekly, daily, and even intra-daily).…”

Section: Introductionmentioning

confidence: 99%

“…Although the concept of complementarity is often not directly discussed, complementarity of renewable resources is implicitly used in the optimization of energy systems when RES are modelled as spatially distributed [74]. Supply side complementarity for different locations around the world is investigated in [11] without considering the complementarity with the local demand profiles, although it was recognized as an important aspect. Paper [11] used the stability coefficient defined in [12] to describe hybrid mixes of complementary variable RES.…”

Section: Introductionmentioning

confidence: 99%

“…Supply side complementarity for different locations around the world is investigated in [11] without considering the complementarity with the local demand profiles, although it was recognized as an important aspect. Paper [11] used the stability coefficient defined in [12] to describe hybrid mixes of complementary variable RES. In paper [12] it was discussed that hybrid mixes of variable RES could be 'tuned' to better match the local demand profile before calculating their stability index.…”

Section: Introductionmentioning

confidence: 99%

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Novel Planning Methodology for Spatially Optimized RES Development Which Minimizes Flexibility Requirements for Their Integration into the Power System

Škrbić

Đurišić

2023

Energies

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An optimization model which determines optimal spatial allocation of wind (WPPs) and PV power plants (PVPPs) for an energy independent power system is developed in this paper. Complementarity of the natural generation profiles of WPPs and PVPPs, as well as differences between generation profiles of WPPs and PVPPs located in different regions, gives us opportunity to optimize the generation capacity structure and spatial allocation of renewable energy sources (RES) in order to satisfy the energy needs while alleviating the total flexibility requirements in the power system. The optimization model is based on least squared error minimization under constraints where the error represents the difference between total wind and solar generation and the referent consumption profile. This model leverages between total energy and total power requirements that flexibility resources in the considered power system need to provide in the sense that the total balancing energy minimization implicitly bounds the power imbalances over the considered time period. Bounding the power imbalances is important for minimizing investment costs for additional flexibility resources. The optimization constraints bound the installed power plant capacity in each region according to the estimated technically available area and force the total energy production to equal the targeted energy needs. The proposed methodology is demonstrated through the example of long-term RES planning development for complete decarbonization of electric energy generation in Serbia. These results could be used as a foundation for the development of the national energy strategy by serving as a guidance for defining capacity targets for regional capacity auctions in order to direct the investments in wind and solar power plants and achieve transition to dominantly renewable electricity production.

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“…As an archipelagic nation subjected to monsoonal winds, it experiences two distinct seasons, offering opportunities to harness wind energy [16]. The synergy of solar and wind energy promises a complementary power source, with solar being predominant during the https://doi.org/10.56578/jse020303 dry season and wind during the rainy season and nocturnal hours [17,18]. The use of hybrid solar and wind energy has proven more effective than relying solely on solar energy in various regions of Indonesia [19].…”

Section: Introductionmentioning

confidence: 99%

Techno-Economic Evaluation of Hybrid Photovoltaic-Wind Energy Systems for Indonesian Government Buildings

Prasetyo,

Regannanta,

Birawa

et al. 2023

JSE

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The burgeoning population in Indonesia necessitates an escalation in energy provision. The reliance on diminishing fossil fuels, coupled with their adverse environmental repercussions, propels the exploration of renewable alternatives. This study investigates the techno-economic viability of implementing hybrid photovoltaic (PV) and wind turbine systems across government edifices within five urban locales: Semarang, Surabaya, Yogyakarta, Jakarta, and Denpasar. Employing the Hybrid Optimization Model for Electric Renewables (HOMER), simulations and optimizations of the hybrid systems were conducted, aiming to fulfil an electrical demand of 2636.1 kWh. The analysis is predicated on a 25-year operational lifespan. Results indicate that Denpasar presents the optimum potential for the hybrid system, with an annual electricity generation of 1,360,195 kWh surpassing the consumption demand of 1,214,136 kWh. The Net Present Cost (NPC) is calculated at IDR 27,529,340,000.00 and the Cost of Energy (COE) at IDR 997.17, yielding an attractive investment prospect with a Break Even Point (BEP) at 8.2 years. The estimated initial outlay for the Denpasar government building's PV system stands at IDR 4,149,376,743.96. The findings underscore the financial and technical feasibility of harnessing solar and wind synergies for sustainable energy solutions in Indonesian government infrastructure. These outcomes have pivotal implications for policymaking and strategic energy planning, demonstrating a replicable model for renewable integration in similar tropical regions.

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Pieces of a puzzle: solar-wind power synergies on seasonal and diurnal timescales tend to be excellent worldwide

Cited by 8 publications

References 41 publications

Deep learning-based correlation analysis for probabilistic power flow considering renewable energy and energy storage

Deep learning-based correlation analysis for probabilistic power flow considering renewable energy and energy storage

Novel Planning Methodology for Spatially Optimized RES Development Which Minimizes Flexibility Requirements for Their Integration into the Power System

Techno-Economic Evaluation of Hybrid Photovoltaic-Wind Energy Systems for Indonesian Government Buildings

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