In 2013, signatories to the Paris Agreement committed to submit a national climate plan to mitigate climate change by reducing greenhouse gas emissions. Subsequently, one of the United Nations’ Sustainable Development Goals, established in 2015, is focused on affordable and clean energy. These two global initiatives have motivated several nations to promote renewable energy sources such as wind, solar, and biomass into their energy mix. As a result, several “green energy transition” initiatives are ongoing in countries such as Germany and Denmark, and subnational jurisdictions such as California, Scotland, and South Australia [1
]. Besides these major players, more than 150 countries have national targets for renewable energy in the power sector [2
The Japanese government recently reiterated its commitment to the projected energy mix for 2030, where fossil fuel-based generation will be reduced to 46%, and renewable energy will comprise 22–24%, of which solar energy will have a 7% contribution [3
]. There was a recent influx of solar PV installation mainly driven by the FIT program. The Kyushu region, located on Japan’s western tip, is one of the country’s leading regions in solar PV generation. Relative to the rest of the country, the region has higher solar power potential and cheaper land, which has driven solar power investments. As of early 2021, the region has a total installed capacity of 10 GW, and additional plants, which will increase this capacity further to roughly 16 GW [4
] by around 2027, are already approved. The share of solar PV generation has been steadily increasing in the region. In 2017, 2018, and 2019, solar PV generation accounted for 8.5%, 9.2%, and 10.1% of the total yearly generation, respectively. The International Energy Agency (IEA) classifies the impact of variable renewable energy (VRE) on the energy system’s operation into four phases. Japan, as a country, is already in phase 2 where there is a minor to moderate impact on the system operation, whereas Kyushu, as a region, was categorized as phase 3, where VRE determines the operation pattern of the system [5
]. This further shows that Kyushu is leading the country in terms of solar PV penetration and is already facing issues ahead of the rest of the country. Kyushu’s situation lends itself as a viable case study in exploring the potential impact of solar energy in reducing CO
emissions by replacing traditional energy sources with solar energy.
Coal remains to be the cheapest and most economically stable source of electricity for many countries. However, it is also one of the major contributors of CO
, which leads to global warming. Among the G7 countries, Germany (by 2038 [6
]), France (by 2023 [7
]), the United Kingdom (by 2024 [7
]), Italy (by 2025 [7
]), and Canada (by 2030 [8
]) have presented their coal phase-out plans. Other European Union member countries have also developed their phase-out plans within the next two decades, and Austria and Belgium have already phased-out their coal plants [7
]. Nonetheless, removing coal is a significant roadblock to the green energy transition in many countries, and as countries install increasing amounts of renewable energy, it might be time to consider reducing coal in the energy mix. Solar photovoltaics (PV) can be a green alternative to coal. However, the generation profile of solar energy is different from that of coal, which complicates the process of replacing coal with solar energy. Simultaneously, the variability of solar power requires another flexible source. Liquefied petroleum gas (LNG), given its flexibility, is often used to balance the VRE. Given these intertwined variables, it is necessary to understand the potential, limitations, and implications of using solar energy to replace coal, which are currently unclear.
Many countries see LNG as a bridge to a clean energy future that will pave the way for less coal in the energy mix [9
]. It is still a fossil fuel, but it produces less CO
, which is acceptable for now until a superior technology is available. Due to many countries’ tendency to rely on LNG to reduce their CO
emissions, the demand for LNG has steadily been increasing, which threatens its supply and price. Shell reported in their LNG Outlook 2020 that global demand for LNG increased by 12.5% to 359 million tons in 2019, which they attributed mainly to the role of LNG in the low-carbon energy transition [10
]. It has been reported that the price of LNG increased in October 2020 in anticipation of a colder winter in East Asia [11
]. This shows the volatility of LNG’s supply and price on the global market, which presents another factor for consideration in the analysis, since solar energy production needs LNG to a certain extent.
Aside from the potential CO
reduction benefits, reducing coal capacity could also reduce solar curtailment experienced by grids with high PV penetration. Kyushu started to suffer from curtailment in October 2018, which was explored in a previous study [12
]. Several studies have also explored this recent issue in Kyushu. Bunodiere and Lee [13
] explored several scenarios to mitigate solar curtailment in Kyushu using a logic-based forecasting method and concluded that reducing the region’s nuclear capacity will reduce curtailment. However, in their approach, they considered coal and LNG as thermal generators as a whole due to data limitations. A coal station behaves like a nuclear plant, since these two technologies are considered baseload generators. By treating coal as separate from LNG and as a baseload generator, it could also be said that coal could reduce curtailment. Although Japan initially used their pump hydro energy storage (PHES) to improve the flexibility of nuclear power plants [14
], it is now used to store excess solar electricity generation. Li et al. [15
] conducted a techno-economic assessment of large-scale PV integration with PHES and concluded that the PHES could effectively absorb some of the surplus PV production and could maintain low generation cost by using the surplus production. Since the available data regarding power generation in the region aggregate coal and LNG together, the understanding of coal generation in the energy balance is limited.
In order to fully understand the optimal conditions for coal, solar, and LNG production, it is necessary to conduct a power flow analysis to evaluate the impact of investing in more solar PV for driving coal decommissioning. This analysis will provide additional information about the energy balance, including information about solar power generation and curtailment, which are difficult to estimate. By gathering the generators’ capacity and generation profiles and the demand profiles, the optimization can calculate the hourly energy balance and minimize the necessary coal capacity and generation. This insight provides the necessary understanding of the potential and limitations of solar energy in regard to replacing coal. However, to ensure the robustness of the analysis and the recommendation, the demand and solar power generation’s stochasticity must be considered. It will be challenging to recommission a decommissioned plant due to an unforeseen circumstance; thus, careful analysis is necessary to account for potential variations.
Replacing part of coal’s electricity production with solar electricity production, coupled with LNG electricity production, is a subset of the generation expansion planning (GEP) problem. Koltsaklis and Dagoumas [16
] wrote a review article exploring the state-of-the-art generation expansion planning where they listed seven challenges to the GEP problem. One of the mentioned challenges is rooted in the risks involved in GEP. They enumerated several potential sources of risks and categorized them according to economic, political, regulatory, environmental, technical, social, and climate categories. Ioannou et al. [17
] reviewed the risk-based methods for sustainable energy system planning and categorized the risks in the same manner. They identified seven risk-based methods: mean-variance portfolio theory, real option analysis, Monte Carlo simulation, stochastic optimization technique, multi-criteria decision analysis, and scenario analysis.
Santos et al. [18
] conducted a study to identify uncertainties in the electricity system and demonstrated the corresponding impacts on the energy mix through scenario analysis. Their results highlighted that climate uncertainty represents primary risk sources for VRE, since it dictates the system’s power generation. A review on the energy sector vulnerability to climate change [19
] summarizes the authors’ contributions on climate and energy, and they noted that climate change could affect variables that influence electricity generation from photovoltaics and concentrated solar power. The review highlighted that global solar radiation has increased in southeastern Europe [20
] and decreased in Canada [21
]. They also highlighted that power output calculations should account for air temperature, since it impacts the solar cell’s efficiency [19
Ioannou et al. [17
] noted that energy planning has extensively used stochastic optimization techniques, and the stakeholder’s motivation mainly drives the constraints. They also mentioned that the Monte Carlo simulation has many advantages, but it requires considerable data inputs to create probability density functions. Alternatively, scenario analysis evaluates the risks by creating potential future developments that range from the worst-case to the best-case scenario, which could then cover all the possible risks in the analysis. As highlighted by several authors [18
], climate, and by extension weather, must be considered in modeling solar energy generation. Factors such as the changing solar irradiance and ambient temperature could influence solar panels’ variability and efficiency.
By carefully identifying the test cases, scenario analysis is sufficient for ensuring the robustness of the analysis. The initial problem is then rooted in creating the scenarios representing the worst case, the best case, and the cases in between. The weather data analysis can provide the representative years that fit the scenario targets, such as warm summers, colder winters, extreme summers, and extreme winters. Although such data are limited, datasets could be synthesized based on the historical relationship between temperature and demand. Solar generation could be calculated from the irradiance and ambient temperature data. The robustness of the analysis and recommendation can be addressed by combining scenario analysis and past weather data.
Therefore, in this study, an hourly power flow analysis was conducted to understand the potential, limitations, and implications of using solar energy as a driver for decommissioning coal power plants. Understanding these factors can provide the necessary recommendations and precautions for energy planners. Since LNG scarcity is anticipated, LNG quota is one of the primary constraints. In order to ensure the robustness of the results, this study presents a straightforward weather-driven scenario generation that utilizes historical weather and electricity demand data processed through machine learning algorithms to generate scenarios that account for weather variations. Through the weather-driven approach, the study aims to reveal the impact of yearly variations in the factors that must be considered for long-term planning that reduce CO emissions while ensuring grid reliability. The Kyushu region in Japan was used as a case study since (a) it is continuously increasing its solar capacity, (b) it has a fleet of coal power plants older than 40 years old ready for decommissioning, and (c) it has enough LNG power plant capacity to support the initial transition.
The code for the weather-driven approach used in this study is available through a public GitHub repository [22
], where most of the code and diagrams used in this paper are documented in jupyter notebooks. The approach, with minor changes, could easily be replicated in other nations or regions provided that historical hourly temperature, irradiance, and demand data are available.
discusses the methodology for the weather-driven approach, including data and data processing, weather-based data generation, and hourly simulation. The results are then presented in Section 3
, and the implications are discussed in Section 4
. Finally, the conclusions are drawn in Section 5
4.1. Potential and Limitations of Solar PV in Coal Decommissioning
Although it cannot phase-out coal, the results show that solar energy has enough potential to be the driver for coal decommissioning with LNG’s help. It has also been shown that the decommissioning potential is robust against yearly weather-driven demand, and standby-plants could be used for the colder and warmer periods of the year. Although solar power has limitations in reducing coal capacity, it continually decreases the necessary coal generation, thereby reducing the load factor of coal plants and the corresponding CO emissions.
In Kyushu’s case, given the 10 GW solar capacity along with a 16 TWh complementary LNG quota, 3.5 GW of the 7 GW coal power plants could be decommissioned. This configuration is already achievable by increasing the LF of the combined-cycle plants of KyEPCO from 20% to 44%. Beyond 12 GW installed solar capacity, solar power alone has no impact on reducing the coal capacity, but it could still reduce coal generation. Compared to the reference scenario, it was shown that CO emissions could be reduced by 27% through 20 GW of solar power and a 20 TWh annual LNG quota. The reduction could reach 37% if all the LNG plants in the region are utilized at 60% LF. As a related consequence, reducing coal and introducing more LNG reduced solar curtailment. This potential and limitations show that energy planners should take the necessary precautions in adding solar energy to the grid since there is an appropriate balance. Solar can reduce coal capacity, but it alone cannot phase-out coal. As was shown in Kyushu’s case, a thorough analysis of the situation that includes complementary energy sources should be considered in evaluating the potential of solar power in coal decommissioning.
4.2. Implications of Solar PV in Coal Decommissioning
Solar has its drawbacks in the form of cost and dependence on complementary flexible generators. The results show that in countries like Japan, where solar power remains to be more expensive than conventional generators—solar power presents an additional cost. Its dependence on flexible generators, which LNG currently fills, poses a threat to its ability to stand-alone. As the demand for LNG steadily increases, this will threaten its supply and price. The cost of LNG could exacerbate the cost problems of solar.
In Kyushu’s case, increasing the solar capacity from 10 GW to 16 GW and 20 GW increases the levelized cost of generation by 3.39% and 4.69%, respectively. Increasing the LNG quota has a minor impact at the moment since the current LNG price is only about 12% higher than coal. In contrast, solar is still almost twice as expensive as coal. Solar prices around the world have been decreasing, and it might decrease in Japan in the future. The impact on CO and cost now becomes a policy decision, and the ratio between these two factors presents several potential combinations between LNG quota and installed solar capacity that could yield identical cost or the same CO targets as seen in and . More LNG is necessary when cost is prioritized, but it will lead to more dependence on LNG. Alternatively, by investing more in solar capacity, it could lead the CO reduction efforts and local power generation. This scenario entails lower dependence on both coal and LNG, which are both imported fuels. As with the previous results, the impact of weather on these values is evident, as seen in the variations in the levelized cost and levelized CO emissions.
4.3. Potential Solutions beyond Solar PV
The supply and demand mismatch in winter and summer is one of the major roadblocks in the total phase-out of coal power plants through solar energy. Diurnal storage will be enough to solve the mismatch during summer, but seasonal storage or seasonal generation will be necessary for winter. Since there is still enough excess energy during peak solar production in summer, storage is the straightforward solution once these options become economically feasible. However, since there is less solar energy in winter, there is not enough excess solar energy for diurnal storage to work, which opens an opportunity for seasonal technology. Seasonal storage in the form of power-to-gas (P2G) could store the excess solar in autumn for winter. Combined heat and power (CHP) plants could be operated at a higher capacity in winter if local water heating is established.
4.4. Impact of Weather on Energy Transition Plans
The stochastic nature of demand and renewable energy sources was the primary motivation for developing the weather-driven approach since energy transition recommendations should consider scenarios that will test the limits of the planned energy mix. The variations are significant at 400 MW to 600 MW coal capacity, as seen from the results. In Japan’s case, this translates to 1–3 coal power plants, but for smaller nations with smaller plants, this could be composed of more than five plants that should be on standby in the event of an extreme weather condition. Coordinating smaller plants will require more dialogue and agreements between the government and plant operators. Consequently, the government could also run standby plants to ensure the reliability of the system. It has also been shown that weather influences the potential for CO reduction and the system’s overall annual generation cost. Beyond coal decommissioning, weather will remain a necessary variable in energy planning since it influences the demand, which is the primary source of stochasticity in the analysis. As more VREs are added to the green energy transition, weather becomes a crucial variable for both wind and solar. Rainfall data could also influence hydropower generation, which was not explored in this study. It could also influence the viability of PHES since this requires sufficient water reservoirs affected by rain and water evaporation. Little is known about wave energy’s potential, but the weather will also influence it since it depends on nature.
4.5. Importance and Limitation of the Proposed Approach
The proposed weather-driven scenario-based analysis revealed the importance of the LNG quota, demand variations, and solar generation through the annual hourly simulation. System reliability could be analyzed using the duration curve, but this does not show the hourly balance, which is greatly influenced by demand and solar generation’s stochasticity. Through careful selection of representative years, the range of potential scenarios was identified and analyzed to ensure robust results. However, the approach is dependent on the yearly assignment and is limited by the probabilistic matching of weekends and holidays to high irradiance days. The former is influenced by human behavior, while the latter is non-deterministic. Thus, although the simulation considered the yearly variations, the probability of a low irradiance day being matched to a high-demand weekday was not covered by the approach. Nonetheless, the approach can be used to provide robust recommendations for green energy transition since it covers the stochastic nature of demand and variable renewable energy. In this study, the approach was used to determine the minimum coal capacity that can ensure the system’s reliability, but it could also be used for energy storage assessments and capacity planning. This study only used a single-bus network, but it could be expanded to a national grid level by representing each region as a bus. The approach can then be used for grid expansion planning.
Driven by the idea of transitioning to a green electricity grid, an hourly power flow analysis was conducted to understand the potential, limitations, and implications of using solar energy as a driver for decommissioning coal power plants. The weather-driven scenario analysis ensured the robustness of the results and recommendations. The analysis revealed that solar power could reduce about half of Kyushu’s coal capacity with the aid of LNG. Beyond 12 GW, solar power could not reduce the minimum coal capacity necessary to ensure the system’s reliability, but it could still reduce the coal generation and the overall CO emissions. The reduction in coal capacity comes at a cost, since solar power is still relatively more expensive in Japan. By installing 20 GW of solar PV systems and having 28 TWh of available LNG, the levelized CO emissions could be reduced by 37%, but this would increase the levelized cost of generation by 5.6%. Most of the price increase is owed to the price of solar electricity generation, which remains high in Japan. In Kyushu’s case, this change could be achieved without constructing additional power plants, since the LNG plants are operated at a low LF. However, additional planning is necessary to acquire more LNG. Countries that use LNG plants as peak-load generators share the same potential, and the results show that a minor change in the system could have a significant impact on emission goals.
The results emphasized that solar power with the aid of LNG could partially replace coal capacity, but it alone could not phase-out coal. For energy planners who are only starting to increase their solar capacity, insights from this work could help with understanding the interactions between coal, solar, and LNG electricity generation. For planners in countries with a considerable amount of solar power (>8%), the results from this study could serve as a precaution by highlighting the risks of further increasing the solar power penetration. Although solar power helped solve midday peak power, the problem remains because it simply shifted to periods where there is no solar energy. Summer and winter are challenging periods due to the increase in peak demand. Although it is counterintuitive, solar energy is not enough during summer, or, to be more precise, misaligned since the problem occurs in the late afternoon. Diurnal storage can address the misalignment in summer, but winter presents a more intricate problem, since the solar energy is insufficient. Thus, exploring other technologies that could further complement solar energy is necessary.
The weather-driven approach revealed the importance of weather in the analysis, as it affected the results to varying degrees. In addition, 400–600 MW of standby coal capacity is necessary due to the yearly fluctuations. Coal generation, coal load factor, curtailment rate, and CO emissions vary by 7–18%, 8–27%, 0–5%, and 6–8%, respectively. Identifying the representative year is crucial since it should cover the worst case, best case, and the cases in between. Energy planners and policymakers should consider the weather when analyzing energy plans, as it could provide a range of values that can guide them in making the correct decisions. Since the approach can generate scenarios based on weather data, it could also be used for storage assessment and capacity planning. The approach could also be used for grid expansion planning by increasing the number of buses and modeling multiple demands. These energy planning topics could also benefit from the range of insights generated through the weather-driven approach.