1. Introduction
Due to the non-renewability of fossil energy, its large-scale development and utilization has led to the depletion of limited resources [
1]. At the same time, in the process of its development and utilization, fossil energy also brings serious environmental and economic problems such as climate warming and ecological destruction [
2]. These create challenges for the sustainable development of human society in the future. As a modern international metropolis, it is imperative that Beijing develops new green energies. During the period of the 12th Five-Year Plan, Beijing has achieved positive results in the development of new and renewable energies [
3]. However, gaps remain in terms of the development requirements for accelerating the construction of green and low carbon energy options, safety and efficiency, and covering urban and rural modern energy systems [
4]. The main performance gaps are as follows: First, the proportion of new and renewable energy consumption is still low, the degree of integration with conventional energy systems is not high, and the development of key regional resources is insufficient [
5]; Second, policies and regulations, market mechanisms etc. need to be further improved, and the development environment for new and renewable energies needs to be optimized [
6]; Third, the levels of independent innovation, core key technology research, and transformation of results still need to be further improved, and high-end industries such as R&D and services need to be strengthened [
7]. Therefore, in order to promote the green, intelligent and efficient transformation of urban energies, accelerating the development and utilization of new and renewable energies is of great significance.
In the past, the development and utilization of new and renewable energies has had serious problems such as the heavy investment required for construction, light planning management, heavy requirements for technology advancement, and light overall planning [
8]. As a result, the energy structure was seriously unbalanced, and its development was greatly restricted. New and renewable energies cannot form a scale effect or form a synergy with traditional energies, and cannot fully substitute for, or even exert a supplemental effect on, traditional energies [
9]. Therefore, it is particularly important to comprehensively consider the multi-level goals of society, the economy and the environment, and to implement total control in optimizing the development structure ratio of various energy forms according to pre-established new and renewable energy development goals [
10]. In addition, on the one hand, climate change has led to a significant increase in the frequency of extreme weather (high temperature phenomena) in Beijing, and an increase in electricity demand (especially peak) [
11], increasing the imbalance between power supply and demand. On the other hand, climate change has triggered dramatic changes in meteorological factors such as wind speed, light and precipitation [
12], which may affect the output of wind power, photovoltaic power and hydropower. These changes will increase the complexity of the issues involved in Beijing’s power system management and planning, and will bring further impacts for the balance of power supply and demand and energy security.
In the past few decades, domestic and foreign scholars have carried out many studies on the impact of climate change on energy supply and demand. In terms of the impact of climate change on energy demand, Ruth and Lin used dynamic computer modeling and time series analysis to analyze energy and power demand in the USA [
13]; Nateghi and Mukherjee established a multi-paradigm framework for estimating the climate sensitivity of end-use energy demand in Indiana [
14]; Auffhammer et al. applied temperature response functions and a global climate model to simulate the relationship between electricity demand and temperature in the USA [
15]. In most cases, existing literature has analyzed the impact of climate change (especially temperature variation) on energy demand. However, this effect has rarely been incorporated into design studies for subsequent energy structure adjustment programs. In terms of the impact of climate change on energy supply, Pašičko et al. used a global climate model to assess renewable energy supply in Croatia [
16]; Crook et al. studied photovoltaic and solar power output based on an ocean-atmosphere climate model [
17]; and Lucena et al. developed a generation system simulation model to analyze renewable energy production in Brazil [
18]. Many previous studies have analyzed the impact of changes in meteorological elements (wind speed, radiation, and precipitation) on energy supply, but few of these effects have been incorporated into the optimization model for energy structure adjustment. Examples of the application of optimization techniques in energy structure design and allocation fields [
19,
20,
21,
22,
23,
24] include Schmidt et al. who assessed the environmental effect in Brazil by optimizing the daily dispatch of energies [
19]; Kocaman et al. constructed an optimal sizing relationship of energy generation to ease concerns about electricity generation [
20]; Pereira et al. proposed a mixed integer optimization model to evaluate costs and CO
2 emissions of electricity generation [
21]; Dong et al. developed a Bayesian interval robust energy system optimization method for a regional energy system planning model [
22]; Prebeg et al. proposed a two-level approach with multi-objective optimization at the global level, which was used to design a Croatian Energy System [
23]; and Yu et al. developed an interval-stochastic basic-possibilistic programming method for planning sustainable energy systems, which could facilitate analysis of the tradeoff between economic objective and pollutant mitigation [
24]. Previous studies have shown that the optimization method was suitable for dealing with energy planning and management issues. It helped decision-makers to determine the optimal energy development and structural adjustment programs, under resource and environmental constraints, necessary in order to meet users’ power needs. However, past research has often focused on the study of optimization algorithms and some key model parameters were based mostly on predictions and estimates. In addition, the interaction between climate change and energy supply and demand was also often overlooked in past research. In fact, the sharp increase in electricity demand caused by climate change and the volatility of new energy supplies caused by changes in meteorological factors (including wind speed, radiation and precipitation), will bring further impacts on the balance of power supply and demand [
25].
There are several relevant published works in the literature which focus on this topic for developed countries, whereas other places such as Beijing have not been fully investigated. Under the conditions of climate change, Beijing’s power load and energy demand are increasing. Previous studies have isolated load simulations, output predictions, and operational mechanisms, and conducted separate studies without correlating these. Based on the existing planning and policies in Beijing, qualitative and quantitative analysis of energy supply and demand under climate change conditions were undertaken in this paper. Then, the results of load simulation and output prediction were used as inputs for the optimization model, which can ensure the rationality of the final scheme. The results obtained using this model will help improve the ability of Beijing’s power system to adapt to climate change and help decision-makers understand the current energy supply and demand situation in Beijing.
3. Methodology
This study used the PRECIS model (Providing Regional Climates for Impacts Studies), statistical regression analysis, and scenario analysis technology to comprehensively analyze Beijing’s electricity supply and demand. Based on the above research results of climate change impact, this study used 2015 as the base year to build a structural optimization model for Beijing’s new and renewable energies in 2020 under climate change conditions. In order to examine the impact of climate change on energy structure adjustment, the impact of changes in meteorological elements on the maximum supply of various energy forms was combined into the power generation limit constraint (6a). In addition, combined with the proportion of future new and renewable energy generation, the impact of temperature change on electricity demand was combined with the power supply and demand balance constraint (6b). The specific form is as follows:
Carbon emission objective function:
Development proportional objective function:
where
refers to the annual development amount of the renewable energies form
i, which is the decision-making variable, (100 million kWh).
is the elasticity coefficient of the income function.
is the elastic coefficient of the carbon emission objective function;
is the coefficient of elasticity of the development proportional objective function;
is the unit income of the development energy form
i (yuan/kWh).
is CO
2 emissions of the development and utilization of unit energy
x, (g/kWh).
Main constraint conditions:
3.1. Requirements and Endowment Constraints
where
xi′ is the development amount of energy
i in the current year (100 million kWh);
Xi is the maximum exploitable amount of energy
i (100 million kWh);
Xe is the annual total national energy demand (100 million kWh);
ti is the total hours that energy
i can be developed in a year (h); ω
t is the power generation time constraint coefficient of the energy
i.
3.2. Technical Constraints
where
is the energy conversion efficiency of each energy in the base year;
is the energy conversion efficiency of each energy in the target year;
is the technical maturity of each energy in the base year;
is the technical maturity of each energy in the target year;
is the constraint coefficient of energy conversion efficiency;
is the technical constraint coefficient.
3.3. Economic Constraints
where
is the power generation cost of each energy in the base year, (yuan/kWh); is the power generation cost of each energy in the target year, (yuan/kWh);
is the installed capacity of each energy in the base year, (MW);
is the installed capacity of each energy in the target year, (MW);
is the constraint coefficient of energy generation cost;
is the constraint coefficient of installed capacity.
3.4. Environmental Constraints
where
is the amount of CO
2 generated during the development and utilization of various energies in the base year (g/kWh);
is the amount of CO
2 generated during the development of various energies in the target year (g/kWh);
is the amount of waste generated during the development and utilization of various energies in the base year (g/kWh);
is the amount of waste generated during the development and utilization of various energies in the target year (g/kWh);
is the impact of various energies on other environment aspects in the base year;
is the impact of various energies on other environment aspects in the target year;
is the constraint coefficient of carbon emissions;
is the constraint coefficient of solid waste emissions;
is the environment constraint coefficient.
3.5. Security Constraints
where
is the reliability index of energy development and utilization in the base year;
is the reliability index of energy development and utilization in the target year;
is the design life of energy generation device in the target year.
is the design life of energy generation device in the base year (year);
is the impact of each energy on other security aspects in the base year;
is the impact of each energy on other security aspects in the target year;
is the constraint coefficient of development controllability index;
is the design life constraint coefficient;
is the safety constraint coefficient.
Finally, based on all of the above constraints, a set of optimization models for Beijing’s new and renewable energy structure adjustment under climate change conditions was constructed.
4. Results and Analysis
4.1. Optimization Analysis of a New and Renewable Energy Structure in Beijing without Consideration of Climate Change Conditions
Three different weight combinations were designed to compare the structural changes of energy development without considering climate change: economy as the priority, environment as the priority and the balanced development of each objective. When the economy was prioritized, the weight coefficients of the objective function were taken as ωf = 0.5, ωg = 0.25, ωh = 0.25, the power generation cost coefficient was 0.75, the economic factor coefficient was 1.25, and the index constraint coefficients of the remaining constraints were taken as 1. When the environment was prioritized, the weight coefficients of the objective function were taken as ωf = 0.25, ωg = 0.5, ωh = 0.25, the carbon emission constraint coefficient and the solid waste emission coefficient were both 0.75, the environmental factor constraint coefficient was taken as 1.2, and the index constraint coefficients of the remaining constraints were taken as 1. In the balanced development of each objective, the weight coefficients of the objective function were taken as ωf = 0.33, ωg = 0.33, ωh = 0.33, the technology factor, economy factor and environment factor were taken as 1.15, and the index constraint coefficients of the remaining constraints were taken as 1. According to Beijing’s new and renewable energy development goals, during the 13th Five-Year Plan period, the generation of new and renewable energies should account for more than 15% of the total power generation. Combined with the forecast total electricity consumption in Beijing in 2020, it was determined that the generation of new and renewable energies should exceed 15 billion KWh when climate change was not considered.
As shown in
Figure 4, when the impact of climate change was not considered, under the condition that economic development was dominant, the development amount of biomass energy remained at the 2015 level. The reason is that the unit revenue of biomass energy is low (0.35 yuan/kWh) and its installed capacity is the minimum [
36], which is not conducive to meeting the requirements of maximizing the economic benefits of the objective function. The development amount of external electricity reached the maximum allowable value. The development amount of other renewable energies also increased. There are some reasons that explain this. Firstly, the unit income of external green power is the highest (0.8 yuan/kWh), which is conducive to the maximization of the objective function. The unit income of other renewable energies is also higher (0.35 yuan/ kWh), which also contributes to the maximum economic benefit. Secondly, external green power and other renewable energies have the highest energy conversion rate. The energy conversion rate of other renewable energies exceeds 70%, which helps to save power generation costs and make it more economical [
37]. At the same time, the optimization results also indicate that two forms of energy are temporarily limited by the amount of energy available, but there is still more room for development, and the primary consideration is to develop such energy. The development of the other two forms of energy, wind and solar energy, also increased significantly compared to 2015, reaching 366.2413 million kWh and 343.7485 million kWh, respectively. This is mainly due to the high technical maturity of wind energy, which can reach second place in the technical maturity of the five energies [
38,
39]. However, the development time of wind energy is shorter, and its power generation cost is higher (0.43 yuan/kWh), so it fails to reach the maximum development amount. Solar energy has a higher unit income (0.45 yuan/KWh), but its energy stability index and energy conversion rate are lower, so it is also not up to the maximum development amount.
If the environment impact was dominant, biomass energy development was at the base year level. This is because the solid waste emission of biomass energy is ranked first among the five energies [
36]. Additionally, the carbon emission (10 g/KWh) and other environment impacts of wind energy are second only to biomass energy, which is not conducive to the realization of the goal of minimizing pollutant emissions [
39]. Therefore, its growth is limited. When the development amount of external electricity reached the maximum value, the development amount of solar energy was also significantly improved. This is mainly because the carbon emission and solid waste emission of external electricity are the lowest, and other environment impacts generated are the smallest, in the same period. The carbon emission and solid waste emission of solar energy are at a low level, and other environment impacts are second only to external electricity. The development amount of other renewable energies has increased compared to 2015. This is due to the fact that the carbon emission (3.9 g/KWh) of other renewable energies is second only to external green power, but their solid waste emissions are only at a medium level, so they did not reach the maximum development amount.
Under the condition of balanced development of various targets, the energy development structure was similar to the condition of giving priority to environment impact. The development amount of external electricity reached the maximum exploitable value, while the development of biomass energy remained at the 2015 level. Solar energy development grew by a large margin. This is because the external green power has the highest unit revenue and the lowest carbon emission and solid waste emission, so it has a large advantage in all energy types. Additionally, the unit income, development safety and other environment impacts of solar energy are second only to external electricity. At the same time, the solid waste emission and carbon emission in the solar energy development process are at a medium level, so its comprehensive score is higher. The unit revenue of biomass energy is ranked second to the bottom and it has the highest solid waste and carbon emissions [
35], so its overall score is the lowest. The development amount of wind energy and other renewable energies was higher than that of 2015, but they did not reach the maximum. The reason is that the solid waste emission of wind energy is second only to that of external electricity and its carbon emission is at the middle level [
39], but its unit income is the lowest. Therefore, the development amount of this energy increased slightly but did not reach the maximum exploitable amount. The technical maturity of other renewable energies is relatively low, and its other environmental impacts may be greater in the process of development [
37]. Therefore, its comprehensive effect is similar to that of wind energy.
Under the conditions of the three different weight combinations, the improved energy structure optimization model was used to predict the Beijing’s optimal power supply in 2020. Through the analysis and comparison of energy optimization results under different conditions, this model has a great contribution to make to understanding the future development of energy supply and demand and improving energy stability in Beijing. At the same time, it also lays the foundation for Beijing’s energy supply and demand with climate change.
4.2. Optimization Analysis of New and Renewable Energy Structure in Beijing with Consideration of Climate Change Conditions
Under the RCP8.5 and RCP4.5 scenarios, this study gave the power generation for five energy forms when the economic benefit was given priority. In the case of climate change, the priority order for the development and use of new and renewable energies in Beijing, in the two different scenarios was: external electricity > other renewable energies > solar energy > wind energy > biomass energy.
As shown in
Figure 5 and
Figure 6, the proportion of external electricity development reached more than 48% of the entire energy system in two scenarios. Furthermore, its development amount reached the maximum developable amount (9.4 billion KWh, 9.8 billion KWh), which was significantly higher than other energies. The main reason is that external electricity is less affected by climate change. It has the lowest development cost, the highest unit revenue, the highest energy conversion rate and technology maturity, and the least solid waste and carbon emissions generated during the development process. In addition, Beijing also has some policy support for the introduction of external electricity, which is the main measure to slow down Beijing’s power supply in the future. Biomass energy is also less affected by climate change, but its unit income is ranked fourth and economic factor is ranked fifth, which is not conducive to maximizing economic benefits. Therefore, its development amount stayed at the 2015 level.
The development amount of wind, solar and other renewable energies increased compared to 2015. The development amount of other renewable energies in the two scenarios can reach 8796.3996 million KWh, 3473.4485 million KWh, respectively. In the RCP8.5 scenario, its proportion was more than 44.43%, which was much higher than that in the RCP4.5 scenario. This is because this energy form has the lowest power generation cost, the highest energy conversion rate, and its installed capacity can reach 2 million KW in 2020. However, due to its low technical maturity [
37], its development amount increased significantly, but it did not reach the maximum exploitable amount. Under the condition of climate change, the solar energy development amount in the two scenarios reached 729.978 million KWh and 656.0185 million KWh, respectively. Although it did not reach the maximum developable amount, it still increased. This is because there is a certain degree of policy support and market demand for the application of solar energy heating and photovoltaic power generation in Beijing [
40]. Its installed capacity in 2020 can reach 1.165 million KW, which is about 10 times that of the base year. The development amount of wind energy in the two scenarios was higher than that in 2015. The reason is that the unit revenue of wind energy is low, and the energy conversion rate is also low. However, its technology maturity is high, and its pollutant emission is small. Therefore, under the influence of developing proportional objective function, its development amount still increased.
Comparing the two optimization results with or without considering climate change, we can see that the development amount and ratios of external electricity, wind energy, solar energy and other renewable energies changed. Among them, although the development amount of external electricity declined, it was always at the maximum exploitable amount (9400 million kWh and 9800 million kWh). This is because its unit revenue, carbon emission, solid waste emission, energy conversion rate and other factors bring the greatest comprehensive advantages. However, due to climate change, the maximum energy supply for external electricity was reduced. When considering climate change, the development amount of other renewable energies in the RCP8.5 scenario was significantly higher than that without considering climate change conditions and RCP4.5 was not much different. The main reason is the rapid increase in the total energy demand. At the same time, external electricity cannot meet the power demand of social production and life, and the development and utilization of other renewable energies is preferred. Therefore, under the constraints, the development of other renewable energies in the RCP8.5 scenario significantly improved. When considering climate impacts, the development amount of wind and solar energy was higher than that without considering climate impacts. Although wind energy and solar energy were greatly affected by meteorological factors such as effective wind speed and radiation, climate change led to an increase in total electricity demand and a decline in total energy development. The development of external electricity and other renewable energies alone was insufficient to meet energy demand, so both wind and solar power generation increased. Although climate change is conducive to the increase of biomass energy reserves, biomass energy is subject to the disadvantages in its own development process, and its development is not supported. Thus, biomass energy maintained its development at the 2015 level. In summary, new and renewable energies will play a large role in Beijing’s future power supply process. This is of great significance for accelerating the development and utilization of new and renewable energies, alleviating the imbalance between power supply and demand, and improving energy security.
All the above predicted results of Beijing’s optimal power supply under climate change conditions were based on the improved energy structure optimization model. Through the comparison of the two sets of results, it is found that the proportion and development of Beijing’s future energy development will change. Therefore, these results provide comprehensive guidance for energy security and the balance of Beijing’s power supply and demand in the future.
5. Conclusions
In this study, regional climate simulation and SPSS multiple linear regression were used to analyze Beijing’s electricity supply and demand situation, and the new and renewable energies structure adjustment optimization model was used to predict the development of five energy types in 2020. However, climate change has intensified the imbalance between power supply and demand. Therefore, a structural adjustment optimization model for new and renewable energies combined with climate change was proposed to predict the Beijing’s optimal electricity supply in the future.
Based on the analysis of Beijing’s electricity supply and demand, the energy structure optimization model and scenario analysis were used to predict the power generation of five energy types in Beijing. Firstly, when the climate change conditions were not considered, the economy, environment, and comprehensive benefit were considered, and the changes in energy development structure under different weight conditions were compared. Secondly, when considering the climate change conditions, this paper predicted the optimal power supply of Beijing’s new and renewable energies in two scenarios, RCP8.5 and RCP4.5, in 2020. The comprehensive results show that whether or not climate change is considered external electricity provides the maximum power supply. Therefore, it is the main development energy in Beijing. Considering the influence of many factors, other renewable energies are the second development energy. At the same time, in order to make up for the shortage of power supply and alleviate the imbalance between power supply and demand, energies such as solar energy, wind energy and biomass energy should be properly developed. Comparing the two optimization results with or without considering climate change, the development amount and development ratio of various energy forms underwent certain changes. In the case of climate change, the priority development order of Beijing’s new and renewable energies is: external electricity > other renewable energies > solar energy > wind energy > biomass energy.
However, the model still needs to be strengthened in some places in order to further enhance its practicality and reliability. First, this study didn’t consider seasonal fluctuations in the relationship between electricity demand and temperature. Only a simple linear regression model was used to fit the relationship between variables. In the future, other patterns such as nonlinear regression, neural networks etc. can be considered to better reflect the relationship between variables. In addition, although climate change can reflect the inherent randomness and volatility of new and renewable energies to a certain extent, it is more a trend forecast. In fact, based on the impact analysis of climate change, the construction of a stochastic variable optimization model can achieve better results. In order to increase the practicability and feasibility of the model, it is worth further study to better identify the impact of climate change on electricity demand and accurately reflect the uncertainty of new and renewable energy outputs. In general, this research can be used as the design basis for the future Beijing energy structure adjustment program, providing scientific support for the government’s decision-making and the development of related industries.