Policy In Region Research Articles

Place-based regional planning: shaping governance, planning policy and practices in a South African region, 1994–2022

ABSTRACT The governance of regions is activated through actors and institutions representing diverse interests. Using place-based planning, this paper reviews local planning in South Africa drawing upon a case study of the iLembe District. We argue that region building is constructed through economic and political forces, currently blocked by poor relationships between the state, civil society, business, and inter-governmental complexities. The study uses empirical evidence on the regional conditions of the iLembe District and associated municipalities, reviews of planning documents and legislation, and interviews with key stakeholders. The authors argue that the local planning framework is ineffectual, lacking strategic direction, and primarily servicing provincial and nationally derived compliance requirements, rather than meeting strategic developmental objectives. Most recently, the global pandemic emphasized interlinked vulnerabilities and weak linkages associated with globalisation and sustainable development, particularly with global supply and value chains, health systems, settlement patterns, energy production and food security. We argue for a new form of collaborative regional planning and governance framework which could be laid through a “learning region” approach as identified in the place-based literature. An example is unlocking green energy production as a value addition to the established but crisis-laden sugar industry in the case study.

Research on Multi-Scenario Simulation of Urban Expansion for Beijing–Tianjin–Hebei Region Considering Multilevel Urban Flows

With the development of urban agglomerations in China, the study of the interactions between cities has become a popular and difficult issue. Exploring the interactions between cities can help decision-makers optimize regional resource allocation and improve regional spatial patterns. Combining the urban flow model and the patch-generating land use simulation (PLUS) model, this study simulates and analyzes the process of urban expansion in the Beijing–Tianjin–Hebei (BTH) region, and investigates the impact of urban hierarchical structure differences on urban expansion. In this study, the role and influence of inter-city economy flow, transportation flow, population flow, and information flow on the development of urban agglomerations are comprehensively considered, and a multilevel urban interaction model is constructed based on a hierarchical generalized linear model (HGLM). Based on the national BTH cooperation and development strategy, a multi-scenario simulation study of urban expansion is carried out using the HGLM-PLUS model. The results indicate the following: (1) compared to the traditional PLUS model, the coupled HGLM-PLUS model, which considers multilevel urban flows, improved the overall accuracy by 0.047, the Kappa coefficient by 0.207, and the figure of merit (FoM) index by 0.051; (2) under different simulation scenarios, the development trend under the cooperation and development policy in the BTH region is more stable, demonstrating a relatively smooth urbanization expansion trend; and (3) under the BTH cooperation and development background, the total area of construction land in the BTH region is expected to be maintained at around 1,164,500 km2 by 2040. The spatial expansion pattern will present a networked expansion with the core driving development, axes and belts connecting, and clusters breaking through.

Energy transition policy and rural revitalization of Chinese ethnic regions

This study addresses socio-economic disparities and environmental challenges in China's ethnic regions by examining the impact of energy transition policies on rural revitalization, with a particular focus on the mediating effects of population quality, economic growth, and industrial upgrading. Using data from 46 Chinese ethnic regions spanning 2003 to 2022, the analysis reveals that industrial upgrading significantly enhances the effectiveness of these policies, while educational attainment, as a measure of population quality, further amplifies their benefits. Although economic growth also contributes positively to rural revitalization, its mediating role is less pronounced. These findings highlight the need for a comprehensive strategy that integrates energy transition with socio-economic development to promote sustainable rural progress. The study underscores the critical role of incorporating energy transition into broader development policies, particularly through industrial and educational improvements, to achieve sustainable development in China's ethnic regions, and offers valuable policy recommendations.

The pupil outdoes the master: Imperfect demonstration-assisted trust region jamming policy optimization against frequency-hopping spread spectrum

Jamming decision-making is a pivotal component of modern electromagnetic warfare, wherein recent years have witnessed the extensive application of deep reinforcement learning techniques to enhance the autonomy and intelligence of wireless communication jamming decisions. However, existing researches heavily rely on manually designed customized jamming reward functions, leading to significant consumption of human and computational resources. To this end, under the premise of obviating designing task-customized reward functions, we propose a jamming policy optimization method that learns from imperfect demonstrations to effectively address the complex and high-dimensional jamming resource allocation problem against frequency hopping spread spectrum (FHSS) communication systems. To achieve this, a policy network is meticulously architected to consecutively ascertain jamming schemes for each jamming node, facilitating the construction of the dynamic transition within the Markov decision process. Subsequently, anchored in the dual-trust region concept, we design policy improvement and policy adversarial imitation phases. During the policy improvement phase, the trust region policy optimization method is utilized to refine the policy, while the policy adversarial imitation phase employs adversarial training to guide policy exploration using information embedded in demonstrations. Extensive simulation results indicate that our proposed method can approximate the optimal jamming performance trained under customized reward functions, even with rough binary reward settings, and also significantly surpass demonstration performance.

Cluster analysis of travel behaviour threats in chosen European functional urban areas during the economic crisis

Motives: Urban mobility models are constantly changing due to economic, social, infrastructural, and geographical factors. Preferences for transport modes vary by country, region, and city, and transport infrastructure and policy have a significant impact on residents’ choices. Additionally, economic factors such as economic crises, public policy decisions, and events such as armed conflicts have a significant impact on the dynamics of mobility in functional urban areas (FUAs).Aim: The main goal of the research was to create groups of countries (clusters) that have similar priorities regarding travel behaviour threats revealed as a result of the economic crisis resulting from the conflict in Ukraine.Results: The study shows that the main threats during the economic crisis (resulting from the war in Ukraine) are economic factors (e.g., ticket prices, an increase in fuel costs), legal factors (e.g., loss of a driving license or passenger transport license), and infrastructural factors (e.g., poor condition of infrastructure). The analysed countries were grouped based on the hierarchical prioritization of threats, using Ward’s hierarchical clustering method. Interestingly, the distance from the conflict epicentre did not significantly influence the prioritization of threat factors influencing transportation behaviour in FUAs. Instead, factors such as membership in international organizations, energy dependence on Russia, the level of economic growth, and transport infrastructure played a more key role in the priority-setting process.

Industrial agglomeration, environmental regulation, and high‐quality development in rural China: From the perspective of spatial effect

AbstractExplore the interaction and spatial spillover effects between industrial agglomeration, environmental regulation, and high‐quality development of agriculture and rural areas, formulate appropriate industrial and environmental policies for different regions, guide the orderly agglomeration of agricultural sectors, and adjust the intensity of environmental regulation, which will help achieve high‐quality development. This manuscript firstly deconstructs the internal logic among industrial agglomeration, environmental regulation, and high‐quality development. Secondly, the Super‐SBM model is used to calculate the high‐quality development efficiency in rural China from 2000 to 2020. Finally, the Spatial Dubin Model (SDM) is used to analyze the spatial spillover effects and regional differences of industrial agglomeration, environmental regulation, and their integration impact on high‐quality development in rural China. The results show that: ① From 2000 to 2020, the high‐quality development efficiency shows a downward trend in fluctuation, and high‐quality development needs to be improved. ② There are significant regional differences in the effects of industrial agglomeration and environmental regulation on the high‐quality development efficiency. Industrial specialization agglomeration can effectively improve the high‐quality development efficiency, while industrial diversification agglomeration has uncertain effects. ③ The integration of environmental regulation and diversification agglomeration inhibits the high‐quality development efficiency, while the integration with specialization agglomeration has a stronger effect on improving high‐quality development efficiency. It is necessary to further enhance the effect of diversification agglomeration.

Regional energy consumption policy practice to promote low-carbon economy

IntroductionEnergy is the fundamental driving force for world economic and social development. However, the growth of carbon dioxide emissions and increasing environmental challenges are becoming increasingly problematic, limiting the pace of economic development.MethodsTo optimize the energy consumption structure and promote the development of low-carbon economy, this study took Shaanxi Province as an example to analyze the impact of low-carbon economy policy variables on the energy consumption structure dominated by coal. The purpose of this study is to examine the influence of policy variables on the evolution of energy consumption structure by constructing a system dynamics model. In addition, this study will explore policy optimization issues.ResultsThe error of simulation results was within ±10%. The consumption of non-fossil energy increased from 2,196,400 tons of standard coal in 2009 to 22.578 million tons in 2030, which is in line with the development trend. Under these four policy combinations, the share of coal will fall to 57.8 percent by 2030. In addition, the share of non-fossil energy sources will increase to 21 percent and the share of natural gas will reach 16 percent.DiscussionThe policy suggestions put forward in this paper are of great significance to the optimization of energy structure led by coal. The model constructed can be effectively applied to practical policy simulation and adjustment, and can provide reference for the development of low-carbon economic policies in other regions.

The Republic of Korea’s Foreign Policy in the Arctic Region: Prospects for the Northern Sea Route

The Republic of Korea’s Foreign Policy in the Arctic Region: Prospects for the Northern Sea Route

Դոհայի համաձայնագիրը ԱՄՆ–Աֆղանստան հարաբերություններում նոր շրջափուլի թևակոխման սկիզբ / The Doha Agreement as the Beginning of a New Period in US-Afghanistan Relations

On February 29, 2020, the United States and the Taliban signed an agreement to establish peace in Afghanistan, which became widely known as the Doha Agreement. This agreement marked the end of one of the largest and bloodiest conflicts of the 21st century, the Afghan Civil War. The Doha Agreement is crucial to consider within the context of Afghan transitions, as well as the signing and content of the agreement itself, which became a turning point for the future of Afghanistan and its people, signaling the end of the long-standing presence of American and coalition forces in Afghanistan. The Doha Agreement is based on four key points: the withdrawal of American and coalition forces, the Taliban's commitment to conduct counter-terrorism operations, the initiation of intra-Afghan negotiations, and the establishment of a comprehensive and long-lasting peace. The Doha Agreement became a turning point in U.S. foreign policy, though it did not lead to long-term peace in Afghanistan. Nevertheless, it marked the beginning of a reevaluation of U.S. foreign policy in the Indo-Pacific region. On the other hand, the agreement is also significant because the U.S. engaged in peace negotiations and signed an agreement with the Sunni extremist group known as the Taliban, which, to this day, it does not recognize as the official ruling force in Afghanistan.

The impact of cryosphere service change on the social-ecological systems resilience: Evidence from the Qilian Mountains Area in China

Research on changes in cryosphere services is crucial for the responsible management of cryospheric resources and for fostering sustainable development in Social-Ecological Systems (SESs) impacted by the cryosphere. While previous research has primarily focused on quantifying cryospheric change through Cryosphere Service Value (CSV), the impact of cryosphere service change on Social-Ecological Systems Resilience (SESR) remains unclear. This study considers the Qilian Mountains as a cryosphere system and assesses the changes in its service value from 2000 to 2020. It also establishes a framework to analyze the spatial-temporal variations in resilience within the Qilian Mountains Area in China (QMAC) and investigates the impact of changes in cryosphere services on SESR. The findings indicate that (1) the CSV exhibited a decreasing trend followed by an increase from 2000 to 2020, with minor increases observed in the three northern inland river basins and substantial increases in other areas; (2) the resilience in QMAC improved consistently, establishing a spatial pattern characterized by higher resilience in the west and lower resilience in the east, as well as higher resilience in the north and lower resilience in the south; (3) the effects of changes in cryosphere services on SESR demonstrate significant spatial-temporal patterns, the decline in climate regulation service has a notably negative impact on ecological resilience, while the increase in value from aesthetic appreciation and tourism service positively boosts economic resilience; and (4) changes in cryosphere services affect social resilience by influencing residents’ livelihoods, with more pronounced effects on SESs in areas with high land use intensity. This research provides a research avenue for examining how cryosphere service change impacts SESR and offers practical experience for promoting the stability of SESs and developing sustainable development policies in regions affected by the global high-mountain cryosphere amid climate change.

МАҢҒЫСТАУ ОБЛЫСЫНДА ХАЛЫҚТЫ ЖҰМЫСПЕН ҚАМТУ САЯСАТЫН БАСҚАРУДЫ ЖЕТІЛДІРУ НӘТИЖЕЛЕРІНЕ ТҰРАҚТЫ МОНИТОРИНГ ЖӘНЕ ТАЛДАУ

This article is a study for continuous monitoring and analysis of the results of activities to improve the management of employment policy in the Mangystau region. The study examines the main aspects of employment policy management, as well as methods for monitoring and analyzing the results of this activity. The purpose of the work is to identify effective strategies and tools to improve the management of employment policy in the region. The results obtained can be used to develop recommendations on optimizing existing management mechanisms and improving the effectiveness of employment policy in the Mangystau region. One of the relevant topics for the Mangystau region that hinder economic development is the labor market, in particular, issues of ensuring employment and reducing unemployment. This employment of the population affects incomes and expenses, and the social stability of the Mangystau region. With high employment in the commodity markets of this area, relatively high consumer demand is ensured, which, in turn, leads to an increase in GDP and GRP, and unemployment leads to incomplete income generation. The change in these indicators is influenced by processes taking place not only in the country, but also in the world. In the Mangystau region, over the past three years, some progress has been made in labor market indicators: only in the period 2020-2022, the number of people employed in the economy increased by 112.3%, the unemployment rate decreased by 1.9%. In order to increase employment and reduce unemployment in all regions of the country, including the Mangystau region, the country has implemented a state "labor program" for 2021-2023. The contribution of this state program to the Mangystau region was great. This is due to the fact that on the basis of the program, not only jobs were created, but also short-term training events were held in order for the population to carry out their business and provide themselves with work.

Evaluation of the impact of security perception on the structural changes of MSEs through system dynamics

Micro and Small businesses (MSEs) face several challenges to survive in the market, some of these challenges are related to security matters which are the subject of this article. In Mexico MSEs are victims of crimes such as extortion, theft, and assaults, among others; this situation leads them to spend their economic resources to make structural changes to be able to continue with their commercial activities. This article is based on a survey conducted on 370 MSEs in the central region of the state of Veracruz in Mexico; the present study aims to evaluate the impact of structural changes made by businesspeople in their perception of business security. In this way, the decision-making process of MSEs facing insecurity is statistically analyzed through a simulation model considering the system dynamics methodology. To evaluate this phenomenon, we have identified four main subsystems: 1) Crime, 2) Security Perception, 3) Structural Changes, and 4) Government Policy Changes; at the same time three hypothetical scenarios were simulated: 1) Reduction in crimes committed against MSEs, 2) Government changes in public infrastructure, and 3) the combination of the previous two. The approach allows us to identify that companies make structural changes based on the events around them, rather than on the crimes that they suffer, making abrupt or precipitated decisions. Therefore, we have identified that it is not only necessary to eliminate crimes, but also to work with government strategies that allow MSEs owners and staff to improve their perception of security. This simulation model can be replicated to evaluate the implementation of security policies in other regions with high insecurity rates.

Storm clouds over innovation: Typhoon shocks and corporate R&D activities

This study investigates the economic impact of typhoon disasters on corporate innovation activities, a critical driver of economic growth and resilience. Utilizing a comprehensive dataset of Chinese public companies from 2010 to 2022 and employing a wind field model to construct a city-level typhoon destruction index, we apply difference-in-differences and instrumental variable methods to analyze the effects on corporate innovation. Our findings reveal that typhoon disasters significantly reduce both patent filings and R&D investment intensity, particularly in coastal areas and technology-intensive industries. The adverse effects are transmitted through financial constraints, human capital loss, and infrastructure damage. This research contributes to understanding the microeconomic implications of extreme weather events on innovation-driven economic growth, offering insights for disaster resilience policies in vulnerable regions.

Knowledge source switching under state interventions of latecomer regions: A case study of Shenzhen

This paper aims to unpack the process and analyze the mechanisms of knowledge source switching in latecomer regions that have evolved from peripheral to core positions. Drawing on four decades of matched patent-company data from Shenzhen, we classify patents into various knowledge classifications and calculate their percentage changes to observe the dynamics of knowledge source switching. Furthermore, we employ Difference-in-Differences (DiD) estimation to examine the causal effects of state interventions on this dynamic. The findings indicate that Shenzhen's knowledge sources have switched from multinational corporations (MNCs) and foreign subsidiaries to global inventors. Notably, state interventions exhibit a significant positive causal effect on this dynamic, particularly following the implementation of independent innovation policies. These findings contribute to the cross-fertilization of regional innovation studies and the Global Production Networks (GPN) approach, highlight the critical role of the state in ensuring the right and dynamic mode of global knowledge sourcing and offer implications for local innovation policies in latecomer regions.

The Impact of Smart City Policies on City Resilience: An Evaluation of 282 Chinese Cities

This study uses four dimensions, namely social resilience, economic resilience, infrastructure resilience, and ecological resilience, to construct an index system for urban resilience. The subject data came from the panel data of 282 prefecture-level cities in China from 2006 to 2020. We selected a multiperiod double-difference model to study the effects of smart city pilot policies on macro-urban resilience. By conducting parallel-trend tests and selecting appropriate robustness tests, this study drew the following relevant conclusion: smart city pilot policies can have a positive effect on the urban resilience level. These policies exert their influence by facilitating industrial structure upgrading, which plays a partial mediating role. Considering different city area distributions and city scales, smart city pilot policies can have significant heterogeneity in their enhancement of urban resilience. The effect is pronounced in the “east > central > west” states and is more likely to have a significant impact on small- and medium-sized cities. Therefore, promoting the scope of smart city pilots, strengthening the intermediary role of industrial structure upgrading, and implementing differentiated policies for different regions and city sizes are important for sustainable urban development.

Assessment of the effectiveness of management at the regional level based on the analysis of the activities of authorities

Relevance. The problem of effective management of regional development is becoming more and more urgent due to the emergence of new conditions (obstacles) of functioning, which pose the task of creating programs for the most effective management of subjects to the regions of Russia and executive authorities. It is important to note the choice of the subject: the Kursk region is an important region of the Central Federal District due to its potential and geographical location.The subject has a specialization in important sectors of the entire Russian economy, but at the same time may face inefficient management, which will cause a decline in the regional economy. The purpose is to assess the effectiveness of management of an economic entity on the example of the Kursk region by analyzing the activities of executive authorities.Objectives: to establish the parameters of effective management; to study regional policy as a means of increasing the effectiveness of regional development; to study methods for assessing the effectiveness of regional development through the prism of actions of public authorities; to compare the economic structures of the Kursk region and neighboring regions of the region using specific methodologies; to identify the main problems in the development of the Kursk region.Methodology. To carry out the research, methods of system analysis and synthesis, statistical data processing, as well as comparative and expert analysis are used. The results of the study include an analysis of the effectiveness of regional policy in the Kursk region and the identification of the main problems in the activities of government agencies that affect the economic growth of the subject.Conclusions. The Kursk Region is an ambiguous region regarding the quality of regional economic management. Studying the state support of subjects, their management by authorities, we can say that in the field of ecology and industrial development, the state supports the region sufficiently, since these areas are specialized in the region, which cannot be said about other areas. Despite the weak development of other industries, the state needs to provide significant support to such specialized sectors as agriculture and industry.

Characteristics of Spatiotemporal Changes in China's Carbon Budget at Different Administrative Scales

Currently, scientifically and reasonably specifying carbon emission reduction measures in the context of "double carbon" has become a common concern worldwide. China's administrative divisions have a notable impact on the formulation and implementation of relevant policies. Therefore the carbon emissions must be calculated accurately under China's administrative divisions at different scales. The spatiotemporal change characteristics of absorption and carbon emissions can provide scientific basis for the formulation of reasonable and differentiated carbon emission reduction policies in different administrative regions in China. To this end, this study used multi-source data such as remote sensing and statistics and integrated ecological models, statistics, and GIS space analysis and other methods to analyze the spatiotemporal dynamic change characteristics of carbon emissions and carbon absorption at different administrative scales （provinces, cities, and counties） in China. The results showed that： ① The total carbon absorption of vegetation in China continued to increase from 2000 to 2021 and the average value gradually increased. Differences were observed in spatiotemporal changes in carbon emissions at different administrative scales. The spatiotemporal changes at smaller scales were more evident. Carbon emissions showed obvious spatial differences of "high in the north and low in the south, high in the east and low in the west." ② The spatiotemporal distribution of CPI at the administrative scale was similar to that of carbon emissions and the overall trend was increasing annually. The pressure of carbon emissions on carbon absorption gradually weakened from the east to the central and western regions. ③ Spatiotemporal hotspot analysis showed that the overall spatial distribution of cold and hot spots in China's carbon absorption was as follows： In the spatial pattern of "hot in the east and cold in the west," the spatial distribution of cold and hot spots of carbon emissions showed agglomeration characteristics. The provincial scale was primarily oscillating hotspot whereas municipal and county scales were majorly continuous hot spots. Further results revealed that： ① Carbon absorption in different regions and periods in China showed significant variability, especially in the central and eastern regions. The possibility of offsetting carbon emissions by increasing carbon absorption remains. ② At the same scale, administrative regions （such as different provinces） and lower-level administrative regions at another scale （such as different cities in the same province） showed varying degrees of variability in carbon absorption and carbon emissions. Therefore, taking provincial administrative regions as an example for subsequent formulation considering carbon trading, emission reduction, and other policies, we should first consider the coordination of emissions between different cities in the province and then consider the coordination between provinces, which is expected to better promote the implementation of relevant policies.

A revised model for calculating virtual scarce water

Accounting for virtual scarce water facilitates and improves the analysis of virtual water, and facilitates comparisons between water use embodied in products from regions with different water resource conditions. However, previous virtual scarce water models were inadequate for the analysis of both water quantity and quality, and only provided a rough estimate. To address this problem, we proposed a modification of this model. In the revised model, we determined the scarcity induced by inadequate water quality by analyzing the availability of suitable quality water for specific sectors (residential, industrial, agricultural, and environmental) rather than focusing on a single sector (usually environmental). Additionally, the revised model evaluated scarcity from water quantity by considering clean water technologies and environmental flow demand. This comprehensive scarcity measure is then incorporated into an input–output model to determine virtual scarce water. We used two typical Chinese river basins (the Hai River and Pearl River basins) with different water endowments to evaluate the model. We found that in the water-scarcity region the virtual scarce water was more strongly affected by water quality and clean water technologies, whereas in the water-rich region it was more strongly affected by the environmental flow demand. These findings underscored the need for more targeted economic and environmental policies for different regions. Water-scarcity regions should prioritize the promotion of clean water technologies and contaminant mitigation techniques, while water-rich regions should pay more attention to ensuring the environmental flow demand.

Nexus between green credit efficiency and strategic, business and management digital transformation–based on 114 commercial banks in China

With the expansion of green finance and the digital economy, the discussion on the evolution of green credit business and the digitalization of commercial banks have grown in prominence. However, limited research has been done on how different degrees of digital transformation in commercial banks—the main issuers—affect the way of green credit efficiency. To fill this gap, based on data from 114 Chinese commercial banks between 2010 and 2021, this paper explores the impact of digitalization on the green credit efficiency through the integration of several methodologies. The paper indicates that enhancing the digitalization, business digitization, and management digitization of commercial banks can greatly enhance the effectiveness of green credit businesses, but the impact of strategic digitization is not significant. Further analysis reveals that digitization facilitates the expansion of overall bank assets, thereby bolstering the green credit business. It also investigates the characteristics of commercial banks and the geographical distribution of their headquarters, indicating a diminished promotional impact for urban and rural banks, as well as banks in the central areas. Finally, this study contends that commercial banks ought to leverage digital resources extensively to facilitate digital transformation and bolster the advancement of green credit operations. It is also recommended that the government should implement preferential policies for regions and banks exhibiting slower developmental progress.

Innovative energy solutions: Evaluating reinforcement learning algorithms for battery storage optimization in residential settings

The implementation of BESS (battery energy storage systems) and the efficient optimization of their scheduling are crucial research challenges in effectively managing the intermittency and volatility of solar-PV (photovoltaic) systems. Nevertheless, an examination of the existing body of knowledge uncovers notable deficiencies in the ideal arrangement of energy systems' timetables. Most models primarily concentrate on a single aim, whereas only a few tackle the intricacies of multi-objective scenarios. This study examines homes connected to the power grid equipped with a BESS and a solar PV system. It leverages four distinct reinforcement learning (RL) algorithms, selected for their unique training methodologies, to develop effective scheduling models. The findings demonstrate that the RL model using Trust Region Policy Optimization (TRPO) effectively manages the BESS and PV system despite real-world uncertainties. This case study confirms the suitability and effectiveness of this approach. The TRPO-based RL framework surpasses previous models in decision-making by choosing the most optimal BESS scheduling strategies. The TRPO model exhibited the highest mean self-sufficiency rates compared to the A3C (Asynchronous Advantage Actor-Critic), DDPG (Deep Deterministic Policy Gradient), and TAC (Twin Actor Cretic) models, surpassing them by ∼ 3 %, 0.72 %, and 3.5 %, correspondingly. This results in enhanced autonomy and economic benefits by adapting to dynamic real-world conditions. Consequently, our approach was strategically designed to deliver an optimized outcome. This framework is primarily intended for seamless integration into an automated energy plant environment, facilitating regular electricity trading among multiple buildings. Backed by initiatives like the Renewable Energy Certificate weight, this technology is expected to play a crucial role in maintaining a balance between power generation and consumption. The MILP (Mixed Integer Linear Programming) architecture achieved a self-sufficiency rate of 29.12 %, surpassing the rates of A3C, TRPO, DDPG, and TAC by 2.48 %, 0.64 %, 2 %, and 3.04 %, correspondingly.