Demand Imbalance Research Articles

Assessing the Accessibility and Equity of Urban Green Spaces from Supply and Demand Perspectives: A Case Study of a Mountainous City in China

Urban green space accessibility is an essential consideration in determining environmental liveability and the well-being of individuals, and the spatial inequity of urban green space supply and demand has become a research focus. However, few studies have conducted a multidimensional and comprehensive assessment of the influences on accessibility from the different perspectives of supply and demand. To address this, our study centred on the mountainous Chongqing region and established a comprehensive research framework examining the spatial pattern of accessibility of urban green spaces and its correlation with physical geographical elements and socioeconomic factors. We reveal the spatial distribution characteristics of urban green space accessibility by using Gaussian-based two-step floating catchment area and network analysis methods and further observe the spatial clustering features utilising hotspot analysis. The ordinary least squares (OLS) model and the spatial lag model were used to evaluate the physical geographical and socioeconomic disparities. Our findings reveal explicit blind spots in urban green space accessibility, primarily within the 30 min travel threshold in the city’s marginal area. A discernible supply–demand imbalance existed in the urban core, constituted by implicit blind spots. Furthermore, we identified that the relationship between urban green space accessibility and elevation under different methods is not always consistently significant over space because spatial heterogeneity may exist. Most concerningly, the study found inequities in urban green space accessibility, particularly impacting vulnerable demographics such as the elderly and lower-income groups. These results can inform urban planners and policymakers about the blind spots of urban green space accessibility and sufficiently consider the physical and socioeconomic heterogeneity of the space to determine where and how to implement inclusive urban greening policies or planning schemes. It is also of great significance in increasing awareness of vulnerable groups and preventing environmental inequality.

Impact of cost approximation on the efficiency of collaborative regulation resolution mechanisms

Air Traffic Flow Management (ATFM) measures are often used to alleviate capacity demand imbalances. Usually, these measures impose a departure delay on flights crossing the airspace in question, where delay is assigned on a “First Planned First Served” (FPFS) base, which minimises total delay. Since delays typically have a different impact on individual flights in terms of cost, a procedure based on cost minimisation could reduce delay-related costs. User-Driven Prioritisation Process (UDPP) is developing a set of solutions aimed at allowing airlines to rearrange their flights within their own slots assigned by the FPFS rule. Inter-airline cost reducing approaches are still missing, but several works have been launched in this direction, using either central optimisations or market-based mechanisms.We analyse the impact of cost approximations procedures, integral part of certain inter-airline mechanisms, overall likely to be used by airlines or the Network Manager (that manages ATFM measures). Using cost models and simulations to collect the true cost of delay profiles, we show that the impact of cost approximations have been severely underestimated, leaving little room for new mechanisms to improve over UDPP. Moreover, we show that the errors made by the airlines on their own costs, expected at least for some airlines, further deteriorate the situation, including UDPP. However, we find that approximation procedures create a strong resilience to these errors, showing how both UDPP and inter-airline procedures may benefit from not having the airlines communicate their detailed costs. Thus, we find that any design of new mechanisms could include a cost approximation procedure in order to increase its resilience.

How America Responds to the Inflation Caused by Covid-19

The Covid-19 pandemic has brought global inflation. Billions of people have been confined to their homes for months, unable to go to work. As an example, in the United States, which has the largest number of Covid-19 confirmed cases, the impact of the epidemic on their economy cannot is a big problem. According to the research, many of them contain the development of inflation by the Covid-19, but few papers research talk about the response of inflation for Covid-19 in U.S. central bank and the company overall. This research could serve as a model for other countries facing inflation. Therefore, this paper will use the background of the United States to explore the causes of inflation, the central bank's strategy, and how inflation reflects the difficulties faced by American companies. This paper mainly uses literature, case, and data analysis methods. Based on this paper, it was found that the fundamental factors of inflation were the imbalance of supply and demand and the break of the supply chain. But because of the Federal Reserves initial miscalculation about the duration of the Covid-19, they switched monetary policy from loose to tight in order to curb inflation. And American companies Apple and Amazon are both facing rising costs, labor shortages, and supply chain disruptions, but their solutions are different because of changing consumer preferences.

Ride-sourcing market equilibrium analysis and optimization under immediate matching strategies

Supply/demand characteristics and price strategies in the ride-sourcing market are affected by matching strategies. In particular, immediate matching strategies are widely adopted to tackle supply–demand imbalance issues. This paper studies a two-sided ride-sourcing market under two immediate matching strategies: driver-first-come-first-serve and passenger-first-come-first-serve. In the former, the system is considered over-saturated with passengers, such that any driver is matched immediately upon posting their availability. Therefore, the market would be devoid of waiting drivers. In comparison, the latter strategy is oversaturated with drivers, such that any newly arriving passenger is immediately matched, and there are no waiting passengers in the system. We first derive generalized supply and demand functions and prove that the immediate matching strategies are optimal to maximize the number of completed trips under certain conditions based on equilibrium analysis. Then, we characterize the market equilibrium and discuss the properties of the wild-goose-chase phenomenon under two immediate matching strategies. We optimize the ride-sourcing platform's strategies to achieve a joint profit of platform and driver maximization (monopoly optimum), social welfare maximization (social optimum), and second-best optimum (entailing a reservation profit for the platform). Numerical experiments are conducted to demonstrate the effects of user heterogeneity, and the properties of pricing strategies under both matching strategies on the monopolistic and social optimal solution. The gained managerial insights provide suggestions for decision-makers to coordinate supply and demand in the ride-sourcing market.

Joint Optimal Dispatch of Complex Urban Raw Water Supply: A Case Study of Lanxi City, Zhejiang Province, China

Water resources play a vital role in supporting urban economic and social development and ecological and environmental protection. Water shortage is a key factor that restricts the high-quality development of cities, while the coordinated and optimized allocation of urban raw water is an important measure to alleviate the water supply–demand imbalance. The current research on urban water supply issues and their underlying causes still needs to be further strengthened. Similarly, the formulation of rules for multi-source and cross-district water supply should pay more attention. This paper proposes a general analytical process consisting of four main stages: problem identification, system generalization, rule formulation, and model construction and solution for the joint optimal scheduling of raw water in a complex urban water supply system. This study investigates the significant water resource wastage and structural water shortage in the reservoirs of Lanxi City. The optimal scheduling plan is proposed by formulating rational rules for inter-district water supply and establishing a multi-source and multi-objective joint optimization scheduling model. Compared to the current independent scheduling scheme and multi-water source joint dispatching scheme based on the current dispatch diagram, the optimal scheduling plan effectively reduced the cumulative water shortage by 68.04 million m3 and 29.72 million m3, respectively, and increased the urban water supply guarantee rate in all districts of the city to over 90%. This study offers valuable insights to urban water resource managers, empowering them to develop optimal multiple water source supply rules that align to the specific characteristics of other case studies.

Analyzing the Supply Potential and Demand for Wood Products in Ethiopia: A Review

Ethiopia's growing population, urbanization, and booming construction industries are all factors in the country's rising demand for wood products. The country's current plantations are inadequate to meet the demand for wood products. The country only exports a small amount of wood, accounting for about 1.45% of all imports, while importing over 3 million m3 round wood equivalent (RWE), amounting to about USD 182.53 million. This showed that there is a large gap between import and export bills, which indicates a negative trade balance. The goal of this study is to examine supply patterns as well as existing and prospective demand for wood products, particularly industrial wood and wood fuel. First, a collection of all relevant documents indicating supply and demand was done. Then, two groups were created out of official records and study papers. Literature that is pertinent and related to the topic was chosen from among the groups. Different publications between 2010 and 2022 a total of 37 were utilized for this review. It was found that Ethiopia consumes more than 130 million m3/year of round wood equivalent, of which about 92.3% is used as wood fuel and the remaining is used to produce industrial goods with added value. Nowadays, imports provide a significant amount of Ethiopia's wood demand, and in 2015 alone, more than 30% of industrial needs were satisfied by imports. The review helps in determining the resource potential, supply-demand imbalance, and current level of demand for wood products.

Environmental governance of transnational regions based on ecological security: The China-Mongolia-Russia Economic Corridor

Ecological security patterns (ESPs) can alleviate the conflict between economic development and ecological protection to ensure regional ecological security. The present study considered the use of the China-Mongolia-Russia Economic Corridor (CMREC) for building an interregional ESP by integrating ecological vulnerability with the supply and demand of ecosystem services using the circuit theory. The results revealed that the supply and demand of ecosystem services in the CMREC were not consistently spatially distributed. High supply areas decreased from east to west and north to south, whereas high demand mainly occurred in highly urbanized areas. The supply and demand imbalance of ecosystem services affected the determination of ecological sources. Fifty-five ecological sources (529,635.56 km2), mainly distributed east of the Northeast Plain, Far East, and around Lake Baikal, were identified. There were no ecological sources in the southwest. Ecological vulnerability decreased from south to north. Mongolia (0.60) had the highest average ecological resistance, followed by China (0.42) and Russia (0.38). According to the circuit theory, 87 ecological corridors (13,306.42 km) and 13 main ecological corridors (3302.50 km) can effectively connect the ecological resources of the CMREC. These sources and corridors are dominated by forests and grasslands. The results also suggest that the connectivity of ecological corridors among the three countries should be improved, ecological restoration in the southern part of the Mongolian Plateau should be emphasized, and the functional stability of the ecological shield areas should be ensured. We propose some management guidelines for optimizing regional ESPs and collaborative environmental governance of the CMREC.

Supply–Demand Imbalance in School Land: An Eigenvector Spatial Filtering Approach

The spatial flows of school-age children and educational resources have been driven by such factors as regional differences in population migration and the uneven development of the education quality and living standards of residents in urban and rural areas. This phenomenon further leads to a supply–demand imbalance between the area of school land and the number of school-age children in the geographical location of China. The georeferenced data characterizing supply–demand imbalance presents an obvious spatial autocorrelation. Therefore, a spatial data analysis technique named the Eigenvector Spatial Filtering (ESF) approach was employed to identify the driving factors of the supply–demand imbalance of school land. The eigenvectors generated by the geographical coordinates of all primary schools were selected and added into the ESF model to filter the spatial autocorrelation of the datasets to identify the driving factors of the supply–demand imbalance. To verify the performance of the technique, it was applied to a county in the southwest of Shandong Province, China. The results from this study showed that all the georeferenced indicators representing population migration and education quality were statistically significant, but no indicator of the living standards of residents showed statistical significance. The eigenvector spatial filtering approach can effectively filter out the positive spatial autocorrelation of the datasets. The findings of this research suggest that a sustainable school-land-allocation scheme should consider population migration and the possible preference for high-quality education.

Improving the service of E-bike sharing by demand pattern analysis: A data-driven approach

In recent years, there has been a surge in the popularity of free-floating e-bike sharing. However, the shared mobility sector is fiercely competitive demanding, efficient operations and high-quality service to cater to user expectations.We propose several data-driven methods that apply demand pattern analysis. We suggest the use of a new spatial unit (i.e., overlapping circles) to enhance the cost-efficiency and user-friendliness of e-bike sharing. Moreover, temporal clustering is employed to develop operational strategies that counter the imbalance in supply and demand in recurrent clusters.To evaluate the impact of these strategies, we introduce a framework and apply it in a case study of an e-bike sharing project in The Hague, The Netherlands. We identify 5 hourly clusters which enable reallocation strategies to alleviate the imbalance among spatial units in these clusters.The results demonstrate that the derived operational strategies improve the service significantly, with almost 1.5 times increased ridership, an approximately 20% decrease in vehicle idle time, and a decent monthly net retention rate of around 60%.

Distributionally robust optimal scheduling of integrated energy systems including hydrogen fuel cells considering uncertainties

The economic operation of the integrated energy system faces the problems of coupling between energy production and conversion equipment in the system and the imbalance of various energy demands. Therefore, taking system safety as the constraint and minimum economic cost as the objective function, including fuel cost, operation, and maintenance cost, this paper proposes the operation dispatching model of the integrated energy system based on hydrogen fuel cell (HFC), including HFC, photovoltaic, wind turbine, electric boiler, electric chiller, absorption chiller, electric energy storage, and thermal energy storage equipment. On this basis, a distributionally robust optimization (DRO) model is introduced to deal with the uncertainty of wind power and photovoltaic output. In the distributionally robust optimization model, Kullback–Leibler (KL) divergence is used to construct an ambiguity set, which is mainly used to describe the prediction errors of renewable energy output. Finally, the DRO economic dispatching model of the HFC integrated energy system (HFC-IES) is established. Besides, based on the same load scenario, the economic benefits of hybrid energy storage equipment are discussed. The dispatching results show that, compared with the scenario of only electric energy storage and only thermal energy storage, the economic cost of the scenario of hybrid electric and thermal storage can be reduced by 3.92% and 7.55% respectively, and the use of energy supply equipment can be reduced, and the stability of the energy storage equipment can be improved.

Examining the absorption of post-internship medical officers into the public sector at county-level in devolved Kenya: a qualitative case study

BackgroundAfter Kenya’s decentralization and constitutional changes in 2013, 47 devolved county governments are responsible for workforce planning and recruitment including for doctors/medical officers (MO). Data from the Ministry of Health suggested that less than half of these MOs are being absorbed by the public sector between 2015 and 2018. We aimed to examine how post-internship MOs are absorbed into the public sector at the county-level, as part of a broader project focusing on Kenya’s human resources for health.MethodsWe employed a qualitative case study design informed by a simplified health labour market framework. Data included interviews with 30 MOs who finished their internship after 2018, 10 consultants who have supervised MOs, and 51 county/sub-county-level managers who are involved in MOs’ planning and recruitment. A thematic analysis approach was used to examine recruitment processes, outcomes as well as perceived demand and supply.ResultsWe found that Kenya has a large mismatch between supply and demand for MOs. An increasing number of medical schools are offering training in medicine while the demand for MOs in the county-level public sector has not been increasing at the same pace due to fiscal resource constraints and preference for other workforce cadres. The local Department of Health put in requests and participate in interviews but do not lead the recruitment process and respondents suggested that it can be subject to political interference and corruption. The imbalance of supply and demand is leading to unemployment, underemployment and migration of post-internship MOs with further impacts on MOs’ wages and contract conditions, especially in the private sector.ConclusionThe mismatched supply and demand of MO accompanied by problematic recruitment processes led to many MOs not being absorbed by the public sector and subsequent unemployment and underemployment. Although Kenya has ambitious workforce norms, it may need to take a more pragmatic approach and initiate constructive policy dialogue with stakeholders spanning the education, public and private health sectors to better align MO training, recruitment and management.

Recent Advances on The Applications of Phase Change Materials in Cold Thermal Energy Storage: A Critical Review

Cold thermal energy storage (CTES) based on phase change materials (PCMs) has shown great promise in numerous energy-related applications. Due to its high energy storage density, CTES is able to balance the existing energy supply and demand imbalance. Given the rapidly growing demand for cold energy, the storage of hot and cold energy is emerging as a particularly attractive option. The main purpose of this study is to provide a comprehensive overview of the current research progress on the utilisation of PCMs in CTES. The greatest difficulties associated with using PCMs for CTES are also examined in this overview. In this regard, a critical evaluation of experimental and numerical studies of the heat transfer properties of various fundamental fluids using PCMs is conducted. Specifically, several aspects that affect the thermal conductivity of PCMs are investigated. These factors include nanoparticle-rich PCM, a form of encapsulated PCM, solids volume percentage, and particle size. Discussions focus on observations and conclusions are drawn from conducted studies on PCMs used in CTES. Based on the findings of this study, a set of plausible recommendations are made for future research initiatives.

Multi-objective optimal scheduling model for shared bikes based on spatiotemporal big data

Station-free bike sharing is one of the most important short-distance means of transportation. However, with the surge in the number of shared bikes, an imbalance of supply and demand in time and space caused by the disorderly parking of shared bikes has also emerged. This research combined massive spatiotemporal trajectory data of shared bikes and user travel demands to propose a feasible multi-objective optimal scheduling method. Specifically, this research presented a model that utilizes extensive order data to analyze user travel patterns, divides shared bike operation areas into internally connected communities by Geohash coding, and analyzes the shared bike dispatch hotspots in each community segment. Then, a novel model for multi-objective optimal scheduling of shared bikes was proposed based on NSGA-II. The model takes the number of transport vehicles participating in shared bike dispatching and the actual number of dispatch points as the decision variables, and its optimization goal is to reduce the cost of dispatching shared bikes and improve the utilization rate of shared bikes. The optimization effect of the model before and after the improvement of the genetic algorithm was analyzed, and the proposed optimized Pareto front solution set and optimal scheduling routes for shared bikes were given. Some of the results are noteworthy. First, the factors that affect the scheduling cost and utilization rate of shared bikes vary, so setting the variables reasonably is helpful for improving the optimization ability of the scheduling optimization model. Second, exploring the connections between shared bikes can effectively improve the scheduling efficiency of shared bikes. The research results are of great significance for optimizing dispatching routes and formulating low-carbon shared bike dispatching strategies.

Research on the Protection of Contracted Land Rights and Interests of Farmers who Settle Down in Cities under the Background of New Urbanization: Empirical Analysis and Foreign Reference

Farmers who settle in cities are the main element of urban-rural mobility, and how to protect their land rights is one of the key and difficult points in promoting China's new urbanization. In this paper, contracted land that bears the social security function of farmers is selected to study the protection of the rights and interests of farmers who settle in cities. Combined with relevant judicial cases, the current protection status of the rights and interests of contracted land of farmers who settle in cities is analyzed. It is found that there are still problems such as the imbalance of supply and demand in legal norms, the operation failure of supporting systems, and insufficient response to property protection. Summarize the basic experience of foreign countries in dealing with farmers' problems in coordinating urban and rural areas, and base on China's unique national conditions and policies. In order to further improve the protection of contracted land rights and interests of farmers who settle in cities, measures should be taken to strengthen the legal regulation of supply, deepen the reform of household registration, clarify the land ownership, build a diversified relief system, expand farmers' property rights and interests, and improve rural social security.

Data-driven robust optimization for contextual vehicle rebalancing in on-demand ride services under demand uncertainty

The rebalancing of idle vehicles is critical to mitigating the supply–demand imbalance in on-demand ride services. Motivated by a ride service platform, this paper investigates a short-term vehicle rebalancing problem under demand uncertainty in the presence of contextual data. We deploy a novel data-driven robust optimization approach that takes a direct path from “Data” to “Decision” instead of the predict-then-optimize paradigm and leverages the prediction problem structure to seamlessly integrate demand predictions with optimization models. We further develop a risk-based uncertainty set to evaluate how well uncertain demand is estimated from contextual data by prediction models, and discuss the classes of prediction models that are highly compatible with robust optimization models. Based on the convex analysis and duality theory, we reformulate the original models into equivalent Mixed Integer Second Order Cone Programmings (MISOCPs) that are solvable via state-of-the-art commercial solvers. To solve large-scale instances, we utilize the affine decision rule technique to derive polynomial-sized reformulations. Extensive experiments are conducted on the instances based on a real-world on-demand ride service in Chengdu. The computational experiments demonstrate the promising performance of our rebalancing strategies and solution approaches.

Challenges and countermeasures of China's research on "sports promoting adolescent socialization"-data mining based on Weibo and CNKI.

Understand the public demand for Adolescent socialization, and compare the hot spots in the researches of "sports promoting Adolescent socialization," so as to clarify the high-quality development direction of sports promoting Adolescent socialization in the new era. Collected the Weibo texts about "Adolescent socialization" from April 13, 2017 to June 1, 2022 through python, and used LDA to understand the relevant hot spots. Used City space to collect CNKI studies related to "sports promote Adolescent socialization," and used keyword co-occurrence network to understand hot spots. A total of 77,900 original Weibo texts were captured. The theme model identified five potential themes: "School and Family Education," "Social Participation," "Community Education," "Ideological and Political Education" and "Media." The semantic network showed that the public concerns of each theme include "Adolescent socialization education content," "relevant policies and regulations," "Adolescent socialization environment," "traditional culture" and "publicity ways and examples"0.52 studies were finally retrieved. The keyword co-occurrence network showed that keywords such as "Adolescent," "Socialization," "Sports Games," "School Sports" and "Family Sports" appeared more frequently and had higher intermediary centrality. Researches focused on Socialization, Internet Addiction, Coupling, School Sports, Sports Socialization Media. The public's attention to "Adolescent socialization" has three characteristics: subject linkage, object susceptibility, and media diversity. The researches on "Sports Promoting the socialization of Adolescents" has some problems, such as the imbalance of subject supply and demand, the inconsistent way of object supply and demand, and the different content of media supply and demand. The reason is that there is an information island between people and scholars. Existing research results can not meet the demands of the public.

Examining supply-demand imbalances and social inequalities of regulating ecosystem services in high-density cities: A case study of Wuhan, China

Rapid urbanization in high-density cities has resulted in supply–demand imbalances and inequalities of urban ecosystem services (ESs), necessitating integrated ESs assessment for managing regulating ecosystem services (RESs). Previous research has mainly focused on ESs supply, largely neglecting ESs demand measurement. To address this gap, this study proposes an evaluation system that considers environmental risks to analyze RESs supply–demand mismatch and social equality in Wuhan’s central area. Our research findings demonstrate that the supply capacity of RESs is closely linked to the distribution of land use, whereas the demand capacity of RESs is influenced by the areas’ environmental risks, such as hazard, exposure, and vulnerability. Additionally, our study reveals that 78.16% of neighborhoods in Wuhan experience a shortfall RESs, indicating that the demand for these services exceeds the supply. This imbalance gap decreases from the city center to the periphery. Notably, social inequalities exist in the allocation of RESs in Wuhan, with women and people residing in low-price houses in central areas, as well as the floating and low-educated population in marginal areas, experiencing more significant supply–demand imbalances. This study offers valuable insights into promoting the balance construction of urban ecological environments and advancing social equality through resilient urban planning.

A control with differential power-flow compensating of microgrid under symmetrical fault conditions

The load side failure of an independent microgrid will lead to an imbalance in power supply and demand and voltage drop in the fault area. The use of traditional reactive power compensation to achieve fault traversal in microgrids cannot effectively solve. This article proposes a differential power flow compensation control strategy based on micro source feeder impedance. Utilize micro source redundant power to increase active power output and compensate for the required power flow in the fault area. Calculate the power flow compensation coefficient based on the difference in feeder impedance, and dynamically adjust the reference value of power flow compensation according to the required power in the fault area. By rationalizing the distribution of fault flow, the transient power balance and voltage support in the fault area can be improved. To a certain extent, it enhances the fault resilience of the independent microgrid, and improves the working reliability during fault traversal. At the same time, it reduces the sharp increase in line losses caused by fault currents, and even endangers the security of network structures. The effectiveness of the strategy was verified through simulation and experiments.

Ride-Hailing Networks with Strategic Drivers: The Impact of Platform Control Capabilities on Performance

Problem definition: Motivated by ride-hailing platforms such as Uber, Lyft and Didi, we study the problem of matching riders with self-interested drivers over a spatial network. We focus on the performance impact of two operational platform controls—demand-side admission control and supply-side repositioning control—considering the interplay with two practically important challenges: (i) spatial demand imbalances prevail for extended periods of time; and (ii) self-interested drivers strategically decide whether to join the network, and, if so, whether to reposition when not serving riders. Methodology/results: We develop and analyze the steady-state behavior of a novel game-theoretic fluid model of a two-location, four-route loss network. First, we fully characterize and compare the steady-state system equilibria under three control regimes, from minimal control to centralized control. Second, we provide insights on how and why platform control impacts equilibrium performance, notably with new findings on the role of admission control: the platform may find it optimal to strategically reject demand at the low-demand location even if drivers are in excess supply, to induce repositioning to the high-demand location. We provide necessary and sufficient conditions for this policy. Third, we derive upper bounds on the platform’s and drivers’ benefits caused by increased platform control; these are more significant under moderate capacity and significant cross-location demand imbalance. Managerial implications: Our results contribute important guidelines on the optimal operations of ride-hailing networks. Our model can also inform the design of driver compensation structures that support more centralized network control. Supplemental Material: The e-companion and Supplemental Material are available at https://doi.org/10.1287/msom.2023.1221 .

Impact of Electric Vehicles toward Energy Reliability of the Jawa-Madura-Bali Electrical Power System

There is an observed limitation in the number of electric vehicles using batteries as power sources (e.g., plug-in electric vehicles) in Indonesia. While the number of said electric vehicles is increasing in response to the government’s commitment to shift the transportation energy source towards electric energy for a more sustainable environment, this change is followed by an inevitable impact on the current electric network and infrastructure. Indonesia’s government predicted that there will be around 20 million 2-wheelers and 4 million 4-wheelers ICE by the year 2030 with an additional load of 29.300 MW to be expected. Lessons learned from other countries have shown that the abrupt changes in the supply-demand energy for the electric vehicle, such as the deficit/surplus of energy or the duck curve phenomena, create an urgency to prevent the said phenomena and the potential financial loss that might have cross-sectoral impacts. Through an analysis of the Jawa-Madura-Bali system, an independent system that can produce 30.970 MW by the year 2020 [1], the paper focuses on the impact of this system in developing an adaptive infrastructure to address increased power needs for electric vehicles in Indonesia. Literature review and data analysis shows that the impact of Electric Vehicles on the Energy Reliability of the Jawa-Madura-Bali Electrical Power System is very pronounced. The amount of energy needed for the grid to be reliable in the EV transition is significantly higher than the natural growth of the grid energy supply. It is feasible that the increasing electricity demand from EVs could be offset by adding more renewable energy sources to the grid. Renewable energy sources, such as solar and wind, (both centralized and decentralized) can help to offset the insufficient total energy supply growth from the conventional power producer. One approach to address these challenges is to continue the development of mixed renewable and non-renewable energy sources, allowing the grid to draw on a variety of sources as needed to meet demand. This development can help to ensure a reliable and stable supply of electricity to meet the needs of electric vehicles and other customers. A supply-demand simulation and prediction, which could be a very helpful tool in the conceptualization of a management plan for the energy system to mitigate the imbalance of supply and demand of electric energy supply should be developed.