Wind Curtailment Research Articles

Optimal Scheduling of Integrated Energy System Considering Hydrogen Blending Gas and Demand Response

In the context of carbon neutrality and carbon peaking, in order to achieve low carbon emissions and promote the efficient utilization of wind energy, hydrogen energy as an important energy carrier is proposed to mix hydrogen and natural gas to form hydrogen-enriched compressed natural gas (HCNG). It is also injected into the natural gas pipeline network to achieve the transmission and utilization of hydrogen energy. At the same time, the participation of demand response is considered, the load’s peak and trough periods are adjusted, and the large-scale consumption of renewable energy and the reduction in carbon emissions are achieved. First of all, a fine model of hydrogen production and hydrogen use equipment is established to analyze the impact of adding hydrogen mixing on the economy and the low-carbon property of the system. With green certificates and demand response, the utilization rate of hydrogen energy is improved to further explore the energy utilization rate and emission reduction capacity of the system. Secondly, on the basis of modeling, the optimal scheduling strategy is proposed with the sum of energy purchase cost, equipment operation cost, carbon emission cost, wind curtailment cost, and green certificate income as the lowest objective function. Considering the constraints such as hydrogen blending ratio and flexible load ratio of the pipeline network, a low-carbon economic scheduling model of hydrogen mixed natural gas was established. The model was linearized and solved by using MATLAB 2021a and CPLEX solver. By comparing different scenarios, the superiority of the model and the effectiveness of the strategy are verified.

Optimal scheduling of integrated energy systems with a ladder-type carbon trading mechanism and demand response

Introduction: To achieve the “dual carbon” goal, the integrated energy system (IES) needs to take into account both economic and low-carbon requirements while meeting the growing energy demand.Methods: Therefore, an optimal scheduling model for low-carbon economic operation is proposed. Firstly, a more accurate carbon emission model is used to consider the actual carbon emission of gas load, to improve the original carbon emission model. A ladder-type carbon trading mechanism is introduced to further constrain the carbon emission of IES. Then, the demand-side response model is proposed, which uses the time-of-use price and mutual substitution of electricity, heat, and gas loads to curtail, time-shift, and substitute the load. Finally, an optimal scheduling model with minimum energy purchase cost, wind and photovoltaic curtailment cost, demand response cost, and carbon emission cost is constructed, which is solved by the GUROBI solver.Results: Through comparative simulation analysis of 6 cases, the results show that the objective function considers the traditional carbon trading cost to reduce carbon emission by about 19.3% compared with the case without considering. After adopting the ladder-type carbon trading mechanism, the carbon emission of IES can be further limited by about 0.35%, and the appropriate carbon trading base price is explored. In addition, after the demand response, the energy purchase cost, carbon trading cost, and carbon emission of IES are reduced by about 3.4%, 18.5%, and 36.2%, respectively, compared with those before the demand response. The simulation results verify the effectiveness of the proposed model.

Optimal configuration of energy storage considering flexibility requirements and operational risks in a power system

The integration of renewable energy units into power systems brings a huge challenge to the flexible regulation ability. As an efficient and convenient flexible resource, energy storage systems (ESSs) have the advantages of fast-response characteristics and bi-directional power conversion, which can provide flexible support for the power system. This paper establishes an optimization model for the ESS based on a bi-level programming model. The upper-level model optimizes the decision strategy of ESS configuration planning. The lower-level model is based on scenario analysis theory to simulate the operation of typical daily scenarios. Flexibility requirement constraints are added to characterize the required flexibility resources of the power system. In addition, the conditional value-at-risk (CVaR) is applied to characterize the risk of wind curtailment and load shedding during operation. To simplify the model, a set of association constraints is introduced to convert the original bi-level programming model into a direct-solvable single-level mixed-integer linear programming (MILP) model. Finally, the effectiveness of the proposed model is verified through case studies.

The potential of decentral heat pumps as flexibility option for decarbonised energy systems

Decarbonising the energy system requires high shares of variable renewable generation and sector coupling like power to heat. In addition to heat supply, heat pumps can be used in future energy systems to provide flexibility to the electricity system by using the thermal storage potential of the building stock and buffer tanks to shift electricity demand to hours of high renewable electricity production. Bridging the gap between two methodological approaches, we coupled a detailed building technology operation model and the open-source energy system model Balmorel to evaluate the flexibility potential that decentral heat pumps can provide to the electricity system. Austria in the year 2030 serves as an example of a 100% renewable-based electricity system (at an annual national balance). Results show that system benefits from heat pump flexibility are relatively limited in extent and concentrated on short-term flexibility. Flexible heat pumps reduce system cost, CO2 emissions, and photovoltaics and wind curtailment in all scenarios. The amount of electricity shifted in the assessed standard flexibility scenario is 194 GWhel and accounts for about 20% of the available flexible heat pump electricity demand. A comparison of different modelling approaches and a deterministic sensitivity analysis of key input parameters complement the modelling. The most important input parameters impacting heat pump flexibility are the flexible capacity (determined by installed capacity and share of control), shifting time limitations, and cost assumptions for the flexibility provided. Heat pump flexibility contributes more to increasing low residual loads (up to 22% in the assessed scenarios) than decreasing residual load peaks. Wind power integration benefits more from heat pump flexibility than photovoltaics because of the temporal correlation between heat demand and wind generation.

A day-ahead coordinated scheduling strategy for source storage and load considering demand response and lines loss

Day-ahead scheduling strategy is an effective way to improve the renewable energy accommodation. To increase the renewable energy accommodation in the regional power grids, reduce the total costs of the power system, and improve the supply reliability of the power system, this research suggests a multi-time-scale “source-storage-load” coordinated dispatching strategy that considers the distribution and characteristics of pumped energy storage and loss of the network. Taking the wind curtailment penalty costs, the system operating costs, and the load loss penalty costs as the objective functions, a day-ahead coordinated scheduling strategy for source storage and load considering demand response and lines loss is established. Finally, the commercial software package CPLEX is called through the MATLAB platform to complete the optimization of mixed integer programming. Simulation results shows that the proposed scheduling strategy could build the power generation plant, effectively adjust the output power of pumped storage, and regulate the assumption of translationable load and transferable load.

Low-Carbon Economic Dispatch of Integrated Energy Systems in Industrial Parks Considering Comprehensive Demand Response and Multi-Hydrogen Supply

To address the increasing hydrogen demand and carbon emissions of industrial parks, this paper proposes an integrated energy system dispatch strategy considering multi-hydrogen supply and comprehensive demand response. This model adopts power-to-gas technology to produce green hydrogen, replacing a portion of gray hydrogen and incorporates a carbon capture system to effectively reduce the overall carbon emissions of the industrial park. Meanwhile, incentive-based and price-based demand response strategies are implemented to optimize the load curve. A scheduling model is established targeting the minimization of procurement, operation, carbon emission, and wind curtailment costs. The case study of a northern industrial park in China demonstrates that the joint supply of green and gray hydrogen reduces carbon emissions by 40.98% and costs by 17.93% compared to solely using gray hydrogen. The proposed approach successfully coordinates the economic and environmental performance of the integrated energy system. This study provides an effective scheduling strategy for industrial parks to accommodate high shares of renewables while meeting hydrogen needs and carbon reduction targets.

Bi-level configuration and operation collaborative optimization of shared hydrogen energy storage system for a wind farm cluster

Energy storage is indispensable to achieve dispatchable and reliable power generation through renewable sources. As a kind of long-duration energy storage, hydrogen energy storage systems are expected to play a key role in supporting the net zero energy transition. However, the high cost has become an obstacle to hydrogen energy storage systems. The shared hydrogen energy storage (SHES) for multiple renewable energy power plants is an emerging mode to mitigate costs. This study presents a bi-level configuration and operation collaborative optimization model of a SHES, which applies to a wind farm cluster. Different operation modes, including the ‘electricity‑hydrogen-electricity (E-H-E)’ mode and the ‘electricity‑hydrogen (E-H)’ mode, are considered. Results show that SHES system offers substantial advantages over individual hydrogen energy storage solutions. It achieves a notable reduction in annual operation and maintenance (O&M) costs by 9.5 % and a significant increase in annual profit by 10.49 %. Moreover, the SHES system demonstrates a lower wind curtailment rate of 0.24 %, in contrast to the 0.37 % observed in individual cases. SHES will play a more significant role in larger wind farm clusters. The aforementioned advantages of SHES systems become even more pronounced in larger wind farm clusters, where their impact on cost reduction and efficiency is significantly amplified.

Optimal Operation Scheduling of Multi-energy Complementary Systems Including Offshore Wind Power

Background: With the rapid development of offshore wind power in China, offshore wind power is accounting for an increasing proportion of the whole installed power generation in China, which put forward higher requirements for operation scheduling of multi-energy complementary systems including offshore wind power. However, existing studies have paid little attention to the complementary output scheduling of multi-energy systems with a high proportion of offshore wind power, this phenomenon is not conducive to the realization of reasonable operation scheduling. Objective: To realize the reasonable operation scheduling of multi-energy systems with a high proportion of offshore wind power. Methods: Firstly, the output characteristics of offshore wind power were analyzed and summarized, and modeling was conducted from the perspectives of time distribution, spatial correlation, volatility and randomness, which would serve as the theoretical basis for subsequent researches. Secondly, the complementary rule among offshore wind power and the multi-energy system was analyzed, and the complementary characteristic index was put forward. Then the safety operation was taken as the constraint, and the two-stage operation model of the integrated energy system was established, which considers the auxiliary service costs. In the first stage, the initial generation scheduling was developed according to the day-ahead forecast values of the offshore wind power; in the second stage, the more accurate intra-day operation scheduling was further achieved by considering the intra-day forecast values of offshore wind power and the day-ahead scheduling results. Costs of rotating reserve capacity could be reduced by correcting the deviation of generating capacity, then the revenue-maximizing scheduling strategies were obtained and the output of the pumped-storage power plants was optimized. Results: The effectiveness of the model proposed in this paper was verified based on the simulation examples. Compared with the traditional scheduling strategy, the scheduling strategy considering auxiliary service cost proposed in this paper can promote the consumption of offshore wind power, reduce the wind curtailment proportion and improve the electricity sales revenues in the end. Conclusion: The research results in this paper provide a reference for the reasonable consumption of multi-energy complementary systems with a high proportion of offshore wind power and improving electricity sales revenues

Exploring wind curtailment effects and economic implications in the growing variable renewable energy penetration

Several countries continue to invest in variable renewable energy (VRE) sources to replace fossil fuels and achieve a nationally determined contribution. Consequently, as the share of VRE generation in each country's power grid increases, its curtailment also increases. Current studies on VRE curtailment are based on a comparative analysis of statistical data collected from different countries. However, only a few studies present detailed results based on historical curtailment data collected from individual wind farms. This study analyzes the curtailment data collected for three wind farms over four years. The duration, curtailed output, and cost per curtailment were determined to be 200 min, 38 MWh, and $3.02k, respectively. Finally, the curtailment loss to wind farms caused by the increasing share of VRE generation in the power grid was estimated. The curtailed output and curtailment cost are estimated to increase by 1.3 GWh and $107.6k, respectively, when the share of VRE in the power grid increases by 1%. These findings can aid in identifying the curtailment experienced by wind farm operators and subsequent potential economic losses. Moreover, they can form the basis for establishing an efficient curtailment cost compensation system.

Integration of curtailed wind into flexible electrified heating networks with demand-side response and thermal storage: Practicalities and need for market mechanisms

Increasingly high renewable penetration in electrified energy systems causes increasing levels of curtailment that must eventually be mitigated. System flexibility, energy storage and demand-side response in the form of flexible heating and cooling demands are efficient solutions for curtailment mitigation, however challenges remain such as the economic benefits of energy storage and the financial impacts of curtailment mitigation on consumers, among others. In this paper the mitigation of curtailed wind energy, incentivised with discount payments, through flexible electrified heating networks with demand-side response and thermal energy storage is investigated with a genetic optimisation algorithm, and results are analysed in terms of overall costs, technical feasibility and level of curtailed wind use from the perspective of the network operator and consumer. It is found that large-scale thermal storage lowers the cost and increases levels of curtailed wind integration, and allows district heating networks to run almost entirely on otherwise curtailed wind energy (up to 97.0 % in the example considered here). However without adequate market mechanisms, demand-side response is financially beneficial to all stakeholders only at low levels; with a split cost approach, financial incentives or market mechanisms are necessary for higher levels of, and more efficient, wind curtailment mitigation.

A risk-aware and second-order cone programming model for wind expansion planning considering correlated uncertainties using the copula method

Integration of large-scale renewable energy sources (RESs) into existing power grids is challenging for power system operators and planners due to the intermittent and uncertain characteristics of RESs and the limitation of transmission capacity. This paper presents a new risk-based framework to obtain the optimal placement and sizing of wind farms in the bulk power system considering the impact of mutual correlation between wind farms’ power productions in different candidate buses. In this regard, a second-order cone programming (SOCP) optimization problem is developed to minimize the total expected social cost including the operation cost of conventional generators, wind curtailment cost, and the investment cost of newly installed wind farms. In the proposed model, the correlated uncertainties of wind power production are incorporated using the copula method. Also, the conditional value-at-risk (CVaR) measure is utilized to manage the risk of the model associated with uncertainties. The proposed planning model is then implemented into the Garver 6-bus and IEEE 118-bus test systems. Given the results, employing SOCP-based AC OPF in the presented planning model results in a precise solution, demonstrating an 87% reduction in running time. Moreover, the numerical results illustrate that by considering the correlation between wind farms’ power production and reducing the risk parameter, there is a significant increase in the installed capacity of wind farms.

Dynamic optimal control strategy for distributed electric heating system under electricity pricing lever

To address wind curtailment, a method is proposed to improve wind power consumption by controlling user demand response. Considering residents’ comfort demand for heating in winter, a distributed electric heating system is established and an optimal control model is established to enhance wind power consumption capacity. By considering the influence of electricity price and comparing the optimal model under basic tariffs, time-of-use and real-time tariffs, a dynamic optimal control method for distributed electric heating systems driven by electricity price leverage is proposed. The simulation results show that the method can effectively guide electric heating users to actively participate in load regulation, significantly improve wind curtailment and ensure economic and stable power grid operation. Using different electricity prices as leverage can systematically incorporate a large number of distributed electric heating users into the controllable load of wind power consumption, providing a new method for large-scale wind power consumption.

Robust optimal dispatch strategy of integrated energy system considering CHP-P2G-CCS

Integrated energy systems (IESs) can improve energy efficiency and reduce carbon emissions, essential for achieving peak carbon emissions and carbon neutrality. This study investigated the characteristics of the CHP model considering P2G and carbon capture systems, and a two-stage robust optimization model of the electricity-heat-gas- cold integrated energy system was developed. First, a CHP model considering the P2G and carbon capture system was established, and the electric-thermal coupling characteristics and P2G capacity constraints of the model were derived, which proved that the model could weaken the electric-thermal coupling characteristics, increase the electric power regulation range, and reduce carbon emissions. Subsequently, a two-stage robust optimal scheduling model of an IES was constructed, in which the objective function in the day-ahead scheduling stage was to minimize the start-up and shutdown costs. The objective function in the real-time scheduling stage was to minimize the equipment operating costs, carbon emission costs, wind curtailment, and solar curtailment costs, considering multiple uncertainties. Finally, after the objective function is linearized with a ψ-piecewise method, the model is solved based on the C&CG algorithm. Simulation results show that the proposed model can effectively absorb renewable energy and reduce the total cost of the system.

Increase the integration of renewable energy using flexibility of source-network-load-storage in district cooling system

The flexibility of power systems is critical to cope with the variability and uncertainty caused by the integration of renewable energy resources. Incorporating district cooling systems (DCSs) into power systems is an emerging approach to provide flexibility for renewable energy utilization. However, the existing models of DCS components, such as ice-storage cooling sources, cooling pipelines, and cold warehouses, are simplified, failing to fully utilize that flexibility, which brings difficulties for renewable energy utilization. Therefore, this paper proposed a coordinated operational strategy for an integrated power and cooling system combining detailed operating characteristics of DCSs to exploit the potential flexibility of DCSs for better integration of renewable energy. The primary cooling source components, including the chiller, ice storage tank, pump, and cooling tower, are established to model a detailed process of cooling generation and storage. The thermal inertial of district cooling networks (DCNs) is formulated as a quasi-dynamic model by considering dynamical temperature characteristics and transmission delay to exploit the virtual energy storage capacity of the cooling water pipeline. Moreover, the thermal inertia of the demand side, such as buildings and cold warehouses, is considered to utilize thermal storage capacity. The objective function of the proposed optimization model is to minimize the overall operating cost of the integrated power and cooling system. Numerical simulations show that the proposed method could reduce the operating cost by 15.4% and the wind curtailment rate by 86.2%, indicating better performance of the proposed method in improving economic benefits and reducing renewable energy curtailment.

Optimal scheduling of electric-gas-heat system considering dual virtual energy storage of gas network management and heat network storage

Aiming at the problem of wind curtailment caused by the lack of system flexibility, an optimal scheduling strategy for improving the flexibility of the electricity-gas-heat interconnection system by the coordinated operation of the gas network management and storage characteristics and the heat storage characteristics of the heat network is proposed. Firstly, the influence of gas network storage and heat network storage on improving flexibility is analyzed respectively. Then, an electricity-gas-heat interconnected system scheduling model considering the dynamic characteristics of gas network management and t the delay characteristics of heat storage in heat network, which greatly improves the imbalance between supply and demand of flexibility in space and time brought by the anti-peak regulation characteristics of wind power to the system. Finally, the IEEE-24 nodes power system, Belgium’s 20-node natural gas network and 6-node thermal network are used, for example, analysis. The results show that the proposed scheduling scheme improves the flexibility of the system while its operating cost and wind curtailment cost are the lowest, which promotes the consumption of wind power.

Low-carbon joint dispatch of integrated energy systems based on differentiated dynamic pricing mechanisms

World is facing the severe crisis of energy supply and great pressure of carbon emissions reduction. The development of an integrated energy system (IES) is a way to meet the goal of carbon peaking and carbon neutrality. To ensure the coordination of economic benefits of source and load sides in the low-carbon dispatch, an internal multi-stakeholder’s joint optimal dispatch model of an IES considering differentiated dynamic pricing mechanisms is proposed. A joint optimization coordination center (JOCC) is established responsible for differentiated dynamic pricing and joint optimal dispatch of an IES. The JOCC sets the selling prices of electricity and heat from different sources by introducing the concept of additional carbon emission price of ladder-type for non-clean units. The JOCC is then responsible for the information interaction of the integrated energy operator (IEO) on the source side and the load aggregator (LA) on the load side. In addition, the JOCC sets the joint optimization objective function to determine the optimal dispatch strategy which realizes the coordination of economic benefits of source and load sides. CPLEX was used to solve the mixed integer linear programming (MILP) model. Case studies verified that the proposed joint optimal dispatch model of an IES considering differentiated dynamic pricing mechanisms can endow users with the right to choose energy from different sources and improve their enthusiasm to participate in integrated demand response (IDR), that realizes the coordination of economic benefits of multi-stakeholders on the basis of ensuring the low-carbon characteristics of the IES. Compared with the time-of-use pricing strategy, carbon emissions are reduced by 2.41%, wind curtailment is reduced by 49.31%, and the total cost of LA is reduced by 26.53%.

Multi energy complementary optimization scheduling method for wind solar energy storage and charging integrated energy system

Abstract IES (The Integrated Energy System), consisting of distributed wind and solar power generation and multiple types of loads for cooling, heating, and electrical systems, is an important application scenario in the current energy configuration. It is not possible to balance multiple objectives like economy, carbon emissions, and wind and solar energy curtailment. Furthermore, there are numerous equipment that have multiple energy flows, complex conversion processes, and multiple scheduling requirements. Therefore, multi-objective optimization and minute-level scheduling strategies are key technologies to improve the utilization efficiency of comprehensive energy systems. This article proposes a comprehensive method for optimizing and scheduling energy systems that is based on multi-objective optimization and multi-time scale decomposition. Firstly, a comprehensive energy system architecture for wind solar storage and charging was constructed, and its operational characteristics were analyzed. Then, a multi-objective optimization scheduling model was established, which comprehensively considered multiple objectives such as system operating cost, minimum carbon emissions, and minimum wind and solar curtailment rate. Through time scale decomposition, the optimization scheduling problem was transformed into multiple subproblems and solved separately. Finally, it was verified through a case study. The simulation results show that the constructed model reduces the total operating cost by 5%, the wind abandonment rate by 7%, and the carbon emissions by 5.6% compared to the system without energy storage and charging piles. This verifies the effectiveness of the constructed model, reduces the system operating cost, and reduces the impact on the environment; compared with the DA-P (Day Ahead Programming), the proposed optimization method reduced the system’s electricity purchase cost by 7.51%, increased renewable energy utilization by 11%, and reduced carbon emissions by 6.1%. This verifies the feasibility of the proposed method in reducing system operating costs, improving system environmental protection, and stabilizing the system.

As Grids Reach 100% Renewable at Peak, Growing Curtailment of 8 Gigawatts Looms as a Challenge to Decarbonization

In April 2022, the California Independent System Operator (CAISO) power grid reached momentary peaks of 100% renewable energy for the first time. After a year, momentary 100% supply from renewables isn't a news any more, and CAISO reported record wind and solar renewable curtailment of 606 GWh (March 2023) and 686 GWh (April 2023). In addition, peak renewable coincided with curtailment rates of 8 GW in April 2023. Our prior studies documented monthly-peak renewable curtailment growth of 40% annually (23 GWh in March 2015 growing to 82 GWh in March 2017). Updating for 2018-2023 shows that 40% annual growth has continued through April 2023 and with it, CAISO has reached an average sunlight hours curtailment rate of 2 GW. If this 9-year trend continues unchecked for the next 5 years, monthly curtailment is projected to reach 3.3 TWh in both March and April of 2028, an average sunlight curtailment rate of nearly 11 GW. We analyze causes of increased curtailment, and discuss its likely future trajectory (growth). We also discuss the challenges its growth represents for grid decarbonization. Finally we outline the difficulties in reducing curtailment growth and highlight several new opportunities for power grids and computing systems.

Low carbon scheduling method of electric power system considering energy-intensive load regulation of electrofused magnesium and wind powerfluctuation stabilization

The significant expansion of wind power has presented challenging obstacles to power system operation. The inherent stochasticity and variability of wind power have emerged as critical issues that impede the advancement of wind energy, affecting its integration and volatility control. Moreover, with the momentum of carbon peaking and carbon neutrality objectives, reducing CO2 emissions has become urgent. This study proposes a low-carbon dispatching methodology for power systems to address these challenges. It considers regulating energy-intensive loads of electrically fused magnesium and mitigating wind power fluctuations. The approach involves integrating electrically Fused magnesium loads with tight regulation characteristics on the demand side alongside thermal power plants to optimize the power grid and dispatch collectively. And battery energy storage devices are introduced into various wind power stations on the supply side to smooth out wind power fluctuations. The objective function aims to minimize the sum of the average variance of power fluctuations at all wind power busbars while adhering to constraints of maximum wind power consumption and minimum carbon emissions from thermal power plants. The problem is solved using genetic algorithms. Ultimately, we show how effective our proposed low-carbon dispatching method for power systems is, which deals with regulating energy-intensive loads of electrically fused magnesium and reducing wind power fluctuations. We demonstrate this through a case study of wind curtailment, CO2 emissions, wind power fluctuations, and other related parameters under different conditions. The approach can enhance renewable energy consumption, reduce carbon emissions, and mitigate the power fluctuations of renewable energy.

Quantifying resilient urban energy systems: Statistical analysis of climate adaptation, renewable integration, and socioeconomic dynamics

Multi-energy systems (MES) become increasingly important to accommodate renewable energy (RE) since fossil fuels diminish and RE is more prevalent. Power systems are challenged by high penetrations of RE, including frequent wind curtailments and uncertain RE resources threatening their security. A 2-step scheme for MES is proposed in the study to generate reliable operational decisions by incorporating integrated heat-electricity demand response (DR). In the initial phase, dynamic programming was applied to determine the optimal solution for previous linkage sessions. Subsequently, machine learning techniques were trained using historical data and the resulting optimal decisions to make optimal real-time decisions without prior knowledge of future power costs or vehicle usage. An accurately trained deep neural network is capable of significantly reducing charging costs, usually approaching the retrospectively calculated optimum charging price. In the suggested scheme, the operating prices are minimized under a base scenario ensuring that no constraint is violated regardless of the scenario. RE curtailment can be reduced significantly with power-to-gas (P2G) devices that convert excess energy from wind and photovoltaic sources into natural gas. In addition, this paper proposes integrated heat-electric DR as a means of reducing operating prices and enhancing security against uncertainties by employing couplings between different systems. The outcomes show that robust optimization enhances the security of systems, and the unified electric-heat DR can boost the use of RE while improving the economic benefit. It should be noted that this paper investigated under the impact of the climate changes and also socioeconomic dynamics that can change consuming energy in urban systems.