Impact Of Electricity Price Research Articles

Unraveling the effect of electricity price on electric vehicle charging behavior: A case study in Shenzhen, China

Estimating price elasticity of demand for electric vehicle charging contributes to the accurate determination of charging price, thereby improving electric vehicle adoption and energy sustainability. However, few studies have studied the impact of electricity price on electric vehicle charging behavior, especially the demand spillover effect caused by price fluctuations. To fill the gaps, on a citywide dataset of public charging piles in Shenzhen, China, first, correlation coefficients and hypothesis tests are used to determine the relationship between charging demand and price. A learning model incorporating two-layer graph attention, temporal pattern attention, and knowledge-embedded meta-learning is developed for accurate spatio-temporal regression. Impulse response analysis is conducted to unravel several noteworthy phenomena: (1) public charging demand is inelastic to electricity price, with an average elasticity of −0.76, and distinction between different functional areas and times is revealed; (2) negative price impulses marginally change the elasticity, while positive ones make electric vehicle charging users more price sensitive, and (3) the spillover effects caused by price increases and decreases bring 89.48% and 53.88% of its local demand changes to neighbors, respectively, with a scope of 3.45 kilometer. These findings provide policy implications for promoting electric vehicle charging to facilitate renewable energy transition.

Hierarchical optimization for the energy management of a greenhouse integrated with grid-tied photovoltaic–battery systems

This study addresses the challenges of high energy consumption and environmental concerns in traditional greenhouse operations by exploring an integrated greenhouse with grid-tied photovoltaic (PV)-battery systems. A two-layer hierarchical optimization framework is proposed for effective energy management. In the upper layer, greenhouse operations are optimized with the Energy Consumption Minimization (ECM) strategy and the Energy Cost Minimization (ECoM) strategy, ensuring suitable climate conditions while reducing energy use and costs. In the lower layer, the scheduling of the hybrid energy system is optimized with the Self-consumption Maximization (SCM) strategy and the Total Cost Minimization (TCM) strategy, aiming to maximize the self-consumption of PV power and minimize total costs, including energy costs, battery aging costs, and carbon emission costs, while meeting the greenhouse’s electricity demand. A sensitivity analysis is conducted to investigate the impact of electricity prices, feed-in tariffs, battery capacity, and PV array area on hybrid energy system scheduling. Results reveal that the ECoM strategy reduces costs by 6.98% compared to the ECM strategy, and the TCM strategy reduces total costs by 43.50% compared to the SCM strategy. Battery capacity and PV array area are found to have a more significant influence on total costs than electricity prices and feed-in tariffs. This study can offer crucial insights for realizing cost-effective and environmentally friendly greenhouse operations, contributing to the advancement of sustainable agriculture.

Multi-objective optimization of a hybrid carbon capture plant combining a Vacuum Pressure Swing Adsorption (VPSA) process with a Carbon Purification unit (CPU)

The imperative challenge posed by climate change requires urgent actions to counteract the harmful effects of greenhouse gas emissions, particularly CO2, which contributes to approximately 80 % of emissions responsible for global warming. A hybrid system combining Vacuum Pressure Swing Adsorption (VPSA) unit with a Cryogenic Carbon Purification Unit (CPU) is evaluated to enhance recovery and purity of CO2captured from flue gas containing CO2concentration ranging from 5 % to 20 %. VPSA preconcentrates the CO2and CPU completes the separation and purifies the CO2. The study uses surrogate models for multi-objective optimization, considering energy consumption, cost, and CO2recovery, providing a time-efficient approach for investigating computationally demanding processes. Results from the study indicate that the hybrid system achieves over 90 % recovery for flue gas concentration range considered, while ensuring the production of high-purity CO2(>99.99 %) suitable for transportation. A trade-off analysis reveals the balance between recovery, electricity consumption, and economic viability. A sensitivity analysis identifies parameters influencing recovery and energy consumption, providing guidance for future optimization efforts. The techno-economic analysis highlights the impact of electricity prices and carbon taxes on total costs, identifying an optimum towards higher recovery values under rising carbon taxes. Furthermore, the research underscores concentration-dependent economic feasibility, emphasizing the attractiveness of concentrations above 10 % compared with other technologies, which require higher concentrations. For an electricity price of 75 €.MWh−1, the total cost of the CO2 capture hydride system considering CO2 emissions with carbon tax of 100 €.tCO2−1 for concentrations ranging from 10 % to 20 % is from 123 to 80 €.tCO2−1, respectively. The analysis of the electricity source shows the importance of a low-carbon emission energy mix for optimal carbon emission reduction.

Lessons from Regional Electricity Demand Change following Natural Disasters in Japan

Analyzing the impact of electricity price changes on electricity demand helps in energy supply planning. This study estimated the electricity demand functions of households and industries, as well as the impact of electricity price hikes on electricity demand following natural disasters. We found that structural changes occurred in various regions' electricity demand's price elasticity following natural disasters. Furthermore, the results showed that the decrease in consumer surplus associated with higher electricity prices was more significant in regions that depended on nuclear power. These results have important implications for regional energy policies.

Research on Industrial Economic Development and Electricity Price Adjustment Strategy Based on Multi-Agent Game

With the deepening of the electricity market reform and the accelerating transformation of the new power system, the number of new electricity customers in the market with local development characteristics has increased. The local industrial and economic development have been affected by the ability to guide electricity prices. In this paper, using the multi-agent game based on exploring the impact of electricity price on the industrial economy, the specific optimization scheme of electricity price adjustment is proposed with the aim of improving the overall efficiency of the power grid and reducing the cost of electricity for industrial users. After the game, the overall efficiency of the electricity supplier will be increased by about 3.06 percent, and the cost of electricity used by various special industries will be reduced by about 6.86 percent to 4.48 percent. The win-win situation of the electricity suppliers’ income and the featured industries’ development can be achieved by the optimization results. As well as the cost of electricity consumption in featured industries can be reduced, and the comprehensive benefits of electricity suppliers can be improved by using the electricity price adjustment scheme after game interaction, which promotes the rational use of energy and meets the current social requirements for the green and sustainable development of the electricity industry.

The electric shock: Causes and consequences of electricity prices in the United Kingdom

This study explores the primary causes of wholesale electricity price fluctuations in the United Kingdom (UK). Using the structural vector autoregression (SVAR) model that identifies both supply-side and demand-side shocks, and monthly data for the period from January 1996 to May 2022, the findings show that the impact of electricity price increases on the real electricity price is dependent on the underlying cause of the price increase. Electricity price movements in the most recent period of global hardships from 2020 to 2022, including the Covid-19 pandemic and the Russian invasion of Ukraine, are further examined, which were widely discussed to have affected the global energy segment. The findings show that although shocks to natural gas had a part to play in the recent price increase of electricity, some major contributing factors remain unique to the UK. Finally, the findings put into perspective and question the effectiveness of the energy cap considering the large contribution of renewable power generation.

Sustainable Development of the European Electricity Sector: Investigating the Impact of Electricity Price, Market Liberalization and Energy Taxation on RES Deployment

Replacing conventional CO2 intensive generation with green electricity from RES constitutes an essential prerequisite of sustainable development. Renewables play a vital role in achieving the UN’s goals for clean low-cost energy production and the reverse of climate change process. Based on a comprehensive dataset including observations for 17 European countries between 2003 and 2020, the present research attempts to unveil the fundamental determinants of RES deployment. A panel FMOLS approach was utilized to provide a detailed analysis of the impact of electricity prices, energy taxes and competition level in both power generation and the retail electricity market on each country’s RES percentage participation in electricity production fuel mix. The final econometric outcomes verified the strong statistical significance of all examined variables for the vast majority of the countries, constituting them crucial aspects of national energy strategies. However, both the actual effects as well as the impact size were found to differ significantly across Europe, signifying the complexity of the EU’s task to develop a unified, autonomous and eco-friendly electricity market based on the principals of a fundamental energy strategy. Contributing to state authorities’ and EU’s colossal effort to deal with the crucial challenges of RES power generation, the paper proposes a series of targeted individual and groupwise policy implications.

Optimization of radiator area of CHP-based district heating system based on energy cascade utilization

Based on energy cascade utilization, the relative radiator area ratio (RRAR) of combined heat and power (CHP)-based district heating (DH) system was optimized. An optimization model for obtaining the optimal RRAR and minimum annual total cost (ATC) was developed. A CHP-based DH system in Tianjin, China, was taken as a case study. The impact of RRAR on the extracted and exhaust heat was analyzed. Moreover, the impact of equipment lifetime, radiator price, electricity price and interest rate on the optimization results was analyzed through sensitivity analysis. Results confirm that the developed model can be used to obtain the optimal RRAR. With the increase of RRAR, the extracted and exhaust heat used in absorption heat pump (AHP) increases, whereas the extracted heat used in heat exchanger related to extracted heat (HEXT) decreases. Correspondingly, the increase of RRAR results in the decrease of the total extracted heat and increase of the total exhaust heat. Enormous economic, energetic and environmental benefits can be achieved through the utilization of the optimal RRAR. According to sensitivity analysis, the radiator price and electricity price have a larger impact on the optimal RRAR, while the impact of electricity price on the minimum ATC is the largest.

Electric vehicle batteries for a circular economy: Second life batteries as residential stationary storage

By 2030 the sales of electric vehicles (EV) are set to increase 6 to 30 folds compared to the levels of 2019 thereby leading to an increase of discarded EV batteries. This creates a challenge to sustainably handle the waste by repurpose and recycling the EV batteries. In this paper, a method to analyze the usage of EV batteries throughout their life cycle in light of their contributions to a circular economy is proposed. The study is divided into two stages which are modelled with mixed-integer linear optimization. Stage 1 considers the optimal charging strategy for an EV and stage 2 represents the second-life of the EV battery as stationary energy storage in a residential building. Six scenarios were created for both stages; stage 1 includes smart charging and/or Vehicle to Grid (V2G) and stage 2 adds demand side management and/or PV self-consumption maximization to stage 1. A sensitivity analysis is performed to assess the impact of electricity prices. The results are analysed to assess the operational lifetime and economic savings for an EV owner. The results show that using second-life batteries in a residentail building can extend the lifetime of an EV battery by 3–5 years while allowing savings above 23%.

Managing energy-water-carbon-food nexus for cleaner agricultural greenhouse production: A control system approach

Poverty, food insecurity and climate change are global issues facing humanity, threatening social, economic and environmental sustainability. Greenhouse cultivation provides a potential solution to these challenges. However, some greenhouses operate inefficiently and need to be optimized for more economical and cleaner crop production. In this paper, an economic model predictive control (EMPC) method for a greenhouse is proposed. The goal is to manage the energy-water‑carbon-food nexus for cleaner production and sustainable development. First, an optimization model that minimizes the greenhouse's operating costs, including costs associated with greenhouse heating/cooling, ventilation, irrigation, carbon dioxide (CO2) supply and carbon emissions taking into account both the CO2 equivalent (CO2-eq) emissions caused by electrical energy consumption and the negative emissions caused by crop photosynthesis, is developed and solved. Then, a sensitivity analysis is carried out to study the impact of electricity price, supplied CO2 price and social cost of carbon (SCC) on the optimization results. Finally, a model predictive control (MPC) controller is designed to track the optimal temperature, relative humidity, CO2 concentration and incoming radiation power in presence of system disturbances. Simulation results show that the proposed approach increases the operating costs by R186 (R denotes the South African currency, Rand) but reduces the total cost by R827 and the carbon emissions by 1.16 tons when compared with a baseline method that minimizes operating costs only. The total cost is more sensitive to changes in SCC than that in electricity price and supplied CO2 price. The MPC controller has good tracking performance under different levels of system disturbances. Greenhouse environmental factors are kept within specified ranges suitable for crop growth, which increases crop yields. This study can provide effective guidance for growers' decision-making to achieve sustainable development goals.

Comparison of groundwater costs calculated with different methods and the effect of electricity subsidy liberalization

In managing groundwater demand, pricing system reform plays an important role; however, changing water price faces political and social resistance for optimal pricing, it is necessary to calculate accurately the cost of water from wells. The present study aimed to calculate the actual cost of water from underground resources for various uses and study the impact of electricity price subsidies liberalization on it. In addition, the impact of choosing engineering economics and accounting methodologies on actual cost outcomes was examined. This study was conducted in Kohgiluyeh and Boyer-Ahmad province, Iran, in 2019 with data obtained from information on the annual budgets of provincial water companies. The results indicated that the actual cost of water for agricultural, drinking, and industrial uses was 1613, 2555, and 4739 Rials/m3, respectively, calculated with engineering economics methods, and 877, 2111, and 2848 Rials/m3, respectively, calculated with accounting methodologies. Furthermore, costs were found to be far different from the current tariffs received for water. Liberalizing electricity price subsidies for agricultural uses and their calculation based on public electricity tariffs increased actual water costs by 63% and could reduce water use by about 21%. Therefore, it is suggested that a policy of gradually reducing electricity subsidies, along with price discrimination among various uses, be considered in order to provide consumers with an opportunity to reform and update water use technologies.

Optimal Electricity Price of TOU Demand Response Program for Distribution Grid Reliability Improvement

Nowadays, the power systems and distribution network’s reliability are critical issues from electric companies’ and consumers’ perspectives. As suppliers of the power required by the consumers, electric companies are trying to deliver the power to customers on a continuous and reliable basis. The existence of customers’ power interruptions causes damage to the customer; moreover, it may cause damage to the electric company due to the lack of energy sales during the hours of a power outage. In this paper, the reliability issue was investigated by examining the two indices EENS and ECOST, on the test distribution network to evaluate the impact of electricity prices in TOU demand response on the reliability of the distribution network has been investigated. Also find the optimal electricity prices for the best distribution network reliability. In this research, simulation studies were conducted on the Roy Billinton Test System (RBTS) distribution network using the GAMS software. From the analysis of the simulation results, the distribution grid reliability was improved by implementing optimal electricity prices of the TOU demand response program.

Modeling and evaluating the impact of electricity price on commute network flows of battery electric vehicles

ABSTRACT In many urban areas and urban-rural regions, the price of electricity is not only subject to time-of-use tariffs, but also dependent on the usage purpose or service sector, significantly varying across different geographic locations or land uses. Such a spatial price difference greatly affects the charging behavior of electric vehicle drivers. This paper models and analyzes the possible impact of electricity-charging price on the routing choice and flow pattern of electric vehicles in a home-workplace commute traffic network. The particular circumstance in such a network accommodating electric vehicles is that commuters driving battery electric vehicles have opportunities to charge their vehicles at both home and workplace and take into account different electricity-charging prices in their travel choices. For the illustration and evaluation purposes, we presented a small synthetic example and proposed a convex programming model for characterizing the commute network flow pattern of electric vehicles that may be charged at home and/or workplace, encapsulating a piecewise electricity-charging cost function that implies commuters’ combined home-based and workplace-based charging behaviors. Given different electricity-charging prices at home and workplace, solving this problem requires tracking all individual paths in the network. As such, a path-based solution algorithm sketched in the disaggregated simplicial decomposition framework, with some modifications in the path generation phase and an added k-shortest path search procedure, is designed for problem solutions. We implemented the modeling and solution methods for deriving the network flow pattern of electric vehicles and comparing it with that of gasoline vehicles, as well as evaluating the network performance change caused by varying electricity-charging prices with multiple network-level and link-level evaluation matrices.

The Impact of Electricity Price on Power-Generation Structure: Evidence From China

Being affected by a variety of factors, power-generation structure plays an essential role in a high-quality and sustainable development. The focus of this paper is to evaluate the influence of electricity price on it. First, we provide a microeconomic framework to understand the impact mechanism. We discuss two effects through which price level can affect power generation, and then the power-generation structure. After that, an empirical test is conducted using provincial panel data, and the results of it are robust. We also test the above-mentioned mechanism empirically. There are two main conclusions. First, the electricity price has a positive effect on the share of thermal power in electricity generation. Second, the mechanism test shows that an increase of electricity price can not only improve efficiency of power plants but also propel firms to invest in more renewable energy plants.

The impact of electricity prices and supply on attracting FDI to South Africa.

Inward Foreign Direct Investment (FDI) plays an important role on the overall economic conditions of host countries, particularly the ones that are still in low developmental stages. South Africa (SA) as an example of this group of countries has also experienced intermittent electricity supply and increasing electricity tariffs since 2008. As the literature suggests that attracting FDI depends on the conditions of the host country, the main purpose of this study is to examine the impact that electricity prices and supply, as representatives of the energy conditions of SA as a host country, had to the attractiveness of FDI to SA. To do so, this study uses the Autoregressive Distributed Lag (ARDL) cointegration approach for the period 1985 to 2018. The findings of the study indicated that indeed the initial hypotheses have been confirmed: (1) electricity supply is a positive contributor to inward FDI, ceteris paribus, and (2) electricity prices are a negative contributor to inward FDI, ceteris paribus.

Research on Revenue Maximizing Dispatch Strategy for New Energy Micro-grid

In this paper, a mathematical model for micro-grid energy management, including photovoltaic, wind power, micro gas turbine and energy storage devices, is established. On this basis, considering the impact of electricity price on user demand, this paper proposes a micro grid scheduling strategy based on revenue maximization.

Modeling and Evaluating the Impact of Electricity Price on Commute Network Flows of Battery Electric Vehicles

Modeling and Evaluating the Impact of Electricity Price on Commute Network Flows of Battery Electric Vehicles

Impact of electricity price forecasting errors on bidding: a price‐taker's perspective

Electricity price forecasting is very important for market participants in a deregulated market. However, only a few papers investigated the impact of forecasting errors on the market participants' behaviours and revenues. In this study, a general formulation of bidding in the electricity market is considered and the participant is assumed to be a price-taker which is general for most of the participants in power markets. A numerical method for quantifying the impact of forecasting errors on the bidding curves and revenues based on multiparametric linear programming is proposed. The forecasted prices are regarded as exogenous parameters for both deterministic and stochastic bidding models. Compared with the existing method, the proposed method can calculate how much improvement will be achieved in the cost or revenue of the bidder if he reduces the price forecasting error level, and such calculation does not require any predefined forecasting results. Numerical results and discussions based on real-market price data are conducted to show the application of the proposed method.

Generation Expansion Planning Considering the Output and Flexibility Requirement of Renewable Energy: The Case of Jiangsu Province

This study presents a generation expansion planning by incorporating the impacts of renewable energy on the generation mix. The wind-solar power output and its flexibility requirement are integrated into an optimization model to provide the realistic representation of wind and solar energy resources. The model is then used for the power system optimization planning of Jiangsu Province. A comparion of power demand, electricity price subsidies, and carbon emission intensity scenarios reveals the power planning scheme and optimization path for power system integrating increasing renewable energy. The results suggest that the installed capacity of renewable energy will increase from 21.6 GW to 133.2 GW in the baseline scenario during the planning period, with its share ranging from 17.9% to 53.7%. Solar photovoltaic power is expected to contribute 72% of renewable capacity and 39% of the total capacity by 2050. The impact of electricity price subsidies on solar PV generation expansion is particularly significant. Additionally, the flexibility requirement of power systems can basically be satisfied with the available generation technologies, however it would become severe if the flexibility requirement grows faster than the flexible generation.

전력가격이 부ㆍ울ㆍ경의 경제성장과 수출에 미치는 효과분석

본 연구는 전력가격이 부산, 울산, 경남의 동남권 지역의 지역내총생산과 수출에 미치는 영향을 분석하였다. 이를 위하여 2000년에서 2017년까지 연도별 그리고 16개 광역시도별 패널자료를 사용하여 시스템 GMM 모형으로 추정하였다. 실증분석의 결과, 첫째, 전력 가격이 동남권 지역내총생산에 미치는 효과는 일관되고, 강건한 추정치를 제시하지는 못 하였다. 다만, 전국자료를 이용한 모형에서는 전력가격이 동남권 GRDP에 부정적 영향을 미치며, 그 효과는 타 지역보다 큰 것으로 추정되었다. 둘째, 전력가격은 수출에 부정적 영향을 미치며 동시에 GRDP에 미치는 효과보다 훨씬 큰 것으로 나타났다. 셋째, 동남권 내에서 전력가격이 수출에 미치는 효과의 크기는 경남, 울산, 부산의 순으로 분석되었다. 이상의 결과에서 전력가격이 지역경제, 특히 수출에 미치는 영향이 대단히 큼을 알 수 있다. 따라서 정부의 에너지정책 수립과 집행에 있어서 지역경제에 미치는 영향은 반드시 고려되어야 할 것이다.