scholarly journals Aggregation of Households in Community Energy Systems: An Analysis from Actors’ and Market Perspectives

Energies ◽  
2020 ◽  
Vol 13 (19) ◽  
pp. 5154
Author(s):  
Seyedfarzad Sarfarazi ◽  
Marc Deissenroth-Uhrig ◽  
Valentin Bertsch
Keyword(s):  
Real Time ◽  
Electricity Market ◽  
Business Models ◽  
Stackelberg Game ◽  
Energy Systems ◽  
Energy System ◽  
Theoretic Approach ◽  
Real Time Pricing ◽  
Tariff Structure ◽  
The Impact

In decentralized energy systems, electricity generated and flexibility offered by households can be organized in the form of community energy systems. Business models, which enable this aggregation at the community level, will impact on the involved actors and the electricity market. For the case of Germany, in this paper different aggregation scenarios are analyzed from the perspective of actors and the market. The main components in these scenarios are the Community Energy Storage (CES) technology, the electricity tariff structure, and the aggregation goal. For this evaluation, a bottom-up community energy system model is presented, in which the households and retailer are the key actors. In our model, we distinguish between the households with inflexible electricity load and the flexible households that own a heat pump or Photovoltaic (PV) storage systems. By using a game-theoretic approach and modeling the interaction between the retailer and households as a Stackelberg game, a community real-time pricing structure is derived. To find the solution of the modeled Stackelberg game, a genetic algorithm is implemented. To analyze the impact of the aggregation scenarios on the electricity market, a “Market Alignment Indicator” is proposed. The results show that under the considered regulatory framework, the deployment of a CES can increase the retailer’s operational profits while improving the alignment of the community energy system with the signals from the electricity market. Depending on the aggregation goal of the retailer, the implementation of community real-time pricing could lead to a similar impact. Moreover, such a tariff structure can lead to financial benefits for flexible households.

scholarly journals Real-Time Pricing Scheme in Smart Grid Considering Time Preference: Game Theoretic Approach

Energies ◽  
2020 ◽  
Vol 13 (22) ◽  
pp. 6138
Author(s):  
Ri Piao ◽  
Deok-Joo Lee ◽  
Taegu Kim
Keyword(s):  
Smart Grid ◽  
Real Time ◽  
Time Preference ◽  
Stackelberg Game ◽  
Price Policy ◽  
Theoretic Approach ◽  
Time Zone ◽  
Efficient Operation ◽  
Game Theoretic ◽  
Real Time Pricing

Unbalanced power demand across time slots causes overload in a specific time zone. Various studies have proved that this can be mitigated through smart grid and price policy, but research on time preference is insufficient. This study proposed a real-time pricing model on a smart grid through a two-stage Stackelberg game model based on a utility function that reflects the user’s time preference. In the first step, the suppliers determine the profit-maximizing price, and then, the users decide the electricity usage schedule according to the given price. Nash equilibrium and comparative analysis of the proposed game explain the relationship between time preference, price, and usage. Additionally, a Monte Carlo simulation demonstrated the effect of the change in time preference distribution. The experimental results confirmed that the proposed real-time pricing method lowers peak-to-average ratio (PAR) and increases overall social welfare. This study is meaningful in that it presents a pricing method that considers both users’ and suppliers’ strategies with time preference. It is expected that the proposed method would contribute to a reduction in the need for additional power generation facilities through efficient operation of the smart grid.

scholarly journals A Real-Time Pricing Scheme for Energy Management in Integrated Energy Systems: A Stackelberg Game Approach

Energies ◽  
2018 ◽  
Vol 11 (10) ◽  
pp. 2858 ◽  
Author(s):  
Tengfei Ma ◽  
Junyong Wu ◽  
Liangliang Hao ◽  
Huaguang Yan ◽  
Dezhi Li
Keyword(s):  
Real Time ◽  
Stackelberg Game ◽  
Supply And Demand ◽  
Energy System ◽  
Stackelberg Equilibrium ◽  
Energy Hub ◽  
Pricing Scheme ◽  
Real Time Pricing ◽  
Aggregated Load ◽  
Energy Provider

This paper proposes a real-time pricing scheme for the demand response management between one energy provider and multiple energy hub operators. A promising energy trading scenario has been designed for the near future integrated energy system. The Stackelberg game approach was employed to capture the interactions between the energy provider (leader) and energy consumers (follower). A distributed algorithm was proposed to derive the Stackelberg equilibrium, then, the best strategies for the energy provider and each energy hub operator were explored in order to maximize their benefits. Simulation results showed that the proposed method can balance the energy supply and demand, improve the payoffs for all players, as well as smooth the aggregated load profiles of all energy consumers.

scholarly journals A Hybrid Energy System Workflow for Energy Portfolio Optimization

Energies ◽  
2021 ◽  
Vol 14 (15) ◽  
pp. 4392
Author(s):  
Jia Zhou ◽  
Hany Abdel-Khalik ◽  
Paul Talbot ◽  
Cristian Rabiti
Keyword(s):  
Time Series ◽  
Gaussian Process ◽  
Electricity Market ◽  
Process Model ◽  
Net Present Value ◽  
Historical Data ◽  
Energy System ◽  
Initial Guess ◽  
Reduced Order ◽  
The Impact

This manuscript develops a workflow, driven by data analytics algorithms, to support the optimization of the economic performance of an Integrated Energy System. The goal is to determine the optimum mix of capacities from a set of different energy producers (e.g., nuclear, gas, wind and solar). A stochastic-based optimizer is employed, based on Gaussian Process Modeling, which requires numerous samples for its training. Each sample represents a time series describing the demand, load, or other operational and economic profiles for various types of energy producers. These samples are synthetically generated using a reduced order modeling algorithm that reads a limited set of historical data, such as demand and load data from past years. Numerous data analysis methods are employed to construct the reduced order models, including, for example, the Auto Regressive Moving Average, Fourier series decomposition, and the peak detection algorithm. All these algorithms are designed to detrend the data and extract features that can be employed to generate synthetic time histories that preserve the statistical properties of the original limited historical data. The optimization cost function is based on an economic model that assesses the effective cost of energy based on two figures of merit: the specific cash flow stream for each energy producer and the total Net Present Value. An initial guess for the optimal capacities is obtained using the screening curve method. The results of the Gaussian Process model-based optimization are assessed using an exhaustive Monte Carlo search, with the results indicating reasonable optimization results. The workflow has been implemented inside the Idaho National Laboratory’s Risk Analysis and Virtual Environment (RAVEN) framework. The main contribution of this study addresses several challenges in the current optimization methods of the energy portfolios in IES: First, the feasibility of generating the synthetic time series of the periodic peak data; Second, the computational burden of the conventional stochastic optimization of the energy portfolio, associated with the need for repeated executions of system models; Third, the inadequacies of previous studies in terms of the comparisons of the impact of the economic parameters. The proposed workflow can provide a scientifically defendable strategy to support decision-making in the electricity market and to help energy distributors develop a better understanding of the performance of integrated energy systems.

scholarly journals The Climate Action Simulation

2019 ◽  
Vol 51 (2) ◽  
pp. 114-140 ◽  
Author(s):  
Juliette N. Rooney-Varga ◽  
Florian Kapmeier ◽  
John D. Sterman ◽  
Andrew P. Jones ◽  
Michele Putko ◽  
...  
Keyword(s):  
Climate Change ◽  
Focus Group ◽  
Energy Systems ◽  
Role Playing ◽  
Energy System ◽  
Initial Evaluation ◽  
Emotional Engagement ◽  
Action Simulation ◽  
Climate Action ◽  
The Impact

Background. We describe and provide an initial evaluation of the Climate Action Simulation, a simulation-based role-playing game that enables participants to learn for themselves about the response of the climate-energy system to potential policies and actions. Participants gain an understanding of the scale and urgency of climate action, the impact of different policies and actions, and the dynamics and interactions of different policy choices. Intervention. The Climate Action Simulation combines an interactive computer model, En-ROADS, with a role-play in which participants make decisions about energy and climate policy. They learn about the dynamics of the climate and energy systems as they discover how En-ROADS responds to their own climate-energy decisions. Methods. We evaluated learning outcomes from the Climate Action Simulation using pre- and post-simulation surveys as well as a focus group. Results. Analysis of survey results showed that the Climate Action Simulation increases participants’ knowledge about the scale of emissions reductions and policies and actions needed to address climate change. Their personal and emotional engagement with climate change also grew. Focus group participants were overwhelmingly positive about the Climate Action Simulation, saying it left them feeling empowered to make a positive difference in addressing the climate challenge. Discussion and Conclusions. Initial evaluation results indicate that the Climate Action Simulation offers an engaging experience that delivers gains in knowledge about the climate and energy systems, while also opening affective and social learning pathways.

Real-time pricing scheme based on Stackelberg game in smart grid with multiple power retailers

2017 ◽  
Vol 260 ◽  
pp. 149-156 ◽  
Author(s):  
Yeming Dai ◽  
Yan Gao ◽  
Hongwei Gao ◽  
Hongbo Zhu
Keyword(s):  
Smart Grid ◽  
Real Time ◽  
Stackelberg Game ◽  
Pricing Scheme ◽  
Multiple Power ◽  
Real Time Pricing

Transient Simulations for Economical Analysis of Energy Systems in Industry and Buildings

2007 ◽  
Author(s):  
Stefan Wischhusen ◽  
Gerhard Schmitz
Keyword(s):  
Reference Model ◽  
Measurement Data ◽  
Energy Systems ◽  
Energy System ◽  
Hot Water ◽  
Industrial Facilities ◽  
Water Storage Tank ◽  
Economical Analysis ◽  
Heating And Cooling ◽  
The Impact

In this paper, criteria which indicate the usage of transient models and dynamic simulation environments for such energy systems are presented. A complex energy system for heating and cooling of industrial facilities and industrial processes is presented as a reference model. A model of a hot water storage tank is presented, which is optimized for the simulation in whole years, in which a very accurate transient response at much quicker simulation times compared to conventional geometric models can be delivered. The model was validated with measurement data from a large cogeneration plant. In addition, the economical impact of system simulation is emphasized on by an optimization study carried out on a large industrial system. Furthermore, the impact of a transient system model is compared to that of a steady state approach of the same system.

The Bioceanic Amazon Corridors: An Opportunity for Development of Sustainable Energy System

2004 ◽  
Author(s):  
Pedro Mendoza G. ◽  
Maximiliano Arroyo Ulloa ◽  
Vincenzo Naso
Keyword(s):  
Alternative Energy ◽  
Energy Systems ◽  
Energy System ◽  
Renewable Sources ◽  
Energy Technologies ◽  
Local Resources ◽  
Decentralized Energy ◽  
Sustainable Energy System ◽  
The Impact ◽  
Principal Energy

The bioceanic Amazon corridor represents a development opportunity for the Peruvian and Brazilian economy but this economic evolution is linked to the production and use of energy. Energy is a conditioning factor of economic growth and development and the application of conventional (or alternative) energy systems is strongly influenced by both quantitative and qualitative trends in energy consumption. Decentralized production of energy is necessary, and new decentralized energy technologies based on renewable sources could provide additional income opportunities, decreasing environmental risk along Amazon corridor, and providing clean fuel and electricity. It’s necessary that the bioceanic Amazon corridors call for the application of energy systems related to the renewable local resources in coast, mountain and forest. In Peru, firewood is the principal energy source for cooking and heating and this fuel is used in inefficient combustion system that increases the impact on ecosystems. Typical Peruvian biomass source are wood, agricultural residues, agro industrial waste and municipal solid waste. The most obvious it’s the availability of agricultural and agro industrial residues that could be used as a biomass fuel source in modern plant to produce electricity. Today, there is a growing interest for ethanol production from sugar cane, but it couldn’t be applied along bioceanic corridors; therefore it is necessary to integrate other renewable sources.

scholarly journals District Cooling Versus Individual Cooling in Urban Energy Systems: The Impact of District Energy Share in Cities on the Optimal Storage Sizing

Energies ◽  
2019 ◽  
Vol 12 (3) ◽  
pp. 407 ◽  
Author(s):  
Dominik Dominković ◽  
Goran Krajačić
Keyword(s):  
Energy Supply ◽  
Energy Systems ◽  
Energy System ◽  
Integrated Modelling ◽  
Economic Costs ◽  
Battery Storage ◽  
Spatial Constraints ◽  
District Energy ◽  
Urban Energy ◽  
The Impact

The energy transition of future urban energy systems is still the subject of an ongoing debate. District energy supply can play an important role in reducing the total socio-economic costs of energy systems and primary energy supply. Although lots of research was done on integrated modelling including district heating, there is a lack of research on integrated energy modelling including district cooling. This paper addressed the latter gap using linear continuous optimization model of the whole energy system, using Singapore for a case study. Results showed that optimal district cooling share was 30% of the total cooling energy demand for both developed scenarios, one that took into account spatial constraints for photovoltaics installation and the other one that did not. In the scenario that took into account existing spatial constraints for installations, optimal capacities of methane and thermal energy storage types were much larger than capacities of grid battery storage, battery storage in vehicles and hydrogen storage. Grid battery storage correlated with photovoltaics capacity installed in the energy system. Furthermore, it was shown that successful representation of long-term storage solutions in urban energy models reduced the total socio-economic costs of the energy system for 4.1%.

The scalability challenge: pathways to future decarbonisation and the impact on the oil and gas industry

2020 ◽  
Vol 60 (2) ◽  
pp. 548
Author(s):  
Gavin Thompson
Keyword(s):  
Business Models ◽  
Oil And Gas ◽  
Energy Transition ◽  
Oil And Gas Industry ◽  
Energy System ◽  
Paris Agreement ◽  
Gas Industry ◽  
Alternative Technologies ◽  
Multiple Challenges ◽  
The Impact

How will the global energy system move sharply towards a pathway compatible with the goals of the Paris Agreement by 2030? Despite great efforts on cost reductions in renewables, alternative technologies, advanced transportation and supportive government policies, progress to date is not enough. The challenge is now one of scalability. Although some technologies required for a 2°C future are economic and proven, many others are not. Optimists look at the cost of solar and wind and say we have all we need to achieve our targets. The reality is that significant additional investment is needed to get them to material scale, globally. And too often huge challenges are downplayed in sectors beyond power and transport, including industry, aviation, shipping, heating and agriculture. Given the criticality of climate change, these multiple challenges must now be addressed. Consequently, any accelerated pace of decarbonisation represents an existential challenge to the oil and gas industry, including in Australia. If companies are to remain investible through the long term, all will need to transition to business models that are aligned with the goals of the Paris Agreement. This paper considers what the path to decarbonisation could look like and how oil and gas companies must respond in order to prosper through the energy transition.

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