Evaluation of Energy Market Platforms Potential in Microgrids: Scenario Analysis Based on a Double-Sided Auction

Local energy markets represent a mean for distributed energy resources trading for prosumers and energy management for utilities. In these markets, prosumers either trade or shift their loads to maximize their trading gains via communicating with an energy market platform. The utility considers the trading process as an approach to maximize the autonomy and minimize the peak loads. The benefits of the prosumer and utility can vary depending on several parameters such as the market rules, microgrid configurations, or the lifestyle and social behavior of the market participants. In this paper, selected scenarios are presented that discuss and analyze the major factors influencing the market dynamics and microgrid energy balance based on a forward double-sided auction market model simulation. These scenarios are divided into three scenario groups that consider market design parameters, microgrid configurations, and user behavior. Furthermore, the same scenarios are once more evaluated using a reference model, where no market platform is integrated, so that the results of the energy market can be compared. The results are analyzed based on multiple metrics from the perspective of the prosumer and utility to quantify and compare the benefits of the two major market players

Experimental Assessment of Energy Performance and Emissions of a Residential Microcogenerator

Microcogeneration can guarantee sensible primary energy savings and greenhouse gas emissions reductions in the residential sector. In this paper, the results of experimental tests carried out on a microcogenerator (5.5 kW electric power and 14.8 kW thermal power) based on a natural gas fuelled internal combustion engine, integrated with a condensing boiler, have been analyzed. Tests have been performed out at Institute for Energy Economy and Application Technology (IfE) of Technical University of Munich (Germany). The test facility allowed to simulate the thermal energy requirements of a real residential application, represented by a Multi Family House consisting of 10 apartments, and to evaluate the energy flows of the conversion devices in actual operating conditions. Four type days, characteristic of Mediterranean climatic conditions, have been used to define space heating and domestic hot water user’s requirements. Experimental tests have been performed to implement energy and environmental analysis, comparing the system consisting of cogenerator and integration boiler with a reference system. Results showed that the former can achieve a primary energy saving of about 6%, and CO2 equivalent emissions reduction of about 12%. Finally, the algorithm defined by the European Directive on the promotion of high efficiency cogeneration has been implemented; it demonstrated that the primary energy saving is well above the limit value prescribed by the Directive. Therefore the cogeneration plant can access support mechanisms that can help to achieve the economic feasibility of the system, besides energy and environmental benefits

Is Bitcoin the Only Problem? A Scenario Model for the Power Demand of Blockchains

When an author under the pseudonym Satoshi Nakamoto published the paper “Bitcoin: A Peer-to-Peer Electronic Cash System” in 2008, the first cryptocurrency using the new blockchain technology was introduced. Over the last decade, more than 1,000 different cryptocurrencies, such as Ethereum, Ripple, and Litecoin were developed and Bitcoin's currency had almost reached an equivalent value of 20,000 $/BTC. After recognizing the disrupting momentum that the blockchain technology generated, scientists started to develop blockchain use cases for the energy sector. However, the scientific literature so far offers only rough and incomplete estimations when questions about the current and future energy consumption of the Bitcoin network are raised. This paper introduces a new scenario model to estimate the mining power demand of the Bitcoin and Ethereum network. Six scenarios are developed on the basis of mining hardware efficiency and network parameter data. The results show that an increase of the mining hardware efficiency will only have a limited impact on the overall power demand of blockchain networks. Furthermore, the current power demand of the Ethereum network is in the range from 0.6 to 3 GW and therefore, is similar to the one of Bitcoin. In case of linear growth of the block difficulty and sigmoidal increase of the hardware efficiency until the year of 2025, the mining power demand for the Bitcoin blockchain will be approximately 8 GW. Furthermore, the model and the scenarios are adaptable to other cryptocurrencies that use the proof-of-work consensus algorithm to create scenarios for their future power demand

Evaluation of Hierarchical, Multi-Agent, Community-Based, Local Energy Markets Based on Key Performance Indicators

In recent years, local energy markets (LEMs) have been introduced to empower end-customers within energy communities at the distribution level of the power system, in order to be able to trade their energy locally in a competitive and fair environment. However, there is still some challenge with regard to the most efficient approach in organising the LEMs for the electricity exchange between consumers and prosumers while ensuring that they are responsible for their electricity-related choices, and concerning which LEM model is suitable for which prosumer or consumer type. This paper presents a hierarchical model for the organisation of agent-based local energy markets. According to the proposed model, prosumers and consumers are enabled to transact electricity within the local energy community and with the grid in a coordinated manner to ensure technical and economic benefits for the LEM’s agents. The model is implemented in a software tool called Grid Singularity Exchange (GSyE), and it is verified in a real German energy community case study. The simulation results demonstrate that trading electricity within the LEM offers economic and technical benefits compared to transacting with the up-stream grid. This can further lead to the decarbonization of the power system sector. Furthermore, we propose two models for LEMs consisting of multi-layer and single-layer hierarchical agent-based structures. According to our study, the multi-layer hierarchical model is more profitable for household prosumers as compared to trading within the single-layer hierarchical LEM. However, the single-layer LEM is more be beneficial for industrial prosumers.© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).fi=vertaisarvioitu|en=peerReviewed

Experimental Study and Modeling of Ground-Source Heat Pumps with Combi-Storage in Buildings

There is a continuous growth of heat pump installations in residential buildings in Germany. The heat pumps are not only used for space heating and domestic hot water consumption but also to offer flexibility to the grid. The high coefficient of performance and the low cost of heat storages made the heat pumps one of the optimal candidates for the power to heat applications. Thus, several questions are raised about the optimal integration and control of heat pump system with buffer storages to maximize its operation efficiency and minimize the operation costs. In this paper, an experimental investigation is performed to study the performance of a ground source heat pump (GSHP) with a combi-storage under several configurations and control factors. The experiments were performed on an innovative modular testbed that is capable of emulating a ground source to provide the heat pump with different temperature levels at different times of the day. Moreover, it can emulate the different building loads such as the space heating load and the domestic hot water consumption in real-time. The data gathered from the testbed and different experimental studies were used to develop a simulation model based on Modelica that can accurately simulate the dynamics of a GSHP in a building. The model was validated based on different metrics. Energetically, the difference between the developed model and the measured values was only 3% and 4% for the heat generation and electricity consumption, respectively

Survey and Analysis of Local Energy Markets Based on Distributed Ledger Technologies

Local energy markets (LEMs) provide opportunity to handle the challenges arising from the lower grid level while using the traditional top-down approach to manage distributed generated renewable energy resources. Blockchain-based local energy markets (LEMs) have been introduced in recent years as a way to enable local consumers/prosumers to trade their energy locally in a distributed and highly secured manner in an LEM. However, there are still some challenges regarding the main factors that can drive local consumers/prosumers to participate in a blockchain-based LEM, optimal community size, and prosumer to consumer ratio for an efficient LEM. Also, there is still no information on how the quantifying factors for participation on a blockchain-based LEM can affect the performance of an LEM. This paper presents a survey and simulation based analysis of quantifying factors for participation in a blockchain-based LEM. The survey was distributed among local consumers/prosumers and a total of 261 responses were received from the responders. The results from the responders were analyzed using a Python code based statistical analysis model. The simulation based analysis was conducted using a community based LEM model and evaluated using data received from a combination of German household profiles and standard load profiles. The survey results showed that the major drive for local consumers/prosumers to participate on blockchain-based LEM is their willingness to support renewable energy integration, transparency, and trust offered by a blockchain network. On the other hand, the simulation based analysis showed that small and medium communities with prosumers to consumer ratios between 0.3 to 0.5 create more economic and technical benefits for local consumers/prosumers compared to large communities. The community based simulation results were modelled together with the survey results to determine how the individual quantifying factors for participating in a blockchain-based LEM can affect the performance of an LEM

Flexibility Estimation of Residential Heat Pumps under Heat Demand Uncertainty

With the increasing penetration of intermittent renewable energy generation, there is a growing demand to use the inherent flexibility within buildings to absorb renewable related disruptions. Heat pumps play a particularly important role, as they account for a high share of electricity consumption in residential units. The most common way of quantifying the flexibility is by considering the response of the building or the household appliances to external penalty signals. However, this approach neither accounts for the use cases of flexibility trading nor considers its impact on the prosumer comfort, when the heat pump should cover the stochastic domestic hot water (DHW) consumption. Therefore, in this paper, a new approach to quantifying the flexibility potential of residential heat pumps is proposed. This methodology enables the prosumers themselves to generate and submit the operating plan of the heat pump to the system operator and trade the alternative operating plans of the heat pump on the flexibility market. In addition, the impact of the flexibility provision on the prosumer comfort is investigated by calculating the warm water temperature drops in the thermal energy storage given heat demand forecast errors. The results show that the approach with constant capacity reservation in the thermal energy storage provides the best solution, with an average of 2.5 min unsatisfactory time per day and a maximum temperature drop of 2.3 °C

High-resolution dataset for building energy management systems applications

Modelling and optimization of energy management systems (EMS) require different data types for operation and validation. In this article, a multi-purpose dataset is provided for EMS applications. It includes PV measurement data for the PV generation and prediction algorithms associated with EMS systems. Weather data has also been measured at the same location for the optimization of PV prediction algorithms and other applications such as building model simulations. Moreover, the dataset contains detailed measurements of a seminar room where not only temperatures have been measured, but also user feedback for comfort assessment. All documented measurements have been gathered at the same location in Munich, Germany

Hardware in the Loop Real-Time Simulation for Heating Systems: Model Validation and Dynamics Analysis

Heating systems such as heat pumps and combined heat and power cycle systems (CHP) represent a key component in the future smart grid. Their capability to couple the electricity and heat sector promises a massive contribution to the energy transition. Hence, these systems are continuously studied numerically and experimentally to quantify their potential and develop optimal control methods. Although numerical simulations provide time and cost-effective solutions for system development and optimization, they are exposed to several uncertainties. Hardware in the loop (HiL) approaches enable system validation and evaluation under different real-life dynamic constraints and boundary conditions. In this paper, a HiL system of a heat pump testbed is presented. It is used to present two case studies. In the first case, the conventional heat pump testbed operation method is compared to the HiL operation method. Energetic and dynamic analyses are performed to quantify the added value of the HiL and its necessity for dynamics analysis. In the second case, the HiL testbed is used to validate a model of a single family house with a heat pump participating in a local energy market. The energetic analysis indicates a deviation of 2% and 5% for heat generation and electricity consumption of the heat pump model, respectively. The model dynamics emphasized its capability to present the dynamics of a real system with a temporal distortion of 3%