LCI Data Modelling and a Database Design

A large scale operative data format for transparent storage, administration and retrieval of environmental Life Cycle Inventory (LCI) data has been implemented by applying data modelling and database design. Key concepts in the design are ‘activity’ and flow’: An activity is a technical system, such as a process or a transport, or an aggregate of different processes or transports. A flow is any matter entering or leaving an activity, such as natural resources, energywarc, raw material, emission, waste or products. Any numerical data set on an activity can he thoroughly described by supplying meta data. Meta data fields are prepared for a wide set of commonly known LCA-data aspects, such as descriptions of data acquisition methods, system boundary conditions and relevant dates

A Congestion Forecast Framework for Distribution Systems with High Penetration of PV and PEVs

This paper presents a congestion forecast framework for electrical distribution systems with high penetration of solar photovoltaic and plug-in electric vehicles. The framework is based on probabilistic power flow to account for the uncertainties in photovoltaic production and load demand. The proposed framework has been implemented and tested using the data of the real distribution grid of Chalmers University of Technology campus. Cases studies have been carried out using the framework to analyse the impact of different local production levels and operating modes of solar photovoltaic inverter. The results have shown that cumulative probability for network congestion in branches and transformers would increase by 30% and 20% respectively, when the level of local PV generation, demand and PEVs demand to increase by 100%, 95% and 100% respectively. Also, results have shown that network congestion in branches and transformers is 4% and 8% respectively, more likely to occur in the constant-V mode as compared to constant-pf mode. These results can help distribution system operators to predict any upcoming congestion in their system and subsequently help them in taking suitable actions in order to mitigate congestion

Energy Scheduling Strategies for Grid-connected Microgrids: A Case Study on Chalmers Campus

This paper focuses on the optimal energy managementof grid-connected microgrids with battery energy storagesystems. The microgrid energy management and the optimalpower flow of the distribution network are formulated as mixed-integerlinear optimization problems to evaluate microgrid energyscheduling strategies including cost minimization, maximum useof own resources, and minimum energy exchange with theupstream network. The real distribution network of ChalmersUniversity of Technology campus is used as a case study. Thestudy results show that economic optimization yields an annualmicrogrid cost reduction of 4%. Alternatively, if the microgridminimizes the energy exchange, virtual islanding operation (zeroenergy exchange) for 3211 hours can be achieved within a year.The results also present the effects on the operation and costof the distribution system and highlight a trade-off betweenmicrogrid cost minimization and battery lifetime

Key Drivers and Future Scenarios of Local Energy and Flexibility Markets

This paper explores the key drivers of local energy and flexibility markets, develops a set of plausible future scenarios for these markets, and analyzes the scenarios\u27 impact. The results can provide insight to policymakers, researchers, system operators, and aggregators in a better design and more successful implementation of local markets. This study is based on the well-established scenario planning technique of "intuitive logics"and it is conducted by means of qualitative methods, surveys, and cross-impact analysis. Results explore and rank the impact and uncertainty of 20 key factors and trends which can affect the future of local energy and flexibility markets. The results show that factors related to the availability of active and smart end-users, and regulatory incentives are the most impactful and uncertain ones in the future of local markets. Four future scenarios are introduced based on these factors and their impacts are discussed

Transmission Line Protection Using Dynamic State Estimation and Advanced Sensors: Experimental Validation

This paper presents the experimental validation of a protection scheme for a transmission line based on dynamic state estimation along with the practical application of advanced sensors in this protection scheme. The scheme performs dynamic state estimation with high-frequency measurements provided by the sensors, assesses the operating condition (i.e., health) of the transmission line in real-time, and thereby determines the tripping signal whenever a fault is detected. The validation was carried out in two steps, first with simulation studies for a three-phase fault and then with the experimental implementation using a physical scaled-down model of a power system consisting of transmission lines, transformers, and loads. The simulation and validation results have shown that the scheme performs adequately in both normal and fault conditions. In the fault case with the experimental setup, the scheme could correctly detect the fault and send the trip signal to the line’s circuit breakers with a total fault clearing time of approximately 65 milliseconds which is comparable to conventional protection methods. The average processing time for a measurement sample block is 12.5 milliseconds. The results demonstrate that this scheme and the sensors would work for transmission line protection which can avoid relay coordination and settings issues

A Review on Challenges and Solutions in Microgrid Protection

Protection of microgrid has become challenging due to the hosting of various actors such as distributed generation, energy storage systems, information and communication technologies, etc. The main protection challenges in the microgrid are the bi-directional power flow, protection blinding, sympathetic tripping, change in short-circuit level due to different modes of operation, and limited fault current contribution by converter-interfaced sources. This paper presents a comprehensive review of the available microgrid protection schemes which are based on traditional protection principles and emerging techniques such as machine learning, data-mining, wavelet transform, etc. A categorical assessment of the reviewed protection schemes is also presented. The key findings of the paper suggest that the time-domain and communication-assisted protection schemes could be suitable solutions to address the identified protection challenges in the microgrid

Dynamic State Estimation based Transmission Line Protection Scheme: Performance Evaluation with Different Fault Types and Conditions

This paper presents the experimental validation of a transmission line protection scheme based on dynamic state estimation for different fault types and conditions. The protection scheme utilizes real-time high-frequency sampled measurements from advanced sensors and evaluates the operating condition of the transmission line based on which a tripping signal is generated in case a fault occurs. The validation is performed using a physical scaled-down model of a power system, consisting of a transmission line, transformer, synchronous generator, and loads. The following faults are examined during the validation: unbalanced faults under different load conditions, high impedance fault, fault current fed from both ends, hidden failure, external fault, and load change conditions. The results show that the scheme performs as intended and thus proves its efficacy to detect various types of faults. The maximum fault detection time is calculated to be 42.5 milliseconds, while the maximum fault clearing time comes out to be 82.5 milliseconds, on par with currently employed protection methods. The obtained results demonstrate the ability of the scheme to detect different fault types under varying conditions and avoid potential issues with relay coordinatio

Market-based Energy Management Model of a Building Microgrid Considering Battery Degradation

This paper presents a model for energy management system of a building microgrid coupled with a battery energy storage. The model can be used to dispatch the battery as a flexible energy resource using a market-based setting. The battery is modeled considering battery degradation and real-life operation characteristics derived from measurements at a residential building. The performance of the model was evaluated first with simulations and integrated afterwards to an energy management system, which was demonstrated at a real residential building (HSB Living Lab) equipped with photovoltaic and battery storage systems. The simulation results showed that the building owner, and subsequently the residents, could benefit from the proposed model in reduced annual cost up to 3.1% under the considered pricing scheme. The demonstration results showed that dispatch under the measurement-based model could decrease the undelivered energy over the daily requested amount from the battery from 13.3% to 3.7%. Thus, the proposed model, which couples the measurement-based dispatch with battery degradation, can lead to a more accurate estimation of the building operation cost and an improved overall performance of battery as a flexible resource in building microgrids

Scenario-based Stochastic Optimization for Energy and Flexibility Dispatch of a Microgrid

Energy storage is one of the most important components of microgrids with non-dispatchable generators and can offer both energy and flexibility services when the microgrid operates in grid-connected mode. This paper proposes a scenario-based stochastic optimization model that can be used to determine the energy and flexibility dispatch of a residential microgrid with solar and stationary battery systems. The objective of the model is to minimize the expected energy and peak power cost as well as the battery aging cost, while maximizing the expected revenue from flexibility. The formulated stochastic optimization problem is solved in rolling horizon with the uncertainty model being dynamically updated to consider the most recent forecast profiles for solar power and electricity demand. The benefits of the proposed approach were demonstrated by simulating the daily operation of a real building. The results showed that the estimated flexibility was successfully dispatched yielding an economic value of at least 7% of the operation cost of the building microgrid. The model can be used by flexibility providers to assess their flexibility and design a bidding strategy as well as by system operators to design incentives for flexibility providers