Merkebu Degefa

Utilization Improvement of Transformers Using Demand Response

Due to load growth, aging infrastructure, and a competitive environment, innovative solutions are required by electrical utilities to enhance the utilization of transformers which are cost intensive. This paper proposes a demand response optimization model based on transformer hottest-spot temperature. The optimization model quantifies the improvement of transformer utilization through DR. The proposed model is applied to a typical Finnish residential primary and secondary distribution transformers for case studies of load with and without DR. The results show that the loading on the transformers can be significantly increased without sacrificing the life of transformers. The gain in utilization depends on the DR capability of the load. Significant monetary benefits can be achieved with the deployment of the proposed model in a real system.

Increased Utilization of Wind Generation by Coordinating the Demand Response and Real-time Thermal Rating

Demand response (DR) will play an essential role in smart grids by contributing to the operational flexibility requirement arising from the increased penetration of intermittent renewable generation. However, DR activation could be hampered in the absence of intelligent network management. Real-time thermal rating (RTTR) functions as a smart network management tool for unlocking the network capacities by allowing the network to safely operate during overload states. This paper offers an optimal residential DR approach integrated with RTTR to balance the hourly wind power production. The proposed framework is modeled from the perspective of an electrical aggregator that manages the population of heating, ventilation and air-conditioning (HVAC) loads for wind power balancing considering the RTTR of a distribution network. The model schedules the HVAC loads without deterioration of the customers temperature preferences. To demonstrate the performance of the proposed approach, simulations are performed on a typical Finnish distribution network plan. The results demonstrate the considerable benefits that can be realized by coordinating the DR and RTTR in a distribution network for wind generation balancing.

Benefits of Real-Time Monitoring to Distribution Systems: Dynamic Thermal Rating

With anticipated proliferation of electric vehicles and distributed generations in near future, dynamic thermal rating (DTR) as a tool for unlocking network capacities, is becoming critical for distribution network operators. DTR is gaining a great and still growing focus of attention in todays power industries. However, potential benefits of DTR, although have been envisioned to be significant, have not yet been studied quantitatively. This paper intends to comprehensively assess the potential impacts of DTR on the performance of a realistic Finnish distribution network. For doing so, first a step-by-step procedure is devised. Then, weather data and loading information of circuits in the network are gathered by advanced metering infrastructure available in the network. Thereafter, the gathered data are fed to mathematical models provided by the IEEE Standard 738-2006 and component dynamic thermal models to give thermal rating of circuits. The ratings are then used in reliability analysis where likely system states are simulated. This paper is performed for several cases and the results are discussed.

Demand Response for Operational Life Extension and Efficient Capacity Utilization of Power Transformers During Contingencies

Severe overloads, caused by the outage of units in multi-transformer substations, may affect transformer life adversely. This paper presents a novel demand response (DR) based optimization model to limit load on healthy transformers during contingencies. The model selects combination of the best remedial actions among DR, load curtailment (LC) and transferring load to a neighboring substation. IEEE standard thermal and aging models are used for transformer loss-of-life (LOL) calculation. For a realistic study, the proposed model is applied to a Finnish residential two-transformer primary substation for case studies of load with and without DR. The load profile and flexibility of the demand are estimated by hourly metered consumption and survey data. Simulations are performed for two situations depending upon availability of connection with a neighboring substation. The results show that the LOL of transformers can be reduced by employing DR following contingency events and the capacity utilization can be increased correspondingly.

Influence of energy demand response actions on thermal comfort and energy cost in electrically heated residential houses

This study has two aims to investigate the energy demand response (DR) actions on thermal comfort and energy cost in detached residential houses (1960, 2010 and passive) in a cold climate. The first one is to find out the acceptable range of indoor air and operative temperatures complying with the recommended thermal comfort categories in accordance with the EN 15251 standard. The second one is to minimize the energy cost of electric heating system by means of the DR control strategy, without sacrificing thermal comfort of the occupants. This research was carried out with the validated dynamic building simulation tool IDA Indoor Climate and Energy. Three different control strategies were studied: A) a strategy based on real-time hourly electricity price, B) new DR control strategy based on previous hourly electricity prices and C) new predictive DR control strategy based on future hourly electricity prices. The results show that the lowest acceptable indoor air and operative temperatures can be reduced to 19.4℃ and 19.6℃, respectively. The maximum annual saving in total energy cost is about 10% by using the control algorithm C.

Comparison of Air-Gap Thermal Models for MV Power Cables Inside Unfilled Conduit

This paper studies the effects of natural convection on longitudinal heat transfer and on the air-gap thermal resistance of cables inside conduit installations. Oversimplification of the physical placement of cables inside unfilled conduits is the main shortcoming in currently available thermal models. The study closely investigates the share of each heat-transfer mechanism and the effect of the natural placement of trefoil cables inside the conduit. Measurements from various installation setups are investigated for their impact on heat transfer. The installation-dependent convection correlations adopted in this study have broader applications for the dynamic thermal rating of underground cables inside conduit, troughs, and tunnels. Laboratory measurements are compared with numerical solutions from the IEC 60287 standards, Electra 143 methods, and FEA simulations.

MAS-Based Modeling of Active Distribution Network: The Simulation of Emerging Behaviors

Agent-based modeling of active distribution network helps to understand the dynamics and to design the control strategies for overall system efficiency. There is, however, a lack of generic and multipurpose agent definitions in existing studies. In this paper, a multi-agent system-based modeling of an active distribution network is presented using cooperative agents. A method to solve a network-wise objective of state estimation is explained with the proposed model. The network component agents are defined to be cooperative to meet the overall objectives and greedy to fulfil individual objectives such as energy cost minimization. A token-ring protocol is deployed for the agent communication among themselves, as well as with market and network operator agents. Furthermore, a MATLAB/Simulink model of active distribution network is used to simulate the emerging stochastic loading scenario, while the autonomous prosumer agents optimize their total energy cost responding to market price variations.

Dynamic Thermal Modeling of MV/LV Prefabricated Substations

With the expansion and infilling of urban areas, the demand for electric power is driving the design and capacity of distribution substations to their thermal limits. Distribution transformer substations are increasingly required to be compact, reliable, safe, and intelligent. To efficiently utilize city space and to support the intermittent load flows imposed by smart-grid features, such as distributed generation, the transformers are expected to operate close to or occasionally over their ratings, with stalled or little air circulation inside the safety enclosure. Dynamic thermal models with physically validated convection and radiation heat-transfer components are essential for the real-time thermal rating of substations. Natural convection via the air inside the cabin to the outside ambient air plays the major role in cooling down a transformer. In this study a scale model of a prefabricated substation is examined to draft a numerical solution which is based on stack ventilation principles. A clear and expandable first principle approach is used to quantify heat transfer through ventilation openings. Measurements from actual cabins and 3-D finite element method simulations are used to validate the numerical model.

Simulation-based validation of smart grids - status quo and future research trends

Smart grid systems are characterized by high complexity due to interactions between a traditional passive network and active power electronic components, coupled using communication links. Additionally, automation and information technology plays an important role in order to operate and optimize such cyber-physical energy systems with a high(er) penetration of fluctuating renewable generation and controllable loads. As a result of these developments the validation on the system level becomes much more important during the whole engineering and deployment process, today. In earlier development stages and for larger system configurations laboratory-based testing is not always an option. Due to recent developments, simulation-based approaches are now an appropriate tool to support the development, implementation, and roll-out of smart grid solutions. This paper discusses the current state of simulation-based approaches and outlines the necessary future research and development directions in the domain of power and energy systems.

Optimal Capacity Management of Substation Transformers Over Long-Run

The management of transformers capacity is a vital task for planners and asset managers due to their high cost. This paper proposes an optimization model for capacity management of transformers in a substation over long-run. The model considers the present worth costs of investment, losses, maintenance, reliability, and the salvage value of transformers for providing the optimal selection and scheduling of multistage transformer installations and their refurbishments. In the optimization model, growing failure rate of transformers along with their age is incorporated and the cumulative loss-of-life (LOL) of transformers is also used in determining their salvage value. The developed model is applied for planning and management of transformer capacities for a residential load dominant two-transformer primary distribution substation over a period of 40 years. The simulations are performed for various case studies representing the situations encountered by utilities. An extensive sensitivity analysis is also conducted for several conditions of the system parameters. The numerical results indicate the worth of inclusion of variable failure rate and LOL of transformers in their capacity management.