Mubbashir Ali

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.

A User-centric Demand Response Framework for Residential Heating, Ventilation, and Air-conditioning Load Management

Abstract The domestic heating, ventilation, and air-conditioning load promises a good prospect for electrical aggregators to consider it for demand response. This article presents a user-centric demand response control for scheduling the electric space heating load under a price and load uncertainty environment. The objective of the framework is to minimize a weighted sum of the expected payment, loss of comfort, and financial risk of a customer while strictly considering the end-user preferences. The household thermal behavior is modeled via an accurate two-capacity building model. The price and load uncertainty is modeled using a scenario-based stochastic programming approach. The proposed decision model is formulated as a non-linear programming problem that can be simply solved via commercially available solvers. The effectiveness of the formulation is demonstrated by applying it to a typical customer. The simulation results demonstrate that the decision mechanism allows consumers to compromise among electricity payment, thermal comfort, and risk exposure based on their thermal comfort preferences and risk priorities.

Optimal use of demand response for lifesaving and efficient capacity utilization of power transformers during contingencies

Contingencies of transformers in a multi-unit substation may affect life of healthy units severely due to overloads. This paper proposes a novel demand response (DR) and dynamic thermal rating (DTR) based optimization model for efficient capacity utilization and life management of transformers during contingencies. The model opts for the optimal combination of corrective actions among load curtailment (LC), DR, and shifting load to an adjacent substation while maintaining the winding hot-spot-temperature (HST) under a predefined limit. Simulations are performed, on a typical Finnish two-transformer primary distribution substation as a test system, for case studies of demand with and without DR & two situations based on availability of neighboring substation connection. The obtained results indicate that the proposed model offers substantial benefits of life-saving and utilization improvement for transformers present in different ambient conditions.

A Framework to Split the Benefits of DR Between Wind Integration and Network Management

In power systems today, considerable developments are being made in the energy transition from centralized fossil fuels to renewable distributed generation (DG) sources. However, this ongoing progress has presented several challenges to the operation and planning of distribution systems due to the variability of intermittent renewable generation. Demand response (DR) is widely regarded as a feasible tool to provide a seamless transition by altering the load profiles according to the intermittent generation profile. However, the resultant volatile power flows can be taxing for network capacity. This paper offers a framework from the distribution system operators perspective for the optimal utilization of DR between DG curtailment mitigation and network management. The application of the developed framework to a generic Finnish distribution system demonstrates that the benefits of DR should be envisioned for network management as long as the wind curtailment rate is below a certain level. This means that, beyond the threshold energy curtailment rate, the distribution system operator would be more economically efficient by making network reinforcements.

Assessing the upward demand response potential for mitigating the wind generation curtailment: A case study

The increased penetration of intermittent renewable generation has already resulted in spilling and it is projected that renewable energy curtailment level will continue to soar. This paper presents a framework to assess the flexibility of domestic thermal loads and Electric vehicles (EVs) charging load for power sink as a means to reduce wind energy curtailment during different times of a year. The objective of the framework is to jointly optimize the flexible loads to mitigate the curtailment thereby increasing the utilization of intermittent renewable generation. The proposed model is applied to the Finnish power system. The simulation results suggested that the proper activation of demand response (DR) is a feasible curtailment mitigation option but with an important caveat that potential subdued as the renewable penetration increases in the system.