Reduction Of Peak Power Consumption Research Articles

Experimental study of an on-grid hybrid solar air conditioner with evaporative pre-cooling of condenser inlet air

This paper presents an experimental study of a split type solar air conditioning system with evaporative pre-cooling at the condenser. The main objective of this research is to evaluate the thermal and electrical performance of the system under hot summer conditions in a Mediterranean climate. Previous studies have separately shown the benefits of both condenser inlet air pre-cooling and photovoltaic solar cooling. The novelty of this work will be the study of the coupling of these two techniques in a real installation, where the viability of the system depends on the component-level design and the operating conditions, since weather variables such as ambient temperature, relative humidity and solar radiation significantly affect the thermal behaviour of the refrigeration cycle, the evaporative pre-cooling capacity and the performance of the photovoltaic panels. Experimental tests were carried out over a summer season to evaluate the behaviour of the system and to obtain performance correlations validated with experimental data. These correlations will allow the modelling of the system and will be used to carry out an economic and environmental feasibility study of the proposed hybrid solar air conditioning system. The results show that a 100mm-thick evaporative pad achieved an average evaporative cooling efficiency for all tests performed of ɛevap=67.4%, reducing the air inlet temperature to the condenser by around 6°C. This resulted in an 18.3% improvement in the EER of the air conditioner. In addition, the use of evaporative pre-cooling resulted in a significant 23% reduction in peak power consumption. The study also evaluated the impact of the air pressure drop caused by the evaporative pad when not in use, with results favouring its installation. The system achieved a solar contribution of more than 30% under different solar radiation conditions when using pre-cooling, compared to 25% with a standard condenser. In addition, the combination of photovoltaic contribution and evaporative pre-cooling reduced energy consumption by 43%.

Residential Consumer-Centric Demand-Side Management Based on Energy Disaggregation-Piloting Constrained Swarm Intelligence: Towards Edge Computing.

The emergence of smart Internet of Things (IoT) devices has highly favored the realization of smart homes in a down-stream sector of a smart grid. The underlying objective of Demand Response (DR) schemes is to actively engage customers to modify their energy consumption on domestic appliances in response to pricing signals. Domestic appliance scheduling is widely accepted as an effective mechanism to manage domestic energy consumption intelligently. Besides, to residential customers for DR implementation, maintaining a balance between energy consumption cost and users’ comfort satisfaction is a challenge. Hence, in this paper, a constrained Particle Swarm Optimization (PSO)-based residential consumer-centric load-scheduling method is proposed. The method can be further featured with edge computing. In contrast with cloud computing, edge computing—a method of optimizing cloud computing technologies by driving computing capabilities at the IoT edge of the Internet as one of the emerging trends in engineering technology—addresses bandwidth-intensive contents and latency-sensitive applications required among sensors and central data centers through data analytics at or near the source of data. A non-intrusive load-monitoring technique proposed previously is utilized to automatic determination of physical characteristics of power-intensive home appliances from users’ life patterns. The swarm intelligence, constrained PSO, is used to minimize the energy consumption cost while considering users’ comfort satisfaction for DR implementation. The residential consumer-centric load-scheduling method proposed in this paper is evaluated under real-time pricing with inclining block rates and is demonstrated in a case study. The experimentation reported in this paper shows the proposed residential consumer-centric load-scheduling method can re-shape loads by home appliances in response to DR signals. Moreover, a phenomenal reduction in peak power consumption is achieved by 13.97%.

Towards Cost and Comfort Based Hybrid Optimization for Residential Load Scheduling in a Smart Grid

In a smart grid, several optimization techniques have been developed to schedule load in the residential area. Most of these techniques aim at minimizing the energy consumption cost and the comfort of electricity consumer. Conversely, maintaining a balance between two conflicting objectives: energy consumption cost and user comfort is still a challenging task. Therefore, in this paper, we aim to minimize the electricity cost and user discomfort while taking into account the peak energy consumption. In this regard, we implement and analyse the performance of a traditional dynamic programming (DP) technique and two heuristic optimization techniques: genetic algorithm (GA) and binary particle swarm optimization (BPSO) for residential load management. Based on these techniques, we propose a hybrid scheme named GAPSO for residential load scheduling, so as to optimize the desired objective function. In order to alleviate the complexity of the problem, the multi dimensional knapsack is used to ensure that the load of electricity consumer will not escalate during peak hours. The proposed model is evaluated based on two pricing schemes: day-ahead and critical peak pricing for single and multiple days. Furthermore, feasible regions are calculated and analysed to develop a relationship between power consumption, electricity cost, and user discomfort. The simulation results are compared with GA, BPSO and DP, and validate that the proposed hybrid scheme reflects substantial savings in electricity bills with minimum user discomfort. Moreover, results also show a phenomenal reduction in peak power consumption.

Robust flow shop scheduling with random processing times for reduction of peak power consumption

Recently, power shortages have become a major problem all over Japan, due to the Great East Japan Earthquake, which resulted in the shutdown of a nuclear power plant. As a consequence, production scheduling has become a problem for factories, due to considerations of the availability of electric power. For factories, the contract with the electric power company sets the maximum power demand for a unit period, and in order to minimize this, it is necessary to consider the peak power when scheduling production. There are conventional studies on flowshop scheduling with consideration of peak power. However, these studies did not consider fluctuations in the processing time. Because the actual processing time is not constant, there is an increase in the probability of simultaneous operations with multiple machines. If the probability of simultaneous operations is high, the probability of increasing the peak power is high. Thus, we consider inserting idle time (delay in inputting parts) into the schedule in order to reduce the likelihood of simultaneous operations. We consider a robust schedule that limits the peak power, in spite of an unexpected fluctuation in the processing time. However, when we insert idle time, the makespan gets longer, and the production efficiency decreases. Therefore, we performed simulations to investigate the optimal amount of idle time and the best point for inserting it. We propose a more robust production scheduling model that considers random processing times and the peak power consumption. The results of experiments show that the effectiveness of the schedule produced by the proposed method is superior to the initial schedule and to a schedule produced by another method. Thus, the use of random processing times can limit the peak power.

Workers' awareness and indoor environmental quality in electricity-saving offices

Owing to the enormous damage caused by the Great East Japan Earthquake of 2011, a 15% reduction in peak power consumption was required to address the gap between demand and supply capabilities in the summer of 2011. Electricity-saving measures are promoted in offices today for both environmental and safety reasons, and indoor office environments have changed greatly. This paper aims to reveal to what extent workers' awareness of electricity-saving has changed since the earthquake disaster had an impact on energy consumption and productivity. The authors have conducted continuous fieldwork and questionnaire surveys in seven electricity-saving office buildings in the summers of 2011–2013. Additionally, our laboratory's past research data were collected together and analyzed. The results show that excessive indoor air temperatures, such as 28 °C, were avoided, and the desk level illuminance greatly decreased, from 750 lux to around 400 lux, after the earthquake. People learned to implement electricity saving in a proper way that does not spoil workers' comfort, and workers' acceptability zone for the indoor environment was extended by the experience of electricity-saving. Moreover, when we compared individual differences in the way environmental information is perceived, it was shown that differences in the workers' awareness of electricity-saving had a more profound effect on their satisfaction with the indoor environmental quality than those in their gender or age. Mechanical power-saving is definitely important; however, building devices that induce the occupants' energy-saving actions are vital. Our results will be considerably useful to other countries, whether or not they experience a natural disaster.

96/02034 Distribution of some natural and artificial radionuclides in the environment of coastal Karnataka of South India

Owing to the enormous damage caused by the Great East Japan Earthquake of 2011, a 15% reduction in peak power consumption was required to address the gap between demand and supply capabilities in the summer of 2011. Electricity-saving measures are promoted in offices today for both environmental and safety reasons, and indoor office environments have changed greatly. This paper aims to reveal to what extent workers' awareness of electricity-saving has changed since the earthquake disaster had an impact on energy consumption and productivity. The authors have conducted continuous fieldwork and questionnaire surveys in seven electricity-saving office buildings in the summers of 2011–2013. Additionally, our laboratory's past research data were collected together and analyzed. The results show that excessive indoor air temperatures, such as 28 °C, were avoided, and the desk level illuminance greatly decreased, from 750 lux to around 400 lux, after the earthquake. People learned to implement electricity saving in a proper way that does not spoil workers' comfort, and workers' acceptability zone for the indoor environment was extended by the experience of electricity-saving. Moreover, when we compared individual differences in the way environmental information is perceived, it was shown that differences in the workers' awareness of electricity-saving had a more profound effect on their satisfaction with the indoor environmental quality than those in their gender or age. Mechanical power-saving is definitely important; however, building devices that induce the occupants' energy-saving actions are vital. Our results will be considerably useful to other countries, whether or not they experience a natural disaster.