Energy-on-Demand system based on combinatorial optimization of appliance operation modes

In this paper, the author proposes an Energy-on-Demand (EoD) system based on combinatorial optimization of appliance operation modes, and describes its implementation and evaluation. Recently, efficient usage of limited amount of electrical energy has been an important issue. EoD is a novel power network architecture of demand-side power management, whose objective is to intelligently manage power flows among power generations under the limitation of available power resource. In an EoD system, the importance of each appliance is explicitly parameterized, and the amount of power consumption of appliances is measured by power sensors. When total power consumption exceeds the limit of power resource, a power allocation manager deployed in the system decides the optimal power allocation to all the appliances based on their parameters, and controls the amount of power supplied to the appliances in a way that causes minimum undesired effect to quality-of-life (QoL) of users. Therefore, one of the most crucial factors in an EoD system is the strategy for deciding the optimal power allocation. From a mathematical viewpoint, the power allocation management in an EoD system can be considered as an optimization problem of appliance operation modes. In the developed system, power allocation is based on the multiple-choice knapsack problem (MCKP), a kind of combinatorial optimization problem. The system measures power consumption of appliances, computes the optimal power allocation based on an algorithm for the MCKP, and realizes computed power allocation by controlling IR-controllable appliances and mechanical relays.

[1]  W. Kempton,et al.  The consumer's energy analysis environment , 1994 .

[2]  Naoyuki Morimoto,et al.  Smart Outlet Network for Energy-Aware Services Utilizing Various Sensor Information , 2013, 2013 27th International Conference on Advanced Information Networking and Applications Workshops.

[3]  Sachin S. Sapatnekar,et al.  Residential task scheduling under dynamic pricing using the multiple knapsack method , 2012, 2012 IEEE PES Innovative Smart Grid Technologies (ISGT).

[4]  Yasuhiro Fuwa,et al.  Decision-making in electrical appliance use in the home , 2008 .

[5]  Naoyuki Morimoto,et al.  A Power Allocation Management System Using an Algorithm for the Knapsack Problem , 2014, 2014 IEEE 38th International Computer Software and Applications Conference Workshops.

[6]  Lukas Weber,et al.  Some reflections on barriers to the efficient use of energy , 1997 .

[7]  Yasuo Okabe,et al.  Quality-aware energy routing toward on-demand home energy networking: (Position paper) , 2011, 2011 IEEE Consumer Communications and Networking Conference (CCNC).

[8]  R. Howarth,et al.  ‘Normal’ markets, market imperfections and energy efficiency , 1994 .

[9]  K. Dudzinski,et al.  Exact methods for the knapsack problem and its generalizations , 1987 .

[10]  David S. Johnson,et al.  Computers and Intractability: A Guide to the Theory of NP-Completeness , 1978 .

[11]  N. Fujita,et al.  A rule generation method for electrical appliances management systems with home EoD , 2012, The 1st IEEE Global Conference on Consumer Electronics 2012.

[12]  Yasuo Okabe,et al.  Power Allocation Algorithms of PoE for On-Demand Power Supply , 2013, 2013 IEEE 37th Annual Computer Software and Applications Conference Workshops.

[13]  Takashi Matsuyama,et al.  Energy on demand: Efficient and versatile energy control system for home energy management , 2011, 2011 IEEE International Conference on Smart Grid Communications (SmartGridComm).

[14]  Willett Kempton,et al.  Folk quantification of energy , 1982 .

[15]  Omid Ameri Sianaki,et al.  A Knapsack problem approach for achieving efficient energy consumption in smart grid for endusers' life style , 2010, 2010 IEEE Conference on Innovative Technologies for an Efficient and Reliable Electricity Supply.

[16]  Osamu Saeki,et al.  Effectiveness of an energy-consumption information system for residential buildings , 2006 .