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In the smart grid, residential consumption scheduling in demand-side management (DSM) is one of the key technologies to facilitate utility companies and users in order to achieve systems optimality such as minimizing energy cost and demand peak. The success of DSM implementation depends on the level of user participation. While most of the prior works on DSM have reported good optimal results, they show a lack of focus towards user-centric issues such as user preferences, consumption deviation, and system fairness. Failure to account for such issues may lead to lower user participation in DSM programs. To address this problem, we propose user-centric consumption scheduling and fair billing mechanism for DSM program which consider economic as well as comfort aspects. First, a user’s discomfort cost is integrated into price incentives for determining consumption schedules. Second, consumption rescheduling mechanism is designed to allow users to change their preferences if necessary, and request new schedules. Finally, to improve the level of system fairness and avoid strategic players who try to manipulate the consumption profile for their benefit, a fair billing mechanism is proposed at the end of the scheduling period which takes into account both rescheduling users and user’s consumption deviation level. Simulation results show the effectiveness of the proposed method in terms of energy cost saving and improving fairness in the user’s billing., identifier:https://dspace.jaist.ac.jp/dspace/handle/10119/16128

The electricity generated by renewable energy sources fluctuates depending on its intermittent nature, and change of weather conditions. Similarly, power demand also vary dynamically due to change of operation mode, user preferences etc. To mitigate the effects of power fluctuations caused by fluctuating power sources and loads, a power flow control is introduced which assigns power levels for controllable power devices and connections between power sources and loads to absorb the power fluctuations of fluctuating power devices. This paper introduces a new robustness test method for a power flow system consisting of controllable and fluctuating power devices which can guarantee the existence of feasible solution for any power level of fluctuating power devices. The proposed test method can be formulated as a linear programming problem, and can be solved with a polynomial time complexity., identifier:https://dspace.jaist.ac.jp/dspace/handle/10119/16216

The integration of renewable energy sources into grid, and ever growing power demand have increased the risks of stability and quality of power of the grid. The purpose of this paper is to present a new approach of formulating a power flow control problem using linear programming model which assigns power levels for controllable power devices and power flows between power sources and loads to accommodate power fluctuations caused by fluctuating power devices. In addition, different cost minimization criteria have been taken into consideration and their effects on power assignment has been investigated. Finally, Linear Programming Solver in MATLAB environment is used to find the solution of the proposed power flow control problem., identifier:https://dspace.jaist.ac.jp/dspace/handle/10119/16452

The increase in distributed energy resources using renewable energy such as photovoltaic and wind generation systems require new strategies for the operation and management of the electricity because of their intermittent nature. The high proportion of distributed energy resources and uncertainty of power loads makes the power flow and energy management complex. Due to the uncontrollability of power devices, power imbalance between generation and consumption is an important issue to be solved. Hence, there is a need to develop sophisticated power flow control systems which can control power flows from distributed power sources to power loads in real-time. This paper presents the power flow control mechanism, which assigns power to controllable power sources and loads, and connections between them to absorb the power fluctuations caused by fluctuating power sources and loads.

Renewable energy sources such as wind power or photo-voltaic power are environmental-friendly, but the fluctuation of the output power can affect the stability and quality of power network due to their intermittent nature. From such point of view, a power flow control is introduced which assigns power levels for controllable power devices and connections between power devices to absorb the power fluctuations caused by fluctuating devices. While, the system controller needs to handle various aspects such as transient behavior, latency of system control, cost efficiency etc., the issue whether the system has a feasible solution or not is one of the most important issues. In the paper, we discuss solvability conditions for a system which includes both controllable and fluctuating power devices (i) with given power generation and consumption levels of fluctuating devices, and (ii) with any power level of fluctuating sources and loads. Hence, the ultimate objective is to design a system which has robustness against power fluctuations caused by fluctuating devices.

In the future smart grid, Demand Side Management (DSM) will be implemented to facilitate utility companies and consumers in order to achieve mutual benefits such as minimizing total energy cost and reducing consumption peaks. The optimal energy consumption scheduling is calculated based on user preferences in advance, e.g., day-ahead schedules. Most of the prior works in the literature have reported good results under the assumption that users are committed to the optimal schedules and do not deviate from their preferences, which may not be true in practice. In this paper, we consider the implications of allowing users to change their preferences and request new schedules at any time. Based on user constraints, we propose single and multi-user adaptive rescheduling algorithms. The algorithms reschedule deviating energy consumption optimally thus reducing the total energy cost. Simulation results show that the total energy cost of the community can be reduced by as much as 11.4% in specific scenarios., identifier:https://dspace.jaist.ac.jp/dspace/handle/10119/16127

In the future smart grid, Demand Side Management (DSM) will be one of the key technologies to facilitate utility companies and customers in order to achieve system optimality such as minimizing energy cost and peak-to-average ratio. While most of the prior works in the literature have reported good results in achieving system optimality, they mostly ignore considering the aspect of system fairness, especially in regards to the electricity bills of the users. More specifically previous works do not address the important problem of users' commitment and their actual consumption level when calculating the payments. In this paper, we tackle this problem and design an alternative fair billing mechanism that assures the system fairness. The proposed billing considers not only real-time consumption information of the grid but also the energy consumption level of each user. Thus, each user's bill will be adjusted based on their commitment and contribution to the system. Simulation results show that the proposed billing mechanism ensures fairness in users' payments., identifier:https://dspace.jaist.ac.jp/dspace/handle/10119/16117

Recent advancements in renewable energy sources and Internet of Things (IoT) technologies has urged energy management to enter the era of Internet of Energy (IoE). The development of renewable and distributed power sources along with the change in power market structure due to deregulation require a new agent to manage these resources in the most efficient way. An aggregator can manage the supply side and the demand side in order to provide some services to the grid as well as to consumers. This paper proposes an IoE based framework of aggregators for power allocation among residential users in the presence of distributed power sources. The novelty of our proposed framework rests in (i) power assignment criteria based on detailed residential demand profile (ii) power supply from multiple power sources based on their capacity limitation (iii) consideration of communication delay., identifier:https://dspace.jaist.ac.jp/dspace/handle/10119/16118

This paper proposes a distributed scheme for demand response and user adaptation in smart grid networks. Our system model considers scarce distributed power sources and loads. User preference is modelled as `willingness to pay' parameter and logarithmic utility functions are used to model the behaviour of users. The energy management problem is cast as an optimization problem, where the objective is to maximize the utility services to the clients based on price-based demand response scheme. We have addressed the issue concerning the allocation of power among users from multiple sources/utilities within a distributed power network based on users' demands and willingness to pay. We envision a central entity providing a coordinated response to the huge number of scattered consumers, collecting power from all generators and assigning the power flow to the interested users. We propose a two layer price-based demand response architecture. The lower level energy management scheme deals with the power allocation from aggregator to the consumers, and the upper level deals with the distribution of power from utilities to aggregators to ensure the demand-supply balance.