Antti Alahäivälä

Optimized Control of Price-Based Demand Response With Electric Storage Space Heating

The increased uncertainty of the electric grid due to the penetration of renewable energy sources and deregulation of the electric market is aimed to be alleviated by demand response (DR) in the future smart grid. The demand-side resources can be incentivized to alter their consumption patterns by varying their electricity price over time. A major residential energy demand contribution is from electric heating, which, when combined with smart energy storage using water heaters, could be utilized to defer consumption to more inexpensive periods without affecting the customers thermal quality of service. The objective is to optimize the consumer electricity price of electric storage space heating customers, in order to maximize the profit of the retailer. This approach of varying the customer electricity prices leads to a game-theoretic scenario, where the procurement and consumption profiles of the retailer and consumer agents are based on the set electricity price. The optimization of the consumer electricity price is shown to offer lesser expense for the retailer. In addition, hourly load-following can be improved by offering further discounts for the consumers.

Agent-based modeling and simulation of a smart grid: A case study of communication effects on frequency control

Abstract A smart grid is the next generation power grid focused on providing increased reliability and efficiency in the wake of integration of volatile distributed energy resources. For the development of the smart grid, the modeling and simulation infrastructure is an important concern. This study presents an agent-based model for simulating different smart grid frequency control schemes, such as demand response. The model can be used for combined simulation of electrical, communication and control dynamics. The model structure is presented in detail, and the applicability of the model is evaluated with four distinct simulation case examples. The study confirms that an agent-based modeling and simulation approach is suitable for modeling frequency control in the smart grid. Additionally, the simulations indicate that demand response could be a viable alternative for providing primary control capabilities to the smart grid, even when faced with communication constraints.

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.

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.

A Distributed ICT Architecture for Continuous Frequency Control.

The active participation of consumers in frequency control can mitigate the negative effects of variable renewable generation in a power system. This study aims at designing a distributed informati ...