This paper investigates heat pump systems in smart grids, focussing on fields of application and control approaches that have emerged in academic literature. Based on a review of published literature technical aspects of heat pump flexibility, fields of application and control approaches are structured and discussed. Three main categories of applications using heat pumps in a smart grid context have been identified: First stable and economic operation of power grids, second the integration of renewable energy sources and third operation under variable electricity prices. In all fields heat pumps - when controlled in an appropriate manner - can help easing the transition to a decentralized energy system accompanied by a higher share of prosumers and renewable energy sources. Predictive controls are successfully used in the majority of studies, often assuming idealized conditions. Topics for future research have been identified including: a transfer of control approaches from simulation to the field, a detailed techno-economic analysis of heat pump systems under smart grid operation, and the design of heat pump systems in order to increase flexibility are among the future research topics suggested.

Coordinated Electric Vehicle Charging Control with Aggregator Power Trading and Indirect Load Control
James J.Q. Yu, Junhao Lin, Albert Y.S. Lam, Victor O.K. Li
(Submitted on 4 Aug 2015)

Due to the increasing concern on greenhouse gas emmissions and fossil fuel security, Electric Vehicles (EVs) have attracted much attention in recent years. However, the increasing popularity of EVs may cause stability issues to the power grid if their charging behaviors are uncoordinated. In order to address this problem, we propose a novel coordinated strategy for large-scale EV charging. We formulate the energy trade among aggregators with locational marginal pricing to maximize the aggregator profits and to indirectly control the loads to reduce power network congestion. We first develop a centralized iterative charging strategy, and then present a distributed optimization-based heuristic to overcome the high computational complexity and user privacy issues. To evaluate our proposed approach, a modified IEEE 118 bus testing system is employed with 10 aggregators serving 30 000 EVs. The simulation results indicate that our proposed approach can effectively increase the total profit of aggregators, and enhance the power grid stability. 

Subjects: Systems and Control (cs.SY)

@INPROCEEDINGS{7174716,
author={Powroznik, Piotr and Michta, Emil},
booktitle={Nonsinusoidal Currents and Compensation (ISNCC), 2015 International School on},
title={Elastic model of energy management in micro smart grid},
year={2015},
month={June},
pages={1-6},
abstract={In modern electric power systems (EPS) solutions based on advanced metering infrastructure (AMI) are required. The data collected by AMI could help to detect an emergency situations in EPS. AMI two way communications allows both to collect measuring data and control devices referred to as a nodes. Nodes providing control and measurement functions create a smart grid (SG). The smart grid nodes are appliances, power generation and storage capacity. In the case of power storage, these nodes can also take power, in the case of having to be recharged. Analysis of all possible power combining, for all three categories of nodes in even micro SG (MSG) may not be feasible due to time. A novel approach to the power management in MSG by use of an elastic management energy model have been presented in the paper.},
keywords={Artificial intelligence;Heating;Reliability;Security;Smart grids;balanced power selection;elastic management energy model;micro smart grids},
doi={10.1109/ISNCC.2015.7174716},}