HEMS technique for heat-harm control and geo-thermal utilization in deep mines

With the increasing exploitation scope and intensity,the shallow resources would be exhausted in the future;and the deep mining will become an essential choice.In deep tunnel engineering,the heat-harm becomes one of the mainbariers.Investigations on high temperature coal mine have been done in Nothem China,with the construting of threemodels of high temperature mines suffering heat-harm,at the Jiahe mine,Sanhejian mine and Zhangshuanglou mine.Thedomestic and abroad cooling technologies of the mine respectively are also summarized after comparatively analyzing theadvantages and disadvantages of each technology.Finally,we find that the high temperature exchange machinery system(HEMS)technology that use mine discharge as the cold source,is excellent to heat-ham control in deep mines.Taking theJiahe coal mine as an example,we systematically introduce this teclnology by disposing three main workstations.HEMStechnology with its operations and functions in different exploitation levels are accomplished,including the extraction ofrefrigerating output,the transportation of chilled water by closed circulation line,the decompression of circulation linesand equipment by pressure transformation machine,and the heat exchange and cooling of workplace by heat exchangebetween wind stream and the chilled water.The exchanged heat source from the workplace is taken to ground heating bythe circulating water which acts as a carrier.It shows that the HEMS-technology benefit in environment protection andemission reduction.Results of this project illustrate that it is efficient in heat-ham control with the temperature decrease ofthe workplace down to 26-29℃,and being 4-6℃ lower than the original,and the relative humidity 5%-15%lowerthan before.It greatly improves the working environment of underground workplace suffering heat-ham of high tem-perature and high humidity.In addition,by the extracting of deep geothermal enery,ground fired boiler for heating hasbeen replaced,reducing environmental pollution.This technology is worth generalization in deep mines and related fields.

AC Scheduling Based on Thermodynamics of Indoor for On-Campus Small Data

This paper proposes a new day-ahead control scheme of an air conditioning (AC) based on thermodynamic model of indoor-temperature. The thermodynamic model of indoor-temperature can be achieved by modified first-order thermal dynamic equation. For the practical verification of proposed model, we implemented the home energy management system (HEMS) in the laboratory and used real experiment data sets. The proposed model can be represented by a state-space model of indoor-temperature and its parameters are obtained by least square algorithm. Through the proposed thermodynamic model, indoor-temperature can be predicted closely, and a behavior pattern of AC can also be achieved. This research involves the experimental verification of the proposed approach and communication architecture between the aggregator and a system user in a laboratory environment.

Probabilistic Assessment of Impact of Flexible Loads Under Network Tariffs in Low-voltage Distribution Networks

Given the historically static nature of low-voltage networks, distribution network companies do not possess the tools for dealing with an increasingly variable demand due to the high penetration of distributed energy resources (DERs). Within this context, this paper proposes a probabilistic framework for tariff design that minimises the impact of DER on network performance, stabilises the revenue of network company, and improves the equity of network cost allocation. To deal with the lack of customers’ response, we also show how DER-specific tariffs can be complemented with an automated home energy management system (HEMS) that reduces peak demand while retaining the desired comfort level. The proposed framework comprises a nonparametric Bayesian model which statistically generates synthetic load and PV traces, a hot-water-use statistical model, a novel HEMS to schedule customers’ controllable devices, and a probabilistic power flow model. Test cases using both energy- and demand-based network tariffs show that flat tariffs with a peak demand component reduce the customers’ cost, and alleviate network constraints. This demonstrates, firstly, the efficacy of the proposed tool for the development of tariffs that are beneficial for the networks with a high penetration of DERs, and secondly, how customers’ HEM systems can be part of the solution.

Distributionally robust optimization of home energy management system based on receding horizon optimization

This paper investigates the scheduling strategy of schedulable load in home energy management system(HEMS)under uncertain environment by proposing a distributionally robust optimization(DRO)method based on receding horizon optimization(RHO-DRO).First,the optimization model of HEMS,which contains uncertain variable outdoor temperature and hot water demand,is established and the scheduling problem is developed into a mixed integer linear programming(MILP)by using the DRO method based on the ambiguity sets of the probability distribution of uncertain variables.Combined with RHO,the MILP is solved in a rolling fashion using the latest update data related to uncertain variables.The simulation results demonstrate that the scheduling results are robust under uncertain environment while satisfying all operating constraints with little violation of user thermal comfort.Furthermore,compared with the robust optimization(RO)method,the RHO-DRO method proposed in this paper has a lower conservation and can save more electricity for users.