Combined Heat and Photo Voltaics (CHPV)

点击翻译按钮获取中文摘要

The Combined Heat and Photo-voltaic (CHPV) based local energy system solution was formulated on the simple, buteffective observation that CHP systems develop low carbon and energy efficient electrical power in the colder months ofthe year in the UK and Photo-voltaic (PV) power generation provides most of its low carbon power generation when there isno demand for heat in commercial buildings. By combining these two primary energy supplies, it is potentially feasible tocreate a LES which is autonomous to the national electricity grid by appropriate sizing of the CHP and PV systems. Thatsaid the supply and demand is highly transient and the use of energy storage and advanced control systems and otherdemand side measures such as Smart DC systems for lighting and ICT networks will enable accurate supply and demandmatching for both heat and power. This potential LES solution is highly attractive to industry partners in the CHPV projectsuch as Peel Utilities, BRE and ARUP. The system potentially offers a high return-on-infrastructure investment (ROI),however it is extremely complex to design to ensure that this ROI can be reliably achieved in practice. In order to assist inthe design and implementation of CHPV based LES systems the following research needs to be carried out:Task 1: Dr J. Counsell with the research assistant will develop ESL based models for the energy supply and demandsystems such as CHP and PV and the already developed through BRE Trust R&D funded projects IDEAS dynamicmodelling of buildings and there energy using systems. The researcher will be able to draw on existing models within theEEE department for PV and other micro-generation systems at Liverpool to rapidly develop comprehensive nonlinear dynamic models for both energy supply and energy demand in the buildings served by the CHPV based LES. (referreferences in Appendix A of the main TSB proposal for references of past modelling work)Task 2: Led by Dr Lin Jiang the researcher will use the ESL models resulting from task 1 to develop nonlinear optimalcontrol solutions to guarantee supply and demand matching with the constraints of satisfying thermal comfort requirementsin the buildings and the minimising the power drawn for the national power grid. The research will need new nonlinearinverse dynamic control algorithms developed by Dr Counsell (refer Appendix A for references) and nonlinear optimalcontrol strategies for demand side management systems developed by Dr Lin Jiang (refer Appendix A for references).These control algorithms will also be modelled and used in simulation studies to prove the effective regulation of theautomated CHPV systems.Task 3: Led By Dr Lin Jiang, the researcher will create the ESL models and tuned control algorithms for each of the threecase studies in this project.Task 4: Dr Counsell will lead the application of the resulting case study models in partnership with Peel, BRE and ARUP totest a number of demand side measures including Smart DC systems for LED lighting and ICT networks and devices. Thetests will establish the energy, carbon and economic benefits that Smart DC systems will bring to the CHPV based LESsolution and the models for Smart DC systems will be validated using the EEE department's new Smart DC PoE Networklaboratory now under construction.The lead academics and the researcher will engage with BRE and the BRE Trust to hold industry/academic researchworkshops and create high quality journal and BRE Trust publications as well as hold workshops to disseminate theeffectiveness of the CHPV concept. The resulting project outputs such as design tools from the university will also bedisseminated to the wider LES community. It will also investigate the potential for the design tools to be used as part ofpotentially new regulatory frameworks which are being developed outside this project for local energy systems.