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Combined Heat and Photo Voltaics (CHPV)

热电联产和光伏发电 (CHPV)

基本信息

批准号：
EP/M507192/1
负责人：
Lin Jiang
金额：
$ 22.9万
依托单位：
University of Liverpool
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2014
资助国家：
英国
起止时间：
2014 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=EP%2FM507192%2F1
关键词：
Combined Heat Photo Voltaics CHPV

项目摘要

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.

基于热电联产（CHPV）的本地能源系统解决方案是基于简单但有效的观察制定的，即热电联产系统在英国一年中较冷的月份开发低碳和节能电力，而光伏（PV）发电在商业建筑不需要热量时提供大部分低碳发电。通过结合这两个主要能源供应，它是潜在的可行toscreate一个LES，这是自主的国家电网的适当规模的热电联产和光伏系统。这就是说，供需是高度瞬态的，使用储能和先进的控制系统以及其他需求方措施，如智能直流照明系统和ICT网络，将使供热和电力的供需准确匹配。这种潜在的LES解决方案对CHPV项目的行业合作伙伴（如Peel Utilities、BRE和ARUP）具有很大的吸引力。该系统有可能提供高的基础设施投资回报率（ROI），但要确保在实践中可靠地实现这一ROI，其设计极其复杂。为了帮助设计和实施基于CHPV的LES系统，需要进行以下研究：任务1：J.Counsell博士和研究助理将为能源供应和需求系统（如CHP和PV）开发基于ESL的模型，以及已经通过BRE Trust研发资助的项目IDEAS建筑物和能源使用系统的动态建模。研究人员将能够利用现有的模型，在光伏和其他微型发电系统在利物浦的能源供应和能源需求的建筑物中的CHPV为基础的LES迅速开发全面的非线性动态模型。（参见TSB主要提案附录A中的参考文献，以供参考过去的建模工作）任务2：由Lin Jiang博士领导，研究人员将使用任务1产生的ESL模型来开发非线性最优控制解决方案，以保证供需匹配，满足建筑物的热舒适性要求，并最大限度地减少国家电网的电力消耗。这项研究将需要新的非线性逆动态控制算法，（参考附录A）和江林博士开发的需求侧管理系统的非线性最优控制策略（参考附录A）。这些控制算法也将被建模并用于模拟研究，以证明自动CHPV系统的有效调节。任务3：在林江博士的带领下，研究人员将为本项目的三个案例中的每一个案例创建ESL模型和调谐控制算法。任务4：Counsell博士将与Peel合作，BRE和ARUP将测试一系列需求方措施，包括用于LED照明和ICT网络和设备的智能直流系统。测试将确定能量，智能直流系统将为基于CHPV的LES解决方案带来的碳和经济效益，智能直流系统的模型将使用正在建设中的美国能源部新的智能直流PoE网络实验室进行验证。首席学者和研究人员将与BRE和BRE Trust合作，学术研究研讨会，并创建高质量的期刊和BRE信托出版物，以及举办研讨会，以传播CHPV概念的有效性。由此产生的项目产出，如大学的设计工具，也将传播到更广泛的LES社区。它还将调查潜在的设计工具，以作为潜在的新的监管框架的一部分，这是正在开发的地方能源系统以外的本项目。