Combined Heat and Photo Voltaics (CHPV)

基于联合热能和光伏(CHPV)的本地能源系统解决方案是基于简单但有效的观察而制定的，即在英国，热电联产系统在一年中较冷的月份开发低碳和高能效的电力，而当商业建筑没有供热需求时，光伏(PV)发电提供其大部分低碳发电。通过将这两种一次能源供应结合在一起，通过适当调整热电联产和光伏系统的规模，创建一个独立于国家电网的LES是潜在的可行的。也就是说，供需是高度瞬变的，使用储能和先进的控制系统以及其他需求方措施，如用于照明和ICT网络的智能直流系统，将使供需双方能够准确匹配热量和电力。这一潜在的LES解决方案对CHPV项目中的行业合作伙伴非常有吸引力，例如Peel Utilities、BRE和ARUP。该系统潜在地提供了高的基础设施投资回报(ROI)，然而，要确保在实践中可靠地实现该ROI，其设计是极其复杂的。为了协助基于CHPV的LES系统的设计和实施，需要进行以下研究：任务1：Dr.J.Counsell将与研究助理一起为热电联产和光伏等能源供需系统开发基于ESL的模型，以及已经通过BRE Trust研发资助的项目想法对建筑物及其能源使用系统进行动态建模。研究人员将能够利用利物浦光伏和其他微型发电系统的EEE部门的现有模型，为基于CHPV的LES服务的建筑中的能源供应和能源需求快速开发全面的非线性动态模型。任务2：在林江博士的带领下，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，以确保供需匹配，满足建筑物的热舒适性要求，并将国家电网的耗电量降至最低。这项研究将需要康塞尔博士开发的新的非线性逆动态控制算法(参考附录A)和林江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仿真研究，以证明自动CHPV系统的有效调节。任务3：在林江博士的领导下，研究人员将为本项目中的三个案例研究创建ESL模型和调整控制算法。任务4：康塞尔博士将与Peel合作领导所产生的案例研究模型的应用，BRE和ARUP测试了一系列需求侧措施，包括用于LED照明的智能直流系统和ICT网络和设备。测试将确定智能直流系统将为基于CHPV的LES解决方案带来的能源、碳和经济效益，智能DC系统的模型将使用EEE部门正在建设的新的智能DC PoE网络实验室进行验证。主要学者和研究人员将与BRE和BRE Trust合作举办行业/学术研究研讨会，创建高质量的期刊和BRE Trust出版物，以及举办研讨会以传播CHPV概念的有效性。由此产生的项目成果，如大学的设计工具，也将传播给更广泛的大专院校。它还将调查设计工具作为潜在的新监管框架的一部分的可能性，这些框架是在该项目之外为当地能源系统开发的。

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.