Combined Heat and Photo Voltaics (CHPV)

基于热电联产和光伏（CHPV）的本地能源系统解决方案是基于一个简单而有效的观察而制定的，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的电力，而光伏（PV）发电在商业建筑没有供热需求时提供了大部分的低碳发电。通过将这两种主要能源供应结合起来，通过适当规模的热电联产和光伏系统，创建一个独立于国家电网的LES是潜在可行的。也就是说，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侧措施，如照明和ICT网络的智能直流系统，将实现热电的准确供需匹配。这种潜在的LES解决方案对热电联产项目的行业合作伙伴（如Peel Utilities、BRE和ARUP）极具吸引力。该系统可能提供高基础设施投资回报率（ROI），然而，要确保在实践中可靠地实现该ROI，其设计非常复杂。为了协助基于热电联产的LES系统的设计和实施，需要进行以下研究：任务1:J. Counsell博士和研究助理将开发基于ESL的能源供需系统模型，如热电联产和光伏，以及已经通过BRE Trust研发资助的项目开发的建筑物和能源使用系统的IDEAS动态模型。研究人员将能够利用利物浦eee部门现有的光伏和其他微型发电系统模型，快速开发基于CHPV的LES服务的建筑物的能源供应和能源需求的综合非线性动态模型。（参考过去建模工作的主要TSB提案附录A）任务2：由林江博士领导，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，以保证供需与满足建筑物热舒适要求的约束相匹配，并最大限度地减少国家电网的电力消耗。这项研究将需要Counsell博士开发的新的非线性逆动态控制算法（参见附录A）和Lin Jiang博士开发的需求侧管理系统的非线性最优控制策略（参见附录A）。这些控制算法也将被建模并用于仿真研究，以证明自动化热电光伏系统的有效调节。任务3：在林江博士的带领下，研究人员将为本项目中的三个案例研究创建ESL模型和调谐控制算法。任务4:Counsell博士将领导与Peel、BRE和ARUP合作的案例研究模型的应用，以测试一些需求侧措施，包括LED照明和ICT网络和设备的智能直流系统。这些测试将确定智能直流系统将为基于CHPV的LESsolution带来的能源，碳和经济效益，智能直流系统模型将使用EEE部门正在建设的新智能直流PoE网络实验室进行验证。首席学者和研究人员将与BRE和BRE信托合作，举办行业/学术研究研讨会，创建高质量的期刊和BRE信托出版物，以及举办研讨会，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，也将传播给更广泛的LES社区。它还将调查设计工具的潜力，将其用作该项目外正在为当地能源系统开发的潜在新监管框架的一部分。

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.