ADJUDICACIÓN DEL CONTRATO 27

The control algorithm for the controllers in the CHPV system was designed using the Inverse Dynamic methodology [118] to create a robust independent controller for the CHPV system as shown in figure

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(4.3). This controller tracks a desired power demand from the national grid (e.g. set to zero watts in this case) and a target heat network temperature set to 85ºC. In this case study simulations showed the CB matrix should be diagonal and invertible. For that it could be assumed that: [ −𝑄̇𝐶𝐻𝑃𝑂+𝑚̇𝑤𝑐𝑤∆𝑇𝑂 𝜏𝑤 𝐾𝑄𝐶𝐻𝑃(1− 𝑈𝑜) 𝜏𝑤 0 −𝑠𝐾_{𝑃𝐶𝐻𝑃} ] −1 ≈ [ −𝑄̇𝐶𝐻𝑃𝑂+𝑚̇𝑤𝑐𝑤∆𝑇𝑂 𝜏𝑤 0 0 −𝑠𝐾_{𝑃𝐶𝐻𝑃} ] −1 (26)

By assuming ∆𝑇𝑂 = 10 And 𝑈𝑜 = 0 equation (26) gives:

[ −0.42∗1800000+92 300 0.42∗1 300 0 −s 0.42] −1 ≈ [ −𝑄̇𝐶𝐻𝑃𝑂+𝑚̇𝑤𝑐𝑤∆𝑇𝑂 𝜏𝑤 0 0 −𝑠𝐾_{𝑃𝐶𝐻𝑃}] −1 (27)

As equation (27) is dominantly diagonal then consequently, two primary single input single output (SISO) control systems can be robustly created to decouple heat and power feedback control loops in the CHPV system. These SISO tracking control systems were specified as follows:

a) A feedback control system that tracks desired national grid demand by regulating the gas power supplied to the CHP engine. b) A feedback control system that tracks a set point of the average

temperature of the heat network (e.g. 85°C) by regulating the target average temperature of the hot water tank thermal store.

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c) A thermostat control for each building/zone to track the desired building temperature by regulating the heat delivered by the heat network to building/zone via its heat exchanger.

A secondary supplementary control operates the back-up gas boiler only when CHP heat output is at its maximum and the average water network temperature is below a set point of 80ºC. Whilst the controllers are non- interacting systems, they were designed using a multi-input multi- output controller Inverse Dynamic [118] [119]. The novel system controller topology has created a remarkable and simple solution to decouple the interaction between heat and power that exists with all CHP based solutions. The control also allows tracking of target set points in the presence of multiple heat [121] and power disturbances such as the power generated by on-site renewables such as PV. A MATLAB/Simulink model was developed to incorporated models of the three SISO control systems and supplementary boiler control to test this new electrically led CHP engine and the heat network control strategy. This strategy in addition to models mentioned also modelled the thermostatic control of the buildings by controlling the heat flow from the heat exchanger in the heat network to maintain the required thermal comfort temperature 21°C (including an optimum start and at night time

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set point of 12°C) and a chiller compressor for electrical cooling of the building when the building temperature exceeds 24°C. The controller of CHP engine follows the electrical demand of the building and at same time pumps the heat generated into the heat network. When the building has enough heat to maintain the thermal comfort requirements and the CHP has surplus heat, the controller directs the surplus of heat to the heat storage. In the case the CHP does not have enough heat and the building requires more heat to maintain comfort then the heat storage will pump heat back into the heat network. If the combined CHP and thermal store heat supplies still cannot provide enough heat, the gas boiler control operates to top up any heat supply deficit.

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Chapter Five

Results

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5.1. Introduction

This chapter shows how the local energy system works and how the controller can control both sides of the system: the electrical side and the heat energy system side minute by minute and second by second. However, the results of the data in this chapter belong to the Copperas

Hill Building Project (Liverpool John Moores University, Liverpool) and

the results obtained using MATLAB/Simulink modelling and simulation software. The other two cases studies (Green Bank student village and Media city in Manchester) are used for calibration and validation the MATLAB model and to be sure the control methodology can work in different criteria, conditions and any number of zones. The results however, in this chapter are divided into two scenarios to show the benefit and the advantages of using Local energy with CHPV system rather than using the ordinary method (using the national grid for electricity and the Gas boiler for heating) as show in the second scenario and how much the new system can save CO2 emission and running cost.

The two scenarios are:

First scenario: the local energy system is run by a CHP engine with

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system. This local energy system is controlled by the new control system. However, the results will show:

1- the controllability of the control system on the temperatures inside each zone independently. Which consists of three stages:

• Control the zones temperatures without a gas boiler but

with an electrical cooling system (published in [112]). • Control the zones temperatures with a gas boiler but

without an electrical cooling system (published in [113]). • Control the zones temperatures with a gas boiler and with

an electrical cooling system. This system is the subject of this thesis.

2- the controllability of the control system on electrical demand and how it responds second by second to variations in electrical demand.

3- The controllability of the control system on the CHP engine and amount of fuel injected inside it (depending on the electrical load), hot water network, heat storage, photovoltaics and gas boiler. 4- Show the amount of CO2 emissions within the local energy system

and compare it to the national grid in terms of reduced emissions and economic benefits.

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5- Finally, the efficiency of the local energy system over a full year- adapting to the four seasons.

The second scenario: the CHP engine and the heat storage turns off

and runs the system solely by the national grid for electrical demand and a gas boiler for heat demand. This is achieved by the same system and the same controller which controls the temperature in the five zones, to give the same ambient temperature.

In other words, the same results are achieved with the same controller but in two different scenarios from two different sources of energy supply. Thereby, the use of the CHPV system yields economic benefits and reduced CO2 emissions.

Finally, the system increases reliability, as it uses the national grid as a secondary temporary source of energy in emergency scenarios or in any situation where the electrical demand is higher than the CHPV engine size.

For example, if the CHPV engine and heat storage turned off for any reason (maintenance, faults, fuel running out or natural disasters etc.) the controller will send a signal to import electrical energy from the national grid.

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