Modelling of an integrated gas and electricity network with significant wind capacity

The large scale integration of wind generation capacity into an electricity network poses technical as well as economic challenges. In this research, three major challenges introduced by wind including non-correlated power output from geographically dispersed wind farms, wind variability and wind uncertainty were studied. In order to address each of the aforementioned challenges an appropriate modelling approach and case studies were used. The impacts of power output from dispersed wind farms on the Great Britain transmission reinforcement were studied using an optimal DC load flow combined with a power generation model. It was shown that Western and Eastern HVDC links play a crucial role to bypass the Scotland to England transmission bottleneck. The impacts of wind variability on the GB gas and electricity network were investigated through application of the Combined gas and Electricity Network (CGEN) Model. Additional gas storage capacity was shown to be an efficient option to compensate for wind variability. Two-stage and multi-stage stochastic programming models were developed to examine the impact of wind forecast uncertainty on the GB electricity and gas networks. Stochastic modelling approaches were shown to be efficient methods for scheduling and operating the system under wind uncertainty. The key contributions of this thesis are the investigation of the impacts of wind generation variability on the gas network, and development of twostage and multi-stage stochastic programming models of integrated gas and electricity network.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Modelling of an integrated gas and electricity network with significant wind capacity

The large scale integration of wind generation capacity into an electricity network poses technical as well as economic challenges. In this research, three major challenges introduced by wind including non-correlated power output from geographically dispersed wind farms, wind variability and wind uncertainty were studied. In order to address each of the aforementioned challenges an appropriate modelling approach and case studies were used. The impacts of power output from dispersed wind farms on the Great Britain transmission reinforcement were studied using an optimal DC load flow combined with a power generation model. It was shown that Western and Eastern HVDC links play a crucial role to bypass the Scotland to England transmission bottleneck. The impacts of wind variability on the GB gas and electricity network were investigated through application of the Combined gas and Electricity Network (CGEN) Model. Additional gas storage capacity was shown to be an efficient option to compensate for wind variability. Two-stage and multi-stage stochastic programming models were developed to examine the impact of wind forecast uncertainty on the GB electricity and gas networks. Stochastic modelling approaches were shown to be efficient methods for scheduling and operating the system under wind uncertainty. The key contributions of this thesis are the investigation of the impacts of wind generation variability on the gas network, and development of twostage and multi-stage stochastic programming models of integrated gas and electricity network

Quantification of flexibility from the thermal mass of residential buildings in England and Wales

The increased integration of variable renewable generation into the power systems, along with the phase-out of fossil-based power stations, necessitate procuring more flexibility from the demand sectors. The electrification of the residential heat sector is an option to decarbonise the heat sector in the United Kingdom. The inherent flexibility that is available in the residential heat sector, in the form of the thermal inertia of buildings, is expected to play an important role in supporting the critical task of short-term balancing of electricity supply and demand. This paper proposes a method for characterising the locally aggregated flexibility envelope from the electrified residential heat sector, considering the most influential factors including outdoor and indoor temperature, thermal mass and heat loss of dwellings. Applying the method to England and Wales as a case study, demonstrated a significant potential for a temporary reduction of electricity demand for heating even during cold days. For a scenario envisaged a fully electrified residential heat sector in England and Wales, total electricity demand reductions of approximately 25 GW and 85 GW were shown to be achievable for the outdoor temperature of 10 °C and -5 °C, respectively. Improving the energy performance of the housing stock in England and Wales was shown to reduce the magnitude of available flexibility to approximately 18 GW and 60 GW for the outdoor temperature of 10 °C and -5 °C, respectively. This is due to the use of smaller size heat pumps in the more efficient housing stock. However, the impact of the buildings' retrofit on their thermal mass and consequently on the duration of the flexibility provision is uncertain

Benefits of demand-side response in combined gas and electricity networks

Active demand side response (DSR) will provide a significant opportunity to enhance the power system flexibility in the Great Britain (GB). Although electricity peak shaving has a clear reduction on required investments in the power system, the benefits on the gas supply network have not been examined. Using a Combined Gas and Electricity Networks expansion model (CGEN+), the impact of DSR on the electricity and gas supply systems in GB was investigated for the time horizon from 2010 to 2050s. The results showed a significant reduction in the capacity of new gas-fired power plants, caused by electricity peak shaving. The reduction of gas-fired power plants achieved through DSR consequently reduced the requirements for gas import capacity up to 90 million cubic meter per day by 2050. The cost savings resulted from the deployment of DSR over a 50-year time horizon from 2010 was estimated to be around £60 billion for the GB power system. Although, the cost saving achieved in the gas network was not significant, it was shown that the DSR will have a crucial role to play in the improvement of security of gas supply

Quantification of flexibility of a district heating system for the power grid

District heating systems (DHS) that generate/consume electricity are increasingly used to provide flexibility to power grids. The quantification of flexibility from a DHS is challenging due to its complex thermal dynamics and time-delay effects. This paper proposes a three-stage methodology to quantify the maximum flexibility of a DHS. The DHS is firstly decomposed into multiple parallel subsystems with simpler topological structures. The maximum flexibility of each subsystem is then formulated as an optimal control problem with time delays in state variables. Finally, the available flexibility from the original DHS is estimated by aggregating the flexibility of all subsystems. Numerical results reveal that a DHS with longer pipelines has more flexibility but using this flexibility may lead to extra actions in equipment such as the opening position adjustment of valves, in order to restore the DHS to normal states after providing flexibility. Impacts of the supply temperature of the heat producer, the heat loss coefficient of buildings and the ambient temperature on the available flexibility were quantified

Electricity Storage in Local Energy Systems

Traditionally, power system operation has relied on supply side flexibility from large fossil-based generation plants to managed swings in supply and/or demand. An increase in variable renewable generation has increased curtailment of renewable electricity and variations in electricity prices. Consumers can take advantage of volatile electricity prices and reduce their bills using electricity storage. With reduced fossil-based power generation, traditional methods for balancing supply and demand must change. Electricity storage offers an alternative to fossil-based flexibility, with an increase expected to support high levels of renewable generation. Electrochemical storage is a promising technology for local energy systems. In particular, lithium-ion batteries due to their high energy density and high efficiency. However, despite their 89% decrease in capital cost over the last 10 years, lithium-ion batteries are still relatively expensive. Local energy systems with battery storage can use their battery for different purposes such as maximising their self-consumption, minimising their operating cost through energy arbitrage which is storing energy when the electricity price is low and releasing the energy when the price increases, and increasing their revenue by providing flexibility services to the utility grid. Power rating and energy capacity are vitally important in the design of an electricity storage system. A case study is given for the purpose of providing a repeatable methodology for optimally sizing of a battery storage system for a local energy system. The methodology can be adapted to include any local energy system generation or demand profile

Revenue stacking for behind the meter battery storage in energy and ancillary services markets

Several sources of revenue are available for battery storage systems that can be stacked to further increase revenue. Typically, price arbitrage is used to gain revenue from battery storage. However, additional revenue can be gained from participation in ancillary services such as frequency response. This study presents a linear optimisation approach to account for local energy system participation in the wholesale day-ahead electricity market and multiple frequency response services. The methodology was applied to a school case study. A breakdown of market revenue and value of investment is presented for five operating strategies. The value of availability revenue and response energy revenue are distinguished for frequency response services. Finally, the impact of revenue stacking on battery degradation is assessed. The results show that local energy systems can decrease their operating costs and improve battery storage investment viability by stacking multiple revenues, whilst reducing degradation and increasing lifetime

Quantifying the value of distributed battery storage to the operation of a low carbon power system

Battery storage provides flexibility to the power system and supports the increased integration of renewable energy sources. Distributed battery storage systems that are behind the meter are operated by their local owners, whose objectives may not align with those of the national power system. This paper presents a Bilevel optimisation approach to investigate the exchange of electricity between distributed battery storage and the national power system. The independent operating objectives of the battery storage systems are explicitly considered to assess their impact on the operation of the national power system. A comparison with a Centralised optimisation approach, that assumes a single objective function for the whole system, shows that the Bilevel optimisation approach captures the independencies of distributed battery storage objectives, while accounting for its interactions with the wider power system. The results show that the Centralised optimisation approach tends to overestimate the value of distributed battery storage for the power system. The results also highlight the influence of the retail contract structure in maximising the value of distributed battery storage for the national power system