Optimisation algorithms for the charge dispatch of plug-in vehicles based on variable tariffs

Plug-in vehicles powered by renewable energies are a viable way to reduce local and total emissions and could also support a highly efficient grid operation. Indirect control by variable tariffs is one option to link charging or even discharging time with the grid load and the renewable energy production. Algorithms are required to develop tariffs and evaluate grid impacts of variable tariffs for electric vehicles (BEV) as well as to schedule the charging process optimisation. Therefore a combinatorial optimisation algorithm is developed and an algorithm based on graph search is used and customised. Both algorithms are explained and compared by performance and adequate applications. The developing approach and the correctness of the quick combinatorial algorithm are proved within this paper. For vehicle to grid (V2G) concepts, battery degradation costs have to be considered. Therefore, common life cycle assumptions based on the battery state of charge (SoC) have been used to include degradation costs for different Li-Ion batteries into the graph search algorithm. An application of these optimisation algorithms, like the onboard dispatcher, which is used in the German fleet test "Flottenversuch Elektromobiliät". Grid impact calculations based on the optimisation algorithm are shown. --BEV,V2G,Plug-In-Vehicles (PHEV),optimisation,mobile dispatcher,demand side management,charging,combinatorial algorithm,graph search algorithm,indirect control by variable tariffs

A means to an industrialisation end? Demand side management in Nigeria

Electricity is essential for economic development and industrialisation processes. Balancing demand and supply is a recurrent problem in the Nigerian electricity market. The aim of this work is to assess the technical and economic potential of Demand Side Management (DSM) in Nigeria given different future levels of industrialisation. The paper places industrialisation at the centrefold of the appraisal of DSM potential in Nigeria. It does so by designing industrialisation scenarios and consequently deriving different DSM penetration levels using a cost-optimisation model. Findings show that under the high industrialisation scenario by the year 2050 DSM could bring about 7 billion USD in cumulative savings thanks to deferred investment in new generation and full deployment of standby assets along with interruptible programmes for larger industrial users. The paper concludes by providing policy recommendations regarding financial mechanisms to increase DSM deployment in Nigeria. The focus on DSM serves to shift the policy debate on electricity in Nigeria from a static state versus market narrative on supply to an engagement with the agency and influence on industrial end-users

Secure and cost-effective operation of low carbon power systems under multiple uncertainties

Power system decarbonisation is driving the rapid deployment of renewable energy sources (RES) like wind and solar at the transmission and distribution level. Their differences from the synchronous thermal plants they are displacing make secure and efficient grid operation challenging. Frequency stability is of particular concern due to the current lack of provision of frequency ancillary services like inertia or response from RES generators. Furthermore, the weather dependency of RES generation coupled with the proliferation of distributed energy resources (DER) like small-scale solar or electric vehicles permeates future low-carbon systems with uncertainty under which legacy scheduling methods are inadequate. Overly cautious approaches to this uncertainty can lead to inefficient and expensive systems, whilst naive methods jeopardise system security. This thesis significantly advances the frequency-constrained scheduling literature by developing frameworks that explicitly account for multiple new uncertainties. This is in addition to RES forecast uncertainty which is the exclusive focus of most previous works. The frameworks take the form of convex constraints that are useful in many market and scheduling problems. The constraints equip system operators with tools to explicitly guarantee their preferred level of system security whilst unlocking substantial value from emerging and abundant DERs. A major contribution is to address the exclusion of DERs from the provision of ancillary services due to their intrinsic uncertainty from aggregation. This is done by incorporating the uncertainty into the system frequency dynamics, from which deterministic convex constraints are derived. In addition to managing uncertainty to facilitate emerging DERs to provide legacy frequency services, a novel frequency containment service is designed. The framework allows a small amount of load shedding to assist with frequency containment during high RES low inertia periods. The expected cost of this service is probabilistic as it is proportional to the probability of a contingency occurring. The framework optimally balances the potentially higher expected costs of an outage against the operational cost benefits of lower ancillary service requirements day-to-day. The developed frameworks are applied extensively to several case studies. These validate their security and demonstrate their significant economic and emission-saving benefits.Open Acces

Frequency response from aggregated V2G chargers with uncertain EV connections

Fast frequency response (FR) is highly effective at securing frequency dynamics after a generator outage in low inertia systems. Electric vehicles (EVs) equipped with vehicle to grid (V2G) chargers could offer an abundant source of FR in future. However, the uncertainty associated with V2G aggregation, driven by the uncertain number of connected EVs at the time of an outage, has not been fully understood and prevents its participation in the existing service provision framework. To tackle this limitation, this paper, for the first time, incorporates such uncertainty into system frequency dynamics, from which probabilistic nadir and steady state frequency requirements are enforced via a derived moment-based distributionally-robust chance constraint. Field data from over 25,000 chargers is analysed to provide realistic parameters and connection forecasts to examine the value of FR from V2G chargers in annual operation of the GB 2030 system. The case study demonstrates that uncertainty of EV connections can be effectively managed through the proposed scheduling framework, which results in annual savings of Misplaced &6,300 or 37.4 tCO2 per charger. The sensitivity of this value to renewable capacity and FR delays is explored, with V2G capacity shown to be a third as valuable as the same grid battery capacity

Hybrid nuclear-solar power

Nuclear and solar power, in the form of concentrated solar power (CSP), play a significant role in achieving the ambitious global targets of reducing greenhouse emissions and guaranteeing security of energy supply. However, both power generation technologies still require further development to realise their full potential, especially in terms of attaining economic load following operations and higher thermal efficiencies. Therefore, the aim of this research is to investigate and thermo-economically evaluate the available options of upgrading the flexibility and enhancing the thermal efficiency of nuclear and solar power generation technologies (i.e., through the integration with thermal energy storage (TES) and by hybridising both power generation technologies) while providing reasonable economic returns. The thesis starts with describing the development and validation of several thermodynamic and economic computational models and the formulation of the whole-energy system model. The formulated models are utilised to perform several thermo-economic studies in the field of flexible nuclear and solar power, and to quantify the economic benefits that could result from enhancing the flexibility of nuclear power plants from the whole-energy system perspective. The studies conducted in this research are: (i) a thermo-economic assessment of extending the conventional TES system in direct steam generation (DSG) CSP plants; (ii) a thermo-economic evaluation of upgrading the flexibility of nuclear power plants by the integration with TES and secondary power generation systems; (iii) an investigation of the role of added flexibility in future low-carbon electricity systems; and (iv) a design and operation analysis of a hybrid nuclear-solar power plant. The most common TES option in DSC CSP plants is steam accumulation. This conventional option is constrained by temperature and pressure limits, leading to lower efficiency operations during TES discharging mode. Therefore, the option of integrating steam accumulators with sensible-heat storage in concrete to provide higher-temperature superheated steam is thermo-economically investigated in this research, taking an operational DSG CSP plant as a case study. The results show that the integrated concrete-steam TES (extended) option delivers 58% more electricity with a 13% enhancement in thermal efficiency during TES discharging mode, compared to the conventional steam accumulation (existing) configuration. With an estimated additional investment of $4.2M, the projected levelised cost of electricity (LCOE) and the net present value (NPV) for the considered DSG CSP plant with the extended TES option are respectively 6The option of upgrading the flexibility of nuclear power plants through the integration with TES and secondary power generation systems is investigated for two conventional nuclear reactors, a 670-MWel advanced gas-cooled reactor (AGR) and a 1610-MWel European pressurised reactor (EPR). In both investigated case studies, the reactors are assumed to continuously operate at full rated thermal power, while load following operations are conducted through the integrated TES tanks and secondary power generators. Based on the designed TES and secondary power generation systems, the AGR-based configuration can modulate the power output between 406 MWel and 822 MWel, while the EPR-based configuration can operate flexibly between 806 MWel and 2130 MWel. The economic analysis results demonstrate that the economics of added flexibility are highly dependent on: (i) the size of the TES and the secondary power generation systems; (ii) the number of TES charge/discharge cycles per day; and (iii) the ratio and difference between off-peak and peak electricity prices. Replacing conventional EPR-based nuclear power plants with added flexibility ones is found to generate whole-system cost savings between$30.4M/yr and $111M/yr. At an estimated cost of added flexibility of$53.4M/yr, the proposed flexibility upgrades appear to be economically justified with net system economic benefits ranging from $5.0M/yr and$39.5M/yr for the examined low-carbon scenarios, provided that the number of flexible nuclear plants in the system is small. The concept of hybridising a small modular reactor (SMR) with a solar-tower CSP integrated with two-tank molten salt TES system, with the aim of achieving economically enhanced load following operations and higher thermal efficiency levels, is also thermo-economically investigated in this research. The integration of both technologies is achieved by adding a solar-powered superheater and a reheater to a standalone SMR. The obtained results demonstrate that hybridising nuclear and solar can offer a great amount of flexibility (i.e., between 50% and 100% of nominal load of 131 MWel) with the SMR continuously operated at full rated thermal power output. Furthermore, the designed hybrid power plant is able to operate at higher temperatures due to the addition of the solar superheater, resulting in a 15% increase of thermal efficiency compared to nuclear-only power plant. Moreover, the calculated specific investment cost and the LCOE of the designed hybrid power plant are respectively 5410 $/kWel and 77$/MWhel, which are 2% and 4% lower than those calculated for the nuclear-only power plant.Open Acces

Bi-directional coordination of plug-in electric vehicles with economic model predictive control

© 2017 by the authors. Licensee MDPI, Basel, Switzerland. The emergence of plug-in electric vehicles (PEVs) is unveiling new opportunities to de-carbonise the vehicle parcs and promote sustainability in different parts of the globe. As battery technologies and PEV efficiency continue to improve, the use of electric cars as distributed energy resources is fast becoming a reality. While the distribution network operators (DNOs) strive to ensure grid balancing and reliability, the PEV owners primarily aim at maximising their economic benefits. However, given that the PEV batteries have limited capacities and the distribution network is constrained, smart techniques are required to coordinate the charging/discharging of the PEVs. Using the economic model predictive control (EMPC) technique, this paper proposes a decentralised optimisation algorithm for PEVs during the grid-To-vehicle (G2V) and vehicle-To-grid (V2G) operations. To capture the operational dynamics of the batteries, it considers the state-of-charge (SoC) at a given time as a discrete state space and investigates PEVs performance in V2G and G2V operations. In particular, this study exploits the variability in the energy tariff across different periods of the day to schedule V2G/G2V cycles using real data from the university's PEV infrastructure. The results show that by charging/discharging the vehicles during optimal time partitions, prosumers can take advantage of the price elasticity of supply to achieve net savings of about 63%

Market Structure Scenarios in International Steam Coal Trade

The seaborne steam coal market changed in recent years. Trade volumes grew dynamically, important players emerged and since 2007 prices increased significantly and remained relatively high since then. In this paper we analyse market equilibria in the years 2006 and 2008 by testing for two possible market structure scenarios in this market: perfect competition and an oligopoly setup with major exporters competing in quantities. We conclude from our results that international steam coal trade is not perfectly competitive as there is a large spread between marginal costs and prices and a low capacity utilisation in 2008. Further, trade flows are generally more diversified in reality than in the competitive scenario. However, also the Cournot scenarios fail to accurately explain real market outcomes. We conclude that only more sophisticated models of strategic behaviour can predict market equilibria in international steam coal trade.Steam coal trade; Mining Costs; Market Structure