Environmental impacts of small-scale hybrid energy systems: Coupling solar photovoltaics and lithium-ion batteries

One of the benefits of hybrid solar PV-battery systems is that they can reduce grid dependency and help balance electricity supply and demand. However, their environmental impacts and benefits remain underexplored. This study considers for the first time life cycle environmental impacts of domestic-scale PV-battery systems in Turkey, integrating multi-crystalline PV and lithium-ion battery. The impacts were estimated for both individual installations and at the national level, considering different regions across the country and taking into account their insolation and other climatic differences. Electricity generation and storage were modelled on an hourly basis taking into account consumer behaviour. The results show that the system can meet between 12.5% and 18.4% of the household's annual electricity needs. On a life cycle basis, it generates 4.7-8 times more energy than it consumes. Solar PV is the major contributor to most impacts (75%-81%). An exception is human toxicity which is mainly due to the battery (66%). The hybrid system has 1.6-82.6 times lower impacts than grid electricity. Assuming a very modest uptake at the national level (2%-8%), the use of hybrid systems would save 558,000 t CO₂-eq./yr compared to grid electricity. Thus, these results demonstrate clearly the environmental benefits of these hybrid systems. Together with the financial and energy security benefits for both the country and the consumer, this provides a strong impetus for their wider deployment. However, this will be difficult to achieve, as there are no incentives for battery storage. Therefore, it is recommended that relevant legislation be introduced to stimulate future uptake of hybrid PV-battery systems.

An optimization model for carbon capture & storage/utilization vs. carbon trading: A case study of fossil-fired power plants in Turkey

We consider fossil-fired power plants that operate in an environment where a cap and trade system is in operation. These plants need to choose between carbon capture and storage (CCS), carbon capture and utilization (CCU), or carbon trading in order to obey emissions limits enforced by the government. We develop a mixed-integer programming model that decides on the capacities of carbon capture units, if it is optimal to install them, the transportation network that needs to be built for transporting the carbon captured, and the locations of storage sites, if they are decided to be built. Main restrictions on the system are the minimum and maximum capacities of the different parts of the pipeline network, the amount of carbon that can be sold to companies for utilization, and the capacities on the storage sites. Under these restrictions, the model aims to minimize the net present value of the sum of the costs associated with installation and operation of the carbon capture unit and the transportation of carbon, the storage cost in case of CCS, the cost (or revenue) that results from the emissions trading system, and finally the negative revenue of selling the carbon to other entities for utilization. We implement the model on General Algebraic Modeling System (GAMS) by using data associated with two coal-fired power plants located in different regions of Turkey. We choose enhanced oil recovery (EOR) as the process in which carbon would be utilized. The results show that CCU is preferable to CCS as long as there is sufficient demand in the EOR market. The distance between the location of emission and location of utilization/storage, and the capacity limits on the pipes are an important factor in deciding between carbon capture and carbon trading. At carbon prices over $15/ton, carbon capture becomes preferable to carbon trading. These results show that as far as Turkey is concerned, CCU should be prioritized as a means of reducing nation-wide carbon emissions in an environmentally and economically rewarding manner. The model developed in this study is generic, and it can be applied to any industry at any location, as long as the required inputs are available.

Deciding between carbon trading and carbon capture and sequestration: an optimisation-based case study for methanol synthesis from syngas

The economic and technical feasibility of carbon capture and sequestration (CCS) systems are gaining importance as CO2 emission reduction is becoming a more pressing issue for parties from production sectors. Public and private entities have to comply with national schemes imposing tighter limits on their emission allowances. Often these parties face two options as whether to invest in CCS or buy carbon credits for the excess emissions above their limits. CCS is an expensive system to invest in and to operate. Therefore, its feasibility depends on the carbon credit prices prevailing in the markets now and in the future. In this paper we consider the problem of installing a CCS unit in order to ensure that the amount of CO2 emissions is within its allowable limits. We formulate this problem as a non-linear optimisation problem where the objective is to maximise the net returns from pursuing an optimal mix of the two options described above. General Algebraic Modelling Systems (GAMS) software was used to solve the model. The results were found to be sensitive to carbon credit prices and the discount rate, which determines the choices with respect to the future and the present. The model was applied to a methanol synthesis plant as an example. However, the formulation can easily be extended to any production process if the CO2 emissions level per unit of physical production is known. The results showed that for CCS to be feasible, carbon credit prices must be above 15 Euros per ton. This value, naturally, depends on the plant-specific data, and the costs we have employed for CCS. The actual prices (≈5 Euros/ton CO2) at present are far from encouraging the investors into CCS technology.