Battery energy storage systems (BESS) are receiving great attention due to their ability in maximizing self-consumption and energy arbitrage. However, in many countries, BESS profitability is still questionable without subsidy due to their high capital costs. This paper proposes an open-source generic tool to provide comprehensive techno-economic analysis on the small-scale PV/BESS. The proposed tool utilizes real-time BESS control method that has been validated using real experimental measurements in addition to integrating a reliable degradation model to determine the loss in savings due to capacity degradation. The profitability is investigated by conducting different cost-benefit analyses for the PV and BESS. An optimization layer is introduced to find the optimal PV/BESS sizes that boost investment profitability by maximizing the net present value. A detailed case study is presented for a household in the U.K. under three different tariff structures that consider practical parameters and assumptions. Furthermore, sensitivity analyses are performed to evaluate the impact of the cost-benefit analysis assumptions on the PV/BESS sizing and profitability. Finally, the BESS investment viability is investigated over the next few years for different investment expectations to answer the question of when the BESS should be installed to be a viable economic-attractive option in the U.K.

Distribution system operators are attracted to battery energy storage systems (BESS) as a smart option to support the distribution network. However, due to its high capital cost, BESS profitability is dependent on the participation in multiple services to stack revenues and rationalize their existence. Yet, revenue stacking is location-dependent based on the available services and regulations. In this paper, specific revenue stacking frameworks are proposed for BESS installed in modern distribution networks that consider the conflicts and synergies that may occur from the involvement in multiple services in practice. A simple yet effective sizing formulation is introduced to find the BESS system size based on the primary service which is to solve the distribution network violations. BESS scheduling is simulated in accordance with the proposed frameworks to maximize the stackable profits for a case study of Northern Ireland. The BESS profitability is investigated through cost-benefit analyses of different technologies for the sole and stacked services. The results show that revenue stacking can boost the annual revenues by 129% with a payback period of 8 years on average. The presented insights are useful for network operators and energy investors in understanding and assessing the profitability of different BESS technologies for various applications.

The integration of battery energy storage systems (BESS) in the electrical grid is accelerating to mitigate the challenges associated with the rapid deployment of low carbon technologies (LCTs). This work investigates the ability of BESS to provide the power networks with important ancillary services such as peak shaving and grid power levelling through two case studies conducted in collaboration with Northern Ireland's distribution network operator. A powerful approach consisting of two strategies is developed to operate the BESS powerfully to enhance the operation of the distribution network. The first strategy is day‐ahead scheduling that aims to dispatch the distributed BESS to smooth the grid power and mitigate voltage and lines stresses. A powerful demand forecasting algorithm is utilised to efficiently apply the day‐ahead scheduling. The second strategy is a real‐time operation to flatten the grid power which can be used separately or to adjust the results obtained from the day‐ahead strategy against the forecasting errors. The proposed approach was validated using real measurements and applied to an 11 kV distribution network located in Northern Ireland, UK. The BESS expected revenues from the participation in different services available in the island of Ireland are quantified and the degradation is considered.

This paper proposes a two‐phase optimization methodology to optimally dispatch the active/reactive power of battery energy storage systems (BESS) installed on the medium voltage distribution network to manage the violations and enhance the power quality and security. The first phase is look‐ahead scheduling that aims to flatten the grid power curve and optimize the network power factor over the scheduling horizon using forecasted demand and generation. The second phase is a real‐time model predictive control (MPC) introduced to adjust the BESS real power setpoints against network violations due to high uncertainties associated with the renewable generation and low carbon technologies as well as other unexpected events. Simulations were carried out for an actual 11 kV, 53‐node distribution network located in Northern Ireland for two case studies representing the winter and summer. The results demonstrate the effectiveness of the proposed methodology in enhancing the network operation through optimizing the power factor, reducing line losses, and mitigating stresses. Sudden over/under voltage events were solved through the real‐time phase efficiently without affecting the power factor or the line losses in a fast manner with a computation time of 0.52 s/time‐point which makes it suitable for real‐time control implementation.

The rapid deployment of renewable‐based generation to meet the net‐zero carbon targets has affected the wholesale energy paradigm. In the island of Ireland, the Single Electricity Market (SEM) aims to deliver high levels of supply security, reliability, and transparency through multiple markets with different trading time frames and clearing procedures. This paper proposes a powerful methodology to maximize the revenues from the participation in the SEM. A forecasting model of four successive stages based on neural networks is proposed to predict the demand and system marginal prices of the SEM ex‐ante markets. An energy arbitrage optimization framework is proposed for battery energy storage systems (BESS) to maximize the arbitrage profits. The methodology efficacy is validated by achieving 91.1% selling accuracy, 97.9% buying accuracy, and 85.1% energy arbitrage net accuracy of the ideal case where the SEM data is perfectly‐known for three consecutive months. Furthermore, the BESS degradation is evaluated and a cost‐benefit analysis is introduced to evaluate the economic feasibility of BESS participating in the SEM ex‐ante markets. The results reveal that the participation of BESS in the SEM solely is not profitable, however, under stacked revenues arrangement, the proposed methodology can be applied to boost the BESS revenues.

Most modern distribution networks are experiencing an energy evolution to satisfy the need of sustainable, secure and clean sources of energy. New technologies are driving this transition, including photovoltaics, energy storage systems and electric vehicles. The integration and deployment of these technologies in the distribution network is having a positive impact on system efficiency. However, their behavior in the power system introduces technical challenges such as reverse power flow, voltage variation and other power quality issues. The integration of these technologies requires careful planning and operation to maintain or improve system stability and reliability. This work reviews the challenges imposed by deploying these low carbon technologies on low voltage systems. The main contributions of this study can be summarized as follows: Firstly, it generally reviews the solution methodologies and power management strategies applied in the distribution network in the presence of low carbon technologies. Secondly, it outlines some important facts and statistics about their deployment. Finally, it discusses the energy evolution of the Northern Ireland network highlighting challenges and solutions and providing recommendations for future research.