Meet Peak Demand Research Articles

Renewable, Flexible, and Storage Capacities: Friends or Foes?

Problem definition: More than 99% of the new power generation capacity to be installed in the United States from 2023 to 2050 will be powered by wind, solar, and natural gas. Additionally, large-scale battery systems are planned to support power systems. It is paramount for policymakers and electric utilities to deepen the understanding of the operational and investment relations among renewable, flexible (natural gas-powered), and storage capacities. In this paper, we optimize both the joint operations and investment mix of these three types of resources, examining whether they act as investment substitutes or complements. Methodology/results: Using stochastic control theory, we identify and prove the structure of the optimal storage control policy, from which we determine various pairs of charging and discharging operations. We find that whether storage complements or substitutes other resources hinges on the operational pairs involved and whether executing these pairs is constrained by charging or discharging. Through extensive numerical analysis using data from a Florida utility, government agencies, and industry reports, we demonstrate how storage operations drive the investment relations among renewable, flexible, and storage capacities. Managerial implications: Storage and renewables substitute each other in meeting peak demand; storage complements renewables by storing surplus renewable output; renewables complement storage by compressing peak periods, facilitating peak shaving and displacement of flexible capacity. These substitution and complementary effects often coexist, and the dominant effect can alternate as costs change. A thorough understanding of these relations at both operational and investment levels empowers decision makers to optimize energy infrastructure investments and operations, thereby unlocking their full potential. Funding: This research was supported in part by Lilly Endowment, Inc., through its support for the Indiana University Pervasive Technology Institute. This research was also supported by Kelley School of Business, Indiana University, and Haslam College of Business, University of Tennessee. O. Q. Wu thanks Grant Thornton for their generous support. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2023.0068 .

Changing economics of China’s power system suggest that batteries and renewables may be a lower cost way to meet peak demand growth than coal

Concerns around reliability in China's electricity sector have rekindled interest in a traditional solution: building more coal-fired generation. However, over the past decade China's electricity sector has seen significant changes in supply costs, demand patterns, and regulation and markets, with falling costs for renewable and storage generation, "peakier" demand, and the creation of wholesale markets. These changes suggest that traditional approaches to evaluating the economics of different supply options may be outdated. This paper illustrates how a net capacity cost metric- fixed costs minus net market revenues- might be a useful metric for evaluating supply options to meet peak demand growth in China. Using a simplified example with recent resource cost data, the paper illustrates how, with a net capacity cost metric, electricity storage and solar PV may be a more cost-effective option for meeting peak demand growth than coal-fired generation.

Optimal sizing of photovoltaic-battery system for peak demand reduction using statistical models

Due to increasing environmental concerns and demand for clean energy resources, photovoltaic (PV) systems are becoming more prevalent. Considering that in several instances, customers pay for both energy and power, PV installations not only must reduce the customers’ energy purchases but also lower their peak demand for maximum financial benefits. However, in many cases, the peak demand does not coincide with the peak of photovoltaic generation. To address this issue, excess energy generated during low-demand periods can be stored in a battery, which can then be used to meet peak demand. Determining the optimal size of photovoltaic and battery components while ensuring system performance and financial benefits is significantly challenging. This study proposes a novel statistical methodology for optimizing PV-battery system size. In the proposed method, the PV-battery system must meet peak demand thresholds with a specific probability. Further, cost and benefit functions are used for financial evaluation. Finally, Monte Carlo simulations, developed using time series clustering and a Bayesian model are utilized to assess system performance and financial feasibility.

Battery Earth: using the subsurface at Boulby underground laboratory to investigate energy storage technologies

Renewable energy provides a low-carbon alternative to power generation in the UK. However, the resultant supply varies on daily, weekly and seasonal cycles, such that for green energies to be fully exploited new grid-scale energy storage systems must be implemented. Two pilot facilities in Germany and the United States have demonstrated the potential of the Earth as a battery to store compressed air, using off-peak surplus energy. Natural accumulations of salt (halite deposits) in the UK represent a large and untapped natural storage reservoir for compressed air with the ability to provide instantaneous green energy to meet peak demand. To realise the potential of this emerging technology, a detailed knowledge of the relationship between mechanics, chemistry and geological properties is required to optimise cavern design, storage potential and economic feasibility. The variable stresses imposed on the rock matrix by gas storage, combined with the cyclic nature of cavern pressurisation are barriers to deployment that need to be addressed to enable large-scale adoption of schemes. Well-designed field experiments are a lynchpin for advancing research in this area, especially when supported by state-of-the-art characterisation and modelling techniques. The research facility at STFC’s Boulby Underground Laboratory presents the ideal location to tackle these fundamental issues to optimise “Battery Earth”.

Techno-economic investigation of hybrid peaker plant and hydrogen refuelling station

The power and transport sectors are responsible for significant emissions of greenhouse gases. Therefore, it is imperative that substantial efforts are directed towards the decarbonisation of these industries. This study establishes a combined-solar-wind system's economic and technical practicality for producing hydrogen for an onsite hydrogen refuelling station (HRS) and electricity to meet peak demand. To minimise the levelised cost of electricity and maximise the system's reliability at different commercial locations in South Africa, the dual-objective optimisation sizing is carried out using Mixed Integer Quadratic Constrained Programming (MICQP) model and was executed with an Advanced Multi-dimensional Modelling System (AIMMS) [61], [62]. The levelised costs of electricity and hydrogen at Johannesburg, Pretoria and Cape Town for 2 MW grid export benchmark are 74.2 $/MWh/5.85 $/kg, 76.3 $/MWh/5.97 $/kg and 50 $/MWh/4.45 $/kg respectively. The CO₂ equivalent emissions (tonnes) are 54,000, 55,800, 59,000 and the corresponding carbon taxes ($) avoided for the locations are 432,100, 446,200, and 472,000 for Johannesburg, Pretoria and Cape Town respectively. The results of the framework show that it can be adopted as a viable and fossil-free replacement for conventional peaking generators.

Yamula barajının hidroelektrik rezervuar işletiminin makine öğrenimi ile simülasyonu

Large-scale reservoirs provide operational flexibility to water managers by storing water during times with higher surface water availability and releasing water when it is most needed. Most large-scale reservoirs serve for multipurpose demands, such as water supply for agricultural, urban and environmental users, hydropower, recreation, fisheries and transportation. Due to its low operating cost, hydropower generation is often maximized in energy systems with mixed hydro and thermal sources. Hydropower generation is also used to meet peak demand by advantage of operating in short notice. This study aims to simulate reservoir operations of the Yamula Dam and hydropower plant using machine learning. Located on the Kızılırmak River, the Yamula Dam is a large-scale multipurpose reservoir with its 3476 million cubic meters storage capacity. Turbine release decisions are learned with Random Forests algorithm. The developed model successfully predict reservoir releases between 2006 and 2015, with a coefficient of determination r2 value of 0.87. Model prediction results are provided, and then hydropower load, generation and revenue are calculated and results are presented. The Yamula Dam generates about 362.3 GWh of energy per year, with an annual average revenue of 14.1 million Dollars.

Evaluating the impact of productive uses of electricity on mini-grid bankability

Mini-grids are discussed as a cost-effective and sustainable solution to provide electricity to populations lacking access, of which the majority reside in sub-Saharan Africa. Projects struggle to be fiscally solvent, however, in part because electricity demand from rural households is low relative to installed mini-grid generation and distribution capacity, making it difficult to recoup investment costs. This paper explores how productive uses of electricity may increase electricity demand and evaluates impacts of increased electrical load to the technical and economic metrics of mini-grid projects. A full cashflow analysis is completed to evaluate business model efficacy for mini-grid developers and investors for a case study of a township in Sierra Leone. Productive uses of electricity are shown to have minimal improvement to the financial viability of residential mini-grid projects, and subsidies are required to reach financial metrics suitable to attract private investment. Of the productive uses investigated, year-round loads had the most positive impact to payback periods. Seasonal loads offer only small improvements to payback period and internal rate of return because they require extra generation assets to meet peak demand in the high season that are left idle or heavily under-loaded during the low season. Overall, the study finds the most effective way to improve financial outcomes through productive uses is to increase the mini-grid load factor with productive uses of electricity that operate year-round.

A Prediction Framework for Turning Period Structures in COVID-19 Epidemic and Its Application to Practical Emergency Risk Management

The goal of this study is to establish a general framework for predicting the so-called critical Turning Period in an infectious disease epidemic such as the COVID-19 outbreak in China early this year. This framework enabled a timely prediction of the turning period when applied to Wuhan COVID-19 epidemic and informed the relevant authority for taking appropriate and timely actions to control the epidemic. It is expected to provide insightful information on turning period for the world's current battle against the COVID-19 pandemic. The underlying mathematical model in our framework is the individual Susceptible-Exposed- Infective-Removed (iSEIR) model, which is a set of differential equations extending the classic SEIR model. We used the observed daily cases of COVID-19 in Wuhan from February 6 to 10, 2020 as the input to the iSEIR model and were able to generate the trajectory of COVID-19 cases dynamics for the following days at midnight of February 10 based on the updated model, from which we predicted that the turning period of CIVID-19 outbreak in Wuhan would arrive within one week after February 14. This prediction turned to be timely and accurate, providing adequate time for the government, hospitals, essential industry sectors and services to meet peak demands and to prepare aftermath planning. Our study also supports the observed effectiveness on flatting the epidemic curve by decisively imposing the Lockdown and Isolation Control Program in Wuhan since January 23, 2020. The Wuhan experience provides an exemplary lesson for the whole world to learn in combating COVID-19.

Dynamic simulation of a novel nuclear hybrid energy system with large-scale hydrogen storage in an underground salt cavern

In this study, a nuclear hybrid energy system (NHES) with large-scale hydrogen storage integrated with a gas turbine cycle is proposed as a flexible system for load following. The proposed system consists of a nuclear reactor, a steam Rankine cycle, a hydrogen electrolyzer, a storage system for hydrogen in an underground salt cavern, and a Brayton cycle that uses hydrogen as fuel to generate additional electricity to meet peak demand. A dynamic mathematical model is developed for each subsystem of the NHES. To evaluate the potential benefits of the system, a one-year study is conducted, using scaled grid demand data from ISO New England. The dynamic simulation results show that the system is capable of meeting the demand of the grid without additional electricity from outside sources for 93% of the year, while decreasing the number of ramping cycles of the nuclear reactor by 92.7%. There is also potential for economic benefits as the system only had to ramp up and down 7.4% of the year, which increased the nuclear capacity factor from 86.3% to 98.3%. The simulation results show that the proposed hybrid system improves the flexibility of nuclear power plants, provides more electricity, and reduces greenhouse gas emissions.

Building-level heat demand mapping of commercial-residential areas for simulated district heating assessments in Montana, Idaho, and Washington

Depending on the climate zone, structure composition, and industry of a place, building heating in the United States can account for 40–60% of total community energy demand. Providing sustainable energy sources to meet this demand is crucial for emissions mitigation. District heating (DH) is energy agnostic, allowing a community to leverage low- or no-emission, locally occurring, natural and fabricated heat sources. The United States, while being the greatest energy consumer on a per capita basis, lacks the heat demand mapping intelligence necessary to plan for DH potential across communities.This work provides a method to map building-level heat demand using energy consumption surveys and property tax information in the absence of proprietary gas and electric utility data. Three demonstration municipalities in this work are from Washington, Idaho, and Montana. With demand mapping readily available in these areas and elsewhere, the policymaker, planner, and developer can quickly assess system potentials using Comsof Heat, a techno-economic simulation software for DH planning. This software auto-routes the necessary pipe networks along the lowest-cost pathways through a community to meet peak demand, providing multi-heat source integration. The constructed heat demand maps from these communities are imported to Comsof Heat to explore the hypothetical energy sources, payback periods, and decarbonization of building stocks using DH.Inconsistencies in structural data exist in property tax information across state, county, and municipal governments. These inconsistences can lead to uncertainties in heat demand mapping that could easily be overcome through greater coordination by local and regional GIS managers. Despite these uncertainties, it is still possible to characterize most commercial-residential heat demand across municipalities in Washington, Idaho, and Montana. These preliminary heat demand maps should be a public-facing product available from governments.

Research of a smart energy system in the internet things

The work considers and investigates the intelligent power system in the Internet of Things. The purpose of the article is to study the intelligent network. The answer to the question «What is a smart energy system?». We compared traditional and smart power systems. Defined measurement infrastructure and technological criteria. Protocols and standards are reviewed. The relevance of the topic is because every day the demand and consumption for electrical energy is growing. The evolution of smart grid concepts in various power grids connects a huge number of devices, many of which are due to outdated automation protocols and internal information systems. Since many of these devices provide little or no indication of the semantics of their data, it is customary to manually create this information, which is cumbersome, expensive, and prone to errors. The Internet of Things is the next step in the evolution of our today’s Internet, where any physical object equipped with computing and communication capabilities can be easily integrated into various areas of our life. Thus, there is a need for an intelligent grid that can effectively solve various aspects of transmission and distribution, reducing the load on the power system, making it reliable and secure. One option to meet peak demand is to reinforce the distribution network with thicker cables and more powerful power systems. Another, more sustainable solution is the introduction of smart grid technology to balance energy demand and supply by increasing the flexibility of the electricity grid through the use of information and communication technologies and remote control in real time, for example, with the Internet of things, artificial intelligence, cloud computing and others. However, security and reliability is seen as one of the main obstacles to the rapid and largescale implementation and deployment of both the IoT concept and smart grid. It is expected that the smart grid and the Internet of Things will revolutionize various spheres of everyday life, industry and business.

The Prediction for COVID-19 Outbreak in China by using the Concept of Term Structure for the Turning Period

This study aims to develop a general framework for predicting the duration of the Turning Period (or Turning Phase) for the COVID-19 outbreak in China that started in late December 2019 from Wuhan. A new concept called the Term Structure for Turning Period (instead of Turning Point) is used for this study, and the framework, implemented into an individual SEIR (iSEIR) model, has enabled a timely prediction of the turning period when applied to Wuhan’s COVID-19 epidemic, and provided the opportunity for relevant authorities to take appropriate and timely actions to successfully control the epidemic. By using the observed daily COVID-19 cases in Wuhan from January 23, 2020 to February 6 (and February 10), 2020 as inputs to the framework it allowed us to generate the trajectory of COVID-19 dynamics and to predict that the Turning Period of COVID-19 outbreak in Wuhan would arrive within one week after February 14. This prediction turned out to be timely and accurate, which has provided adequate time for the government, hospitals and related sectors and services to meet peak demand and to prepare aftermath planning. We want to emphasize that emergency risk management entails the implementation of an emergency plan, where timing the Turning Period is key to express a clear timeline for effective actions. Our study confirms the observed effectiveness of Wuhan’s Lockdown and Isolation control program imposed since January 23, 2020 to the middle of March, 2020 and resulted in swiftly flattened epidemic curve, and Wuhan’s success offers an exemplary lesson for the world to learn in combating COVID-19 pandemic.

Modeling the Idaho National Laboratory Thermal-Energy Distribution System (TEDS) in the Modelica Ecosystem

Integrated energy systems (IES)—including the intimate coupling between thermal generators, the grid, ancillary processes, and energy storage—are becoming increasingly pertinent to the energy grid. To facilitate a better understanding of IES, Idaho National Laboratory (INL) has developed the experimental Thermal Energy Distribution System (TEDS) to test the interoperability of nuclear reactors, energy storage, and ancillary processes in a real-world setting. This paper provides an overview of the development of TEDS within INL’s Modelica dynamic process modeling ecosystem as part of the IES initiative. The model will bridge the gap between lab-scale experimental results and desired grid-scale energy solutions. Two simulation sets were run. The first was a 5-h test simulating a facility shakedown test, putting the facility through five potential operating modes and showcasing the ability of the valving, control sensors, and component controllers to meet system demands. The second case imposed a typical summer day demand on the system from a region with mixed commercial and residential electrical needs. In this case, the generator alone could not meet peak demand but instead required the thermal-storage unit to act as a peaking unit.

Asymmetric risk and fuel neutrality in electricity capacity markets

In many liberalized electricity markets, power generators can receive payments for maintaining capacity through capacity markets. These payments help stabilize generator revenues, making investment in capacity more attractive for risk-averse investors when other outlets for risk trading are limited. Here we develop a heuristic algorithm to solve large-scale stochastic equilibrium models describing a competitive market with incomplete risk trading. Introduction of a capacity mechanism has an asymmetric effect on the risk profile of different generation technologies, tilting the resource mix towards those with lower fixed costs and higher operating costs. One implication of this result is that current market structures may be ill-suited to financing low-carbon resources, the most scalable of which have high fixed costs and near-zero operating costs. Development of new risk trading mechanisms to replace or complement current capacity obligations could lead to more efficient outcomes. Capacity markets are designed to ensure availability of sufficient production capacity to meet peak demand. Mays et al. show that these markets favour technologies such as coal and gas by mitigating their capital investment risks while not compensating for operational risks associated with solar and wind energy.

How big a battery?

Countries are investing in renewable energy such as wind or solar to meet electricity demand and minimize CO2 emissions. Due to the intermittent nature of these energy sources, back-up generating assets or adequate storage is needed to meet peak demand. In this study, we evaluate the extent to which an electricity grid can rely on intermittent renewable energy (wind and solar) if a ‘black box’ battery is used for storage. We examine the potential for 100% generation from wind and solar, as well as scenarios that are consistent with a policy to eliminate coal generation. A constrained optimization model is used that minimizes thermal generating capacity and battery size subject to load and battery constraints. Our application is to the fossil-fuel dependent Alberta electricity system. Our results suggest that it might be difficult and costly to supply the grid with 100% renewable energy. Replacing coal with renewable energy and using natural gas and a battery as back-up would be feasible, but would require a very large battery and result in high costs. Other storage methods should be considered to facilitate increased generation from renewable sources.

Techno-economic assessment and optimization of a hybrid renewable co-supply of electricity, heat and hydrogen system to enhance performance by recovering excess electricity for a large energy consumer

This study attempts to optimize and examine the techno-economic feasibility of off-grid hybrid renewable energy systems (HRES) to satisfy simultaneously electric, heat and hydrogen load of a large energy consumer. An innovative method is adopted so as to recover surplus electricity to generate heat and cut emissions. The system is comprised of solar panels, wind turbine, diesel generator, electrolyzer and boiler to supply 9910 kWh/day of electricity, 14 kg/day of hydrogen and thermal energy in five different major cities in Iran, namely Bandar Abbas, Shiraz, Tabriz, Tehran and Yazd. These figures are computed on average and the thermal load differs according to yearly weather temperature, which are 75, 22, 2000, 5200, 2200 and 1800 kWh/day respectively. To serve this purpose, HOMER Pro software was used and thermal load controller (TLC) (including electric boiler) was added to generate thermal energy by converting excess electricity of renewable energy production. Thus, a decrease in conventional fuel consumption, emissions and cost of energy (COE), as well as an increase in the renewable fraction of HRES without increasing project’s size would be achievable. To meet peak demand and avoid intermittent behavior of HRES, a 1000 kW generator was picked up. Results indicate that recovering extra electricity can enhance renewable fraction by up to 35% and bring down COE and exhausted CO2 by 7.1% and 10.6% respectively, which highlight the necessity of TLC in HRES, chiefly in off-grid systems.

Practical Design and Implementation of Cloud Computing for Power System Planning Studies

The increased penetration of renewable resources and retirement of traditional generation units are posing new challenges to power system operations and planning to meet the ever-growing demand for more computing resources to run large-scale, computationally intensive simulations. As the traditional on-premises infrastructure loses pace to the constantly increasing computing needs, cloud computing has become an attractive addition for increasing average computing capacity, and alternative for meeting peak demands. ISO New England (ISO-NE) pioneered the use of cloud computing technology for large-scale power system simulations, believing it to be the only viable solution that is capable of keeping pace with the growing challenge in the foreseeable future. This paper shares the practical design and implementation of an elastic, on-demand, application-independent cloud platform that ISO-NE deployed in production at the end of 2017. As a secure, cost-effective and scalable platform for addressing the intensive computing demand in planning studies, this platform made using Amazon Web service as easy as using on-premises computers by completely automating the access to cloud based resources. This frees ISO engineers to focus on power system analysis, and thus significantly increased their productivity. To accommodate simulation jobs with varying urgency requirements, this platform allows the users to make the tradeoff between cost and completion time. The platform also further strengthened its support for cyber security and data privacy.

Uniting for Energy Democracy in South Africa

28 | International Union Rights | 26/4 FOCUS | CLIMATE CHANGE & TRADE UNIONS The South African electricity industry is in crisis. Although peak electricity demand reaches only 60 percent of installed generating capacity, there have been periodic episodes of ‘load shedding’ since 2008 when public utility Eskom was unable to meet peak demand and had to implement rotational cut-offs to avoid total blackout. This escalating crisis reached further unprecedented levels in December 2019. With electricity prices having increased by 356 percent over the last ten years and 43 percent of people considered ‘energy poor’, this latest episode of load shedding was met by a massive public outcry. Government response measures aiming to tackle Eskom’s capacity shortfalls have so far have been successful. In a country with excellent solar and wind resources, the obvious solution to increasing access to affordable electricity, increasing supply and reducing emissions is to tap into renewable energy sources. But currently coal provides an estimated 83 percent of South Africa’s total generating capacity. The coal-dominated energy sector also provides many with jobs and livelihoods, especially within low-income and black majority communities. Renewable energy has been introduced to the country through the Renewable Energy Independent Power Producers Programme (REIPPPP), but the privatised nature of this electricity generation has been opposed by the National Union of Mineworkers (NUM) and National Union of Metalworkers of South Africa (NUMSA). REIPPPP is a manifestation of an overall shift to neoliberal policies taking place since the late 1980s – including the corporatisation of Eskom that precipitated the utility’s increasingly unsustainable and precarious financial and governance situation. Given the myriad financial and governance problems that currently plague the South African energy system, and the current deadlock between unions and the government, the possibility of both turning Eskom into a leader in renewable energies and retaining its vertically integrated utility status will be extremely challenging. Far less attention has been paid to the role that local governments can play in relation to renewables and just transition. Municipalities, in their constitutionally sanctioned function as electricity distributors, already occupy a central position in South African energy distribution. In addition, energy sourced from renewables lends itself well to a decentralised and locally managed system of generation and distribution. Thus, getting Eskom and local governments to combine their efforts to roll out renewable energy appears as a potentially viable and effective way of increasing access to clean, affordable electricity. The idea is not to prevent community organisations, cooperatives and other forms of smallscale ownership from playing their part in renewable energy development but rather to insert these smaller entities into a well-coordinated and publicly run energy sector so as to ensure equitable, reliable and affordable access to clean energy. Eskom and local governments would subsequently be tasked with overseeing and running the process. While both the government and trade unions frequently express their commitment to renewables and refer to the just transition concept, their conflicting understandings of transition have led to paralysis. Securing a just transition to a low-carbon energy system must involve more than simply helping energy workers and their communities to transition away from coal; it must also guarantee adequate access to clean energy for all. Local governments could potentially form the basis for such a low-carbon and people-centred electricity system. However, for this to happen will require breaking the current deadlock and a radical shift in the existing power dynamics around electricity in South Africa. It will also require a concerted effort to strengthen Eskom and local government institutionally and financially. The transition to a more socially, environmentally and politically just electricity system will only happen when trade unions, environmental groups, women’s groups, youth groups and frontline community organisations unite around a common vision of a people’s energy system. Uniting for Energy Democracy in South Africa SANDRA VAN NIEKERK researches energy transitions and energy democracy with the Alternative Information & Development Centre (AIDC) Energy democracy is the only way to break the deadlock between government and unions over South Africa’s electricity crisis The NUM and NUMSA have been working in partnership with Trade Unions for Energy Democracy (TUED), the Transnational Institute and AIDC under the banner of a...

Modelling and performance of an automated small hybrid plant

Small rivers that can generate useful quantities of electricity are freely and proportionally distributed in Africa. Thousands of potential sites are available in South Africa, capable of generating hundreds of megawatts. Small hydropower generation is not a new approach in this part of the world, as many nearby countries are embarking it.This research proposes a generic model of a complete hybrid hydropower plant. The plant combines a river run-off unit and a pumped storage unit to form a complete standalone power plant for rural communities. The river run-off unit in the design generates power continuously for 24 hours while the pumped storage is filled at low consumption periods from power generated by the river run-off unit, to be released in peak periods to meet consumers’ immediate electricity load needs. The plant is operated using a microchip control model. It is projected that the plant will be able to meet peak demand power needs, and can be implemented in typical farm settlement and suburban communities in Africa.

Identifying energy efficiency improvements and savings potential in Croatian energy networks

Croatian 10-year distribution network development plan (2016–2025) is characterised by peak-driven network design in which the network is primarily developed and designed to meet peak demand in a safe and reliable manner and in which losses have been considered more as a consequence of design and operational management decisions, rather than and explicit development criteria. Faced with the requirement from the article 15 of the Energy Efficiency Directive, in 2015 Croatian regulatory authority launched the vast study in order to examine the opportunities of making distribution network more energy efficient within the framework of the approved investments from 10-year plan. Based on the outcomes of the study, in this study key measures for increasing energy efficiency (EE) and their EE potential are presented.