Maximisation and optimisation of solar PV generation with limited grid capacity through the adoption of new technologies

To achieve the UK's target of reducing carbon emissions by 80% of 1990 levels by 2050, it is widely accepted that the decarbonisation of the UK's electricity network is the most cost-optimal route.

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Jul 20, 2017
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Authors: James P. Hoare  and  Laura A. Jones 

Abstract

As coal-fired power stations are decommissioned and the development of nuclear power stations face continued political challenges, the UK is facing an ‘energy gap’ and renewable technologies such as solar photovoltaic (PV) must play a bigger role. The introduction of incentive schemes resulted in a rapid adoption of low-carbon technologies; however, as a consequence the electricity network is under considerable strain. New distributed generation (DG) projects are faced with high reinforcement costs and export constraints. Nonetheless, the adoption of DG systems is essential for the country's future energy supply. In light of grid capacity issues, innovative solutions within the solar PV sector including generation maximisation and optimisation offer solutions to grid-connectivity issues.

Introduction

Background

Following the enactment of the 2008 Climate Change Act [1], which sets out legally binding carbon reduction targets, the UK Government released its 2009 White Paper on ‘The UK Low Carbon Transition Plan’ [2]. The Plan identified the mechanisms required to achieve a low-carbon future and a key focus was placed on energy generation. The White Paper outlined that by 2020 40% of the UK's electricity was to be sourced from low-carbon technologies and that ‘clean energy cash-back schemes’ were to be introduced to encourage their adoption. In 2009, the Renewable Energy Directive sets out targets for 15% of the UK's energy consumption to be sourced from renewable technologies by 2020. In April 2010, the feed-in Tariff (FiT) was introduced and the owners of renewable technologies began receiving financial payments for the generation and export of renewable energy.

Since the introduction of FiTs and other incentive schemes, the cumulative installed renewable electricity capacity of the UK was 32.5 GW at the end of the second quarter of 2016, a 13.8% increase compared with a year earlier. Electricity generated from solar PV accounted for 33% of all renewable energy capacity at ∼10.7 GW [3].

The rapid adoption of low-carbon technologies has put the electricity distribution network under considerable strain. Historically, the UK's electricity network distributed electricity from centralised power stations to decentralised consumers; however, in recent years there has been a shift toward non-uniform distributed generation (DG) and governmental policy signals suggest a continuing trend in the decentralisation of electricity generation. This poses a number of different challenges for the distribution and transmission operators as significant investment is required to ensure that customer demands are met without adversely compromising the quality and security of supply and distribution [4].

The National Grid Company (NGC) and local distribution network operators (DNOs) have a duty under the Electricity Act to provide grid-connection capacity to renewable energy customers. However, the rapid growth in DG over a short time period has resulted in the electricity network becoming constrained or at capacity [5]. As a consequence, new DG projects are faced with network reinforcement and upgrade works most of which are subject to high capital costs and long delays, resulting in many projects becoming unviable.

Despite limited grid capacity, the development of new renewable energy projects is necessary for the UK's future energy supply and their adoption is essential. Many of the UK's coal-fired power stations are due for closure by 2025, proposals for new nuclear power stations are plagued by delays, and all the while energy demand continues to grow. The UK is facing a potential supply gap of 40–55%, depending on wind levels [6]. Renewable energy technologies including solar PV are expected to play a crucial role in the UK's energy mix as the country strives to meet demands and improve energy security.

Decarbonising the electricity network

In the Climate Change Act of 2008, the UK Government committed to reducing its carbon emissions by at least 80% of 1990 levels by 2050 and the decarbonisation of the electricity network is seen as the most cost-optimal route [7].

The carbon dioxide (CO ) contributions of coal-fired power stations and Combined Cycle Gas Turbines are estimated to be ∼846 and 488 gCO eq/kWh, respectively, compared with 88, 20 and 26 gCO eq/kWh for solar PV, wind and nuclear power, respectively [8]. The UK is working toward a decarbonised future and both nuclear power renewable technologies are poised to play a greater role in the country's energy mix.

NGC future energy scenarios

The NGC's Future Energy Scenarios report [7] identifies three key technologies required to achieve decarbonisation: nuclear power, renewables and carbon capture and storage. It acknowledges that at least two of the three technologies are required and both nuclear power and renewables appear to have the strongest political backing.

In recent years however, the development of new nuclear power stations has been markedly slow. The development of new nuclear power stations such as Flamanville in France and Olkiluoto 3 in Finland have been plagued by construction delays and cost over runs. In light of the UK, recent decision to leave the European Union there is currently some doubt regarding the advancement of the European pressurised reactor programme. In the event that the UK cannot develop nuclear power stations in the coming years, an onus will be placed on demand reduction and renewable energy.

Incentive schemes and grid capacity

The introduction of renewable energy incentive schemes such as FiT and renewables obligations (ROs) resulted in a sudden uptake in renewable energy systems which resulted in a dramatic decrease in equipment and installation costs, particularly within the solar PV industry. As costs decreased, exceptional returns on investment (ROI) could be achieved and the solar PV market in the UK exploded.

An inadvertent consequence of the sudden rush for solar PV was that large sections of the electricity network, particularly in the South of the country, have today become saturated with consented renewable energy projects, limiting the ability of the network to accommodate more projects.

In 2016, tariff rates for solar PV were reduced and a far more rigorous review of projects is required to ensure feasibility. In particular, a greater emphasis is placed on imported electricity alleviation where offsetting imported electricity costs is given greater weighting.

In the face of a probable energy supply gap, the development of renewable energy schemes such as solar PV is paramount, yet grid-connection issues pose considerable time delays and challenges.

Grid-connection process

The UK's electricity network is split into two distinct areas: the high-voltage transmission network, operated by NGC and the distribution network, operated by DNOs.

To obtain grid-connection for solar PV systems (of system size >16 A per phase), a grid-connection application must be submitted to the local DNO and a network analysis is conducted to assess its impact on the network.

The connection of a DG system and the subsequent power flow through export can cause the network to become more dynamic and unpredictable and key areas of concern to the DNOs include:

  • i. Voltage rise – electricity safety, quality and continuity regulations: Electrical equipment installed in the European Union (EU) must operate between 216.2 and 253 V. The DNO grades the electrical system at 11 kV and below therefore over the course of a year, the supply voltage will remain within the 216.2 and 253 V range. Localised DG causes the voltage to rise and should the voltage exceed 253 V the local DNO would be in breach of its conditions of supply licence. Therefore, in the event that the network analysis indicates a voltage rise beyond the operational range as a consequence of a DG connection, network upgrades or generation constraints maybe imposed.
  • ii. Exceedance of thermal limit: DG can cause the thermal limit of a cable to be exceeded due to the heating effect caused by electrical losses, causing a cable or an overhead line's rated capacity to be exceeded.
  • iii. Reverse power flows: DG can cause energy to flow in the opposite direction from the consumers, necessitating expensive protection upgrades at the DNO and NGC interfaces.
  • iv. Fault level contributions: DG can contribute to fault levels by causing the highest current that can exist in a particular system under short-circuit conditions to be exceeded. This can necessitate expensive switchgear upgrades.
  • v. Power quality: DG can adversely affect the quality of the voltage and the fitness of the electrical power to consumer devices (harmonics in particular). Resonance of the network where the natural frequency of capacitive and inductive elements of the network can cause extreme voltages due to the harmonic content [5].

Active networks and smart grids are poised to become central to future networks; currently, there is limited control of the 11 kV and low-voltage networks. As such, the DNO must appraise the impact of a new DG scheme under the worst-case scenario, i.e. all locally connected DG schemes are simultaneously generating at peak outputs.

In the event that the network analysis finds that the connection will adversely impact the network, reinforcement works must be undertaken prior to grid-connection. The costs of the reinforcements works are borne by the customer. Increasingly, the high capital costs and long lead times delay or cancel the development of solar PV systems, yet their role in the country's future energy mix has never been so important.

As the transmission and DNOs work to modernise the electrical grid, technological innovations within the solar PV industry are working to overcome grid capacity issues by maximising and optimising generation.

System maximisation – export limiting and demand against generation modelling

The development of a solar PV system depends on numerous factors including location, local demand, available area, capital costs, tariff rates and ROI. Grid-connection costs can impact the viability and the profitability of a system and the customer may request the maximum allowable capacity without reinforcement works. In some cases, the project remains viable at a lower capacity; however, in many cases the project will become unfeasible.

Despite the barriers to grid-connection, through demand against generation modelling and export limiting technologies system size and on-site consumption of solar energy can be maximised.

In recent years, the development of solar PV systems has predominantly centred on revenue maximisation and little consideration was given to demand profiles. As grid capacity becomes scarcer, the focus has shifted toward the maximisation of generation and consumption, as well as fuel cost savings.

Recently, developed simulation software packages offer features whereby solar PV systems can be appropriately sized for optimal on-site consumption where export constraints are present. This is achieved by modelling half-hourly (HH) generation data against HH consumption data.

The fundamental enabler behind this methodology is that the capacity factor of solar PV is low (circa 11% based on 24 h and 22% based on hours of operation) and if there is a quantified on-site demand, significantly larger systems can be installed with a small amount of generating constraint.

Capacity factor

Capacity factor is a measure of how much energy is produced by a plant compared with its maximum output. It is measured as a percentage, generally by dividing the total energy produced during a period of time by the amount of energy the plant would have produced if it ran at full output during that time [ ].

Typically, a wind turbine will have a capacity factor of 25–35%, whereas a solar PV system will have a capacity factor of 11% (24/7) and 22% (when operational). Fig illustrates the monthly generation profile of a solar PV system. The same data can be further transposed to represent solar PV generation as a percentage of maximum output (Fig 2).

Fig 1: Monthly generation profile of a solar PV system

Fig 2: Solar PV generation as a percentage of maximum output

Constrained generation – an example

Projects with on-site demand located in areas of limited or zero export capacity can install solar PV systems with constrained generation and by modelling HH generation data against HH consumption data the appropriate solar PV system size can be determined.

Table summarises the level of generation constraint for range of solar PV system sizes for a site located in Corby, England with a 100 kW demand and a zero export capacity [solar PV (kWp) to inverter (kVA) output ratio of 1.23 has been assumed for modelling purposes].

SOLAR PV SYSTEM SIZE, KWPMAXIMUM INVERTER OUTPUT, KVAOUTPUT AS PROPORTION OF MAXIMUM, >#/TH###GENERATION CONSTRAINT, >#/TH###
100811000
150122991
160130982
170138964
180146955
190154946
200163928
2502038515
3002447822

Table 1: Percentage generation constraint for a site with 100 kW demand and zero export capacity

The results illustrate that a 200 kWp solar PV system installed at the site will only be constrained by 8% over a typical year.

A similar assessment of a domestic property indicates that a 2 kWp solar PV system with a zero export capacity and a 200 W minimum baseload demand would result in 58% of the energy generated being consumed locally. A 1 kWp system would result in 85% of the energy generated being consumed locally.

Whilst it is possible to constrain generation using modern solid-state inverters, this is achieved by operating the inverters inefficiently. It is preferable to optimise the size of the system for on-site demand.

Optimisation – module optimiser technology

String inverters

Solar PV modules (or ‘panels’) generate direct current (DC) and as solar irradiance levels fluctuate, the power generated continually varies. Modules are typically connected in series to form ‘strings’ with the strings connected to inverters that convert DC to alternating current (AC) for on-site consumption or export. The lengths of the strings are determined by the voltage rating of the inverter and in some cases can exceed 1000 V .

Fig.  illustrates a typical current–voltage curve for a solar PV module. The curve indicates that at the point of short-circuit current, the voltage is zero and the resulting power will also be zero. Similarly, at the point of open-circuit voltage, the current is zero and the resulting power will also be zero. There is a point on the curve where both the current and voltage are at their maximum, equating to a point at which the power is also at its maximum, commonly referred to as the ‘maximum power point’ (MPP).

Fig 3: Solar PV module – current–voltage curve

String inverters have been the preferred inverter technology type since the outset of grid-connected PV systems. They continually track the power output of the strings, varying the load to in order to attain the MPP. The process is commonly referred to as ‘MPP tracking’ (MPPT). The voltage of a string will fluctuate as the load is varied to attain the MP.

The principal disadvantage associated with tracking the MPP of a string is that regardless of the effectiveness of the MPPT software, the output of the string will always be limited by the poorest performing module.

Many factors can cause a module to underperform and on a visible level a common cause is shading. Full or partial shading reduces the output of the module, and if the module forms a part of a string the output of the whole string will be reduced to that of the shaded module.

There are however other, less visible factors that can also impact the performance of a module and the respective string, these include: faulty cells, bypass diode failure, junction box failure, poor connections, module degradation rates, module mismatch and soiling losses. All these issues will result in a drop in output, and over the lifetime of the system (normally assumed to be 25 years) the effects will be compounded. Furthermore, it is difficult to identify an underperforming module as the inverter is only capable of monitoring the string as a whole.

Module optimisers

Module optimiser technology overcomes the limitations of inverter optimised stringed systems by individually optimising the MPP of each individual module, as opposed to a whole string of modules.

Optimisers are DC–DC converters that are either connected externally to each module or incorporated into the module at the manufacturing stage. The optimisers are strung in series and are connected to the inverters.

The standard PV module used today is typically comprised of 60 cells and rated at 270 Wp, with three bypass diodes for each group of 20 cells connected in series.

When a cell within a module is shaded, the current generated will be lower than that of the other unshaded cells within the same module. Cells are connected in series, and as a consequence the shaded cell will be forced to operate at the higher current of the unshaded cells. However, operating at this increased current will result in a negative voltage, causing the cell to consume power which is dissipated as heat (resulting in ‘hot spots’).

Bypass diodes attempt to minimise the dangers associated with ‘hot spots’ by allowing the current to flow around the shaded cell. However, this also bypasses other cells within the string.

When considering a partially shaded module in a string configuration, a standard string inverter can only optimise the MPP of the string as a whole, and many works by reducing the current so that all modules produce power, but at a lower output.

Module optimisers decrease the output voltage of a shaded panel and increase the output current in order to eliminate any mismatch in current between shaded or unshaded modules. This allows the shaded module to produce power at lower levels without the need for the bypass diode to conduct [10].

Unlike a non-optimised string inverter, MPPT at a module level allows the inverter to maintain a fixed string voltage. This optimises the inverter's DC–AC conversion and works to maintain maximum efficiencies during operation. In addition, this allows longer string lengths to be used compared with that of a non-optimised string inverter, a factor which can be particularly advantageous for improved design, installation flexibility and balance of system savings (upfront costs associated with a PV system, excluding the module).

A study conducted by the National Renewable Energy Laboratory [10] found that the adoption of module optimisers can result in improved performances compared against un-optimised systems. Testing indicated that under a range of shading scenarios, annual performance increases of between 10 and 17% can be realised for rooftop systems under a range of shading scenarios, and up to 2% for commercial systems with 3% shading.

Communications and monitoring

Some module optimiser manufacturers incorporate hardwired communications into the optimiser system, enabling remote monitoring of a module's performance. Not only does this result in making routine and reactive maintenance more effective, but it is especially beneficial over the lifetime of a system, as without such monitoring, underperforming or faulty modules can be difficult to identify.

Multiple facing roofs

In the northern hemisphere, the optimal orientation for solar PV systems is South facing roofs. Many domestic properties however have East/West facing roofs and as energy demand is typically largest in the early mornings and late afternoons, bifacial solar PV arrays offsetting imported electricity are ideal contexts for optimiser technology as generation is maximised regardless of orientation.

Optimising poor installations

The generous ROI offered from the FiT scheme prompted a rush by both clients and installation companies to install PV systems. Regrettably, this left many sub-optimally designed systems installed across the country. The retrofit of module optimiser technology could improve energy yields significantly for string inverter systems that are subject to heavy shading, as illustrated in Fig 4.

Fig 4: Existing solar PV system subject to heavy shading from adjacent wall

Fig 5: Energy profile of a solar PV system coupled with on-site battery storage (image: Building Research Establishment (BRE) National Solar Centre, ‘Batteries with Solar Power’)

Fig 6: 436.44 kWp solar PV system installed at BSkyB's new HQ building System size: 436.44 kWp Technology: 1372 optimisers 31×17 kW inverters

Fig 7:

248.40 kWp solar PV system installed at Lilford Lodge, Northampton

System size: 248.40 kWp

Technology: 480 dual optimisers

15×16 kW inverters

Fig 8: Lilford Lodge generation profile for 6th June 2016

Fig. 9

Fig 9: 23.4 kWp solar PV system installed at Rye Harbour

System size: 23.4 kWp

Technology: 90× optimisers

4×5 kW inverters

1× export limiting device

Fig 10: Daily solar production and self-consumption profile against times for the solar PV system installed at Rye Harbour

Fire safety

Module optimiser technology not only offers improved system design flexibility, performance and monitoring, it also offers improved safety features. In the event of a fire, it is normal practise for the Fire Brigade to cut-off a building's power supply; however, if a non-optimised solar PV system is present on-site, the PV modules will continue to generate DC voltage regardless of whether the AC supply has been isolated. Depending on string lengths, voltages of up to 1000 V can be generated, posing significant safety risks for firefighters. In recent years, there have been media reports, in which Fire Departments in the USA have refused to fight fires due to the presence of solar PV systems and concerns for the safety of the firefighters [11].

Module optimisation equipment is able to mitigate the risks posed to firefighters by reducing the DC voltages to safe levels. The mechanisms by which the voltages are reduced vary based on the optimiser manufacturer.

Optimisation of long-term performance and maximising return on investment

The power output of solar PV modules degrades over time and the rate of degradation will vary from module to module. Differing rates of degradation over a long-term period will be compounded if MPPT is conducted at an inverter level; however, should optimisation take place at a module level the impact of the degradation is isolated. This will result in maximised generation and ROI.

Note on future proofing

The price paid for exported energy from solar PV systems is lower than the cost of imported energy (with commercial users typically paying between £0.07 and £0.12/kWh and domestic users paying £0.14/kWh). Energy storage costs are falling significantly as a consequence of the economies of scale associated with global manufacturing. The need to minimise the export is driving the adoption of on-site energy storage. This is a major step to overcome the intermittency issues associated with renewable energy technologies.

Fig.  illustrates the energy profile of a solar PV system coupled with battery storage. A standard solar PV system, with no energy storage generates electricity during daylight hours and the electricity is either consumed locally or exported. Peak electricity demand in the UK typically occurs during the evening periods and this commonly coincides with periods where the solar PV system does not generate.

Fig. 11

Fig 11: 2.35 MWp solar PV system installed at Ingarsby

System size: 2.35 MWp

Technology: 7446×315 Wp solar PV modules with embedded optimisers

73×27 kW inverters

The adoption of battery storage systems can assist in delivering electricity during these peak periods, alleviating the impact of peak demand periods on the distribution network.

Fig.  illustrates a typical daily profile of a solar PV system with a battery energy storage system. The image illustrates how excess generation (yellow curve) which would typically be exported to the grid is diverted to a battery for consumption at a later time, when the system has ceased generating.

Conclusions

For the UK to achieve its target of reducing its carbon emissions by at least 80% of 1990 levels by 2050, it is widely accepted that the decarbonisation of the electricity network is the most cost-optimal route. Nuclear power and renewables appear to have the strongest political backing; however, the development of nuclear power stations continues to face numerous challenges. As coal-fired power stations are decommissioned, the UK is facing an ‘energy gap’ and renewable technologies such as solar PV must play a bigger role in the country's energy mix.

The introduction of incentive schemes such as FiT and ROs resulted in a rapid adoption of low-carbon technologies; however, as a consequence, the electricity distribution network has been put under considerable strain. The grid-connection of DG systems such as solar PV result in issues such as voltage rise, thermal limits, reverse power flows, fault level contributions and power quality. As a consequence, new projects are faced with either high reinforcement costs or export constraints. Nonetheless, the adoption of DG systems is essential for the country's future energy supply. Innovative methodologies and technologies, specifically within the solar PV sector, are offering solutions to grid-connection issues.

The maximisation of generation is one key solution. As grid capacity becomes scarcer, the focus has shifted toward the maximisation of generation and consumption, as well as fuel cost savings.

New software that models HH generation data against HH consumption data enables solar PV systems to be appropriately sized for optimal on-site consumption where export constraints are present. The modelling software allows the level of generation constraint to be selected without the need for inefficient generation constraints at the inverter level.

The optimisation of solar PV systems also offers benefits over the long term, maximising generation and performance.

Module optimiser technology overcomes some of the limitations of inverter optimised stringed systems by individually optimising the MPP of each module. Optimisation allows inverters to operate at maximum efficiencies and offers a number of benefits including improved design, balance of system savings, installation flexibility, fire safety and the optimisation of existing solar PV systems through retro-fitting. Furthermore, annual performance improvements can be realised through the use of module optimisers.

A common criticism of DG systems is that of intermittency. However, as storage systems become economically viable, the coupling of maximised and optimised solar PV systems with battery storage will become commonplace, forming an essential component in the UK's decarbonised energy mix.

References

  1. Climate Change Act 2008, Chapter 27, London: The Stationary Office .
  2. ‘National strategy for climate and energy’ (The Stationary Office, 2009), p. 4, London, UK .
  3. Department for Business, Energy & Industrial Strategy: ‘Energy trends section 6: renewables’ (BEIS, 2016), London, UK.
  4. EA Technology Ltd.: ‘Assessing the impact of low carbon technologies on Great Britain's power distribution networks’ (EA Technology Ltd., 2012), p. 3, Chester, UK.
  5. Energy Networks Association: ‘Connecting community energy. A guide to getting a network connection’ (ENA, 2015), p. 8, London, UK.
  6. ‘Engineering the UK electricity gap’ (IMechE, 2016), p. 2, London, UK .
  7. National Grid Company: ‘ Future energy scenarios’ (NGC, 2016), p. 9, Warwick, UK .
  8. Parliamentary Office of Science and Technology: ‘ Carbon footprint of electricity generation’ (POST, 2011), London, UK.
  9. National Renewable Energy Laboratory: ‘Solar energy and capacity value’ (NREL, 2013), p. 1, Golden, USA.
  10. National Renewable Energy Laboratory: ‘A performance and economic analysis of distributed power electronics in photovoltaic systems’ (NREL, 2011), Golden, USA.
  11. Allianz Risk Consulting: ‘Understanding the fire hazards of photovoltaic systems’ (Allianz Global Corporate & Specialty AG, 2012), p. 2, Munich, Germany.

Case study 1 – British Sky Broadcasting Group (BSkyB) New Headquarters (HQ) Building

Arup, the main consulting engineer for the development of BSkyB's new headquarters (shown in Figure 6) specified the requirement for fire alleviation technology to be incorporated into the design of the 436.44 kWp solar PV system. Following a review of the available fire alleviation options and their respective benefits, module optimiser technology was specified throughout.

As a new build project with a high focus on sustainability, the development was set a high Building Research Establishment Environmental Assessment Method target and consequently a large solar PV system was required. Owing to the presence of a number of roof lights, edge protection and six large services cores on the roof, the design was complex and the system was subject to significant levels of shading. Optimiser technology not only offered improved fire safety benefits, but it also offered improved system outputs and long-term performance.

Case study 2 – Lilford Lodge

The owner of a 300-acre mixed-use farm and business park located in East Northamptonshire had ambitious plans to develop a site into a low-carbon mixed-use hub including agriculture and recreational activities.

The first step in the development was the installation of a solar PV system to generate low-carbon electricity for on-site consumption. Owing to limited export capacity and high connection costs, the desired system size was determined unfeasible and the system size had to be reduced to 250 kWp.

A 248.40 kWp system (shown in Figure 7), connected to an 11 kV private wire network, was selected to synergistically maximise generation and on-site consumption and a sun tracked framing system was selected to provide additional generation during morning and afternoon periods. The single axis tracker system was selected due to the technology being a mechanically proven and robust solution less vulnerable to mechanical stresses compared with dual axis solutions.

Dual module optimiser technology was chosen in order to maximise the system yields and the modules were paired according to flash test results, minimising module mismatch losses.

The combination of single axis trackers, module optimisers and module tolerance pairing has to date realised a 28% improvement in specific yield per year (kWh/kWp/year). An example of the daily generation profile of the system is shown in Figure 8.

The owner took an interest in new innovation led technologies with the primary target of maximising the energy generated. Future plans include a ground source heat pump and a pumped storage hydro scheme to provide demand side management with autonomy outside of daylight hours.

About 2 years on the system is one of the best performing systems in the UK demonstrating that through the adoption of innovative technologies and careful design, generation can be maximised despite limited grid-connection capacity.

Case study 3 – Rye Harbour

The main objective of the project was to generate renewable energy for on-site consumption and provide additional revenue through FiT payments for a maximum budget allowance of £25,000.

The site had a split phase 20 kVA transformer with a 10 kVA feed to the campus. A grid-connection application was submitted to the local DNO for the connection of a 25 kW system with a request for an upgrade to a three phase supply. A quotation of £30,000 was received for undertaking the upgrade works, exceeding the total project budget.

Following discussion with the DNO, it was apparent that the existing transformer could however accommodate a lower export capacity of 10 kW. Export constraint modelling was undertaken indicating that a 10 kVA export limited system with 90% non-constrained generation output was viable.

The system, shown in Figure 9, was installed and commissioned in March 2015 and to date the system has generated 33.5 MWh. Without constraint the generation has been estimated to be 35.6 MWh. The level of constraint is 6%. Figure 10 illustrates the daily production and on-site consumption profile for the system. Much of the Rye Harbour energy consumption is harbour lighting which comes on after dark. As such the adoption of on-site energy storage is envisaged in the near future and the technology selected facilitated future developments for the 100% use of generated power.

Case study 4 – Ingarsby

Figure 11 illustrates a 2.35MWp project, where innovative energy harvesting was adopted, and consequently the energy generation over the lifetime of the project will be significantly higher, and the operational costs lower. A particular feature of the project is that there is currently a minimum import price on PV modules from China, but there is an exception for embedded technology within the module. By adopting module-based optimisers, the true price of the modules/optimisers was realised, and consequently the capital cost capital expenditure (CAPEX) of the PV farm was lower than an equivalent string inverter system, and additionally the yield (revenue) will be higher and the operational costs operational expenses (OPEX) lower.

Go to the profile of James Hoare

James Hoare

Electrical and energy engineers, LHW Partnership LLP

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